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The fragmentation properties of jets containing $b$-hadrons are studied using charged $B$ mesons in 139 fb$^{-1}$ of $pp$ collisions at $\sqrt{s} = 13$ TeV, recorded with the ATLAS detector at the LHC during the period from 2015 to 2018. The $B$ mesons are reconstructed using the decay of $B^{\pm}$ into $J/\psi K^{\pm}$, with the $J/\psi$ decaying into a pair of muons. Jets are reconstructed using the anti-$k_t$ algorithm with radius parameter $R=0.4$. The measurement determines the longitudinal and transverse momentum profiles of the reconstructed $B$ hadrons with respect to the axes of the jets to which they are geometrically associated. These distributions are measured in intervals of the jet transverse momentum, ranging from 50 GeV to above 100 GeV. The results are corrected for detector effects and compared with several Monte Carlo predictions using different parton shower and hadronisation models. The results for the longitudinal and transverse profiles provide useful inputs to improve the description of heavy-flavour fragmentation in jets.
Longitudinal profile for 50 GeV < pT < 70 GeV.
Transverse profile for 50 GeV < pT < 70 GeV.
Longitudinal profile for 70 GeV < pT < 100 GeV.
Transverse profile for 70 GeV < pT < 100 GeV.
Longitudinal profile for pT > 100 GeV.
Transverse profile for pT > 100 GeV.
Average longitudinal profile
Transverse profile for pT > 100 GeV.
A measurement of the top-quark mass ($m_t$) in the $t\bar{t}\rightarrow~\textrm{lepton}+\textrm{jets}$ channel is presented, with an experimental technique which exploits semileptonic decays of $b$-hadrons produced in the top-quark decay chain. The distribution of the invariant mass $m_{\ell\mu}$ of the lepton, $\ell$ (with $\ell=e,\mu$), from the $W$-boson decay and the muon, $\mu$, originating from the $b$-hadron decay is reconstructed, and a binned-template profile likelihood fit is performed to extract $m_t$. The measurement is based on data corresponding to an integrated luminosity of 36.1 fb$^{-1}$ of $\sqrt{s} = 13~\textrm{TeV}$$pp$ collisions provided by the Large Hadron Collider and recorded by the ATLAS detector. The measured value of the top-quark mass is $m_{t} = 174.41\pm0.39~(\textrm{stat.})\pm0.66~(\textrm{syst.})\pm0.25~(\textrm{recoil})~\textrm{GeV}$, where the third uncertainty arises from changing the PYTHIA8 parton shower gluon-recoil scheme, used in top-quark decays, to a recently developed setup.
Top mass measurement result.
List of all the individual sources of systematic uncertainty considered in the analysis. The individual sources, each corresponding to an independent nuisance parameter in the fit, are grouped into categories, as indicated in the first column. The second column shows the impact of each of the individual sources on the measurement, obtained as the shift on the top mass induced by a positive shift of the each of the nuisance parameters by its post-fit uncertainty. Sources for which no impact is indicated are neglected in the fit procedure as their impact on the total prediction is negligible in any of the bins. The last column shows the statistical uncertainty in each of the reported numbers as estimated with the bootstrap method.
Ranking, from top to bottom, of the main systematic uncertainties (excluding recoil) showing the pulls and the impact of the systematic uncertainties on the top mass, from the combined opposite sign (OS) and same sign (SS) binned-template profile likelihood fit to data. The OS or SS refers to the charge signs of the primary lepton and the soft muon. The gamma parameters are NPs used to describe the effect of the limited statistics of the sample.
Correlation matrix for the individual sources of systematic uncertainty considered in the analysis, for the combined opposite sign (OS) and same sign (SS) binned-template profile likelihood fit to data. The OS or SS refers to the charge signs of the primary lepton and the soft muon. The gamma parameters are NPs used to describe the effect of the limited statistics of the samples.
This paper presents a measurement of the electroweak production of two jets in association with a $Z\gamma$ pair, with the $Z$ boson decaying into two neutrinos. It also presents a search for invisible or partially invisible decays of a Higgs boson with a mass of 125 GeV produced through vector-boson fusion with a photon in the final state. These results use data from LHC proton-proton collisions at $\sqrt{s}$ = 13 TeV collected with the ATLAS detector and corresponding to an integrated luminosity of 139 fb$^{-1}$. The event signature, shared by all benchmark processes considered for the measurements and searches, is characterized by a significant amount of unbalanced transverse momentum and a photon in the final state, in addition to a pair of forward jets. Electroweak $Z\gamma$ production in association with two jets is observed in this final state with a significance of 5.2 (5.1 expected) standard deviations. The measured fiducial cross-section for this process is 1.31$\pm$0.29 fb. An observed (expected) upper limit of 0.37 ($0.34^{+0.15}_{-0.10}$) at 95% confidence level is set on the branching ratio of a 125 GeV Higgs boson to invisible particles, assuming the Standard Model production cross-section. The signature is also interpreted in the context of decays of a Higgs boson into a photon and a dark photon. An observed (expected) 95% CL upper limit on the branching ratio for this decay is set at 0.018 ($0.017^{+0.007}_{-0.005}$), assuming the Standard Model production cross-section for a 125 GeV Higgs boson.
Post-fit results for all $m_\text{jj}$ SR and CR bins in the EW $Z \gamma + \text{jets}$ cross-section measurement with the $\mu_{Z \gamma_\text{EW}}$ signal normalization floating. The post-fit uncertainties include statistical, experimental, and theory contributions.
Post-fit results for all DNN SR and CR bins in the search for $H \to \text{inv.}$ with the $\mathcal{B}_\text{inv}$ signal normalization set to zero. For the $Z_\text{Rev.Cen.}^\gamma$ CR, the third bin contains all events with DNN output score values of 0.6-1.0. The $H \to \text{inv.}$ signal is scaled to a $\mathcal{B}_\text{inv}$ of 37%. The post-fit uncertainties include statistical, experimental, and theoretical contributions.
Post-fit results for the ten [$m_\text{jj}$, $m_\text{T}$] bins constituting the SR and CRs defined for the dark photon search with the $\mathcal{B}(H \to \gamma \gamma_\text{d})$ signal normalization set to zero. A $H \to \gamma \gamma_\text{d}$ signal is shown for two different mass hypotheses (125 GeV, 500 GeV) and scaled to a branching ratio of 2% and 1%, respectively. The post-fit uncertainties include statistical, experimental, and theoretical contributions.
Post-fit $m_\text{T}(\gamma, E_\text{T}^\text{miss})$ distribution in the inclusive signal region for the dark-photon search with the 125 GeV mass $\mathcal{B}(H \to \gamma \gamma_\text{d})$ signal normalization set to zero. A $H \to \gamma \gamma_\text{d}$ decay signal is shown for two different mass hypotheses, 125 GeV and 500 GeV, and scaled to a $\mathcal{B}(H \to \gamma \gamma_\text{d})$ of 2% and 1%, respectively. Events with $m_\text{T}(\gamma, E_\text{T}^\text{miss})$ larger than the rightmost bin boundary are added to that bin.
The 95% CL upper limit on the Higgs boson production cross-section times branching ratio to $\gamma \gamma_\text{d}$ is shown for different VBF-produced scalar-mediator-mass hypotheses in the NWA. The theoretically predicted cross-section of a Higgs boson produced via VBF and with the $\mathcal{B}(H \to \gamma \gamma_\text{d}) =$ 5% is superimposed on the $\pm 1\sigma$ and $\pm 2\sigma$ NNLO QCD + NLO EW uncertainty band of the expected production cross-section limit.
Post-fit $m_\text{jj}$ distribution in the inclusive signal region. The Higgs boson invisible decay signal is scaled to a $\mathcal{B}_\text{inv}$ of 37%. Events with $m_\text{jj}$ larger than the rightmost bin boundary are added to that bin.
Post-fit $m_\text{jj}$ distribution in the one-lepton control region $W_{\ell \nu}^\gamma$ CR. Events with $m_\text{jj}$ larger than the rightmost bin boundary are added to that bin.
Post-fit $m_\text{T}$ distribution in the one lepton control region. Events with $m_\text{T}$ larger than the rightmost bin boundary are added to that bin.
Post-fit photon centrality distribution in the zero lepton signal plus control region with the $\mathcal{B}_\text{inv}$ signal normalization set to zero in the fit.
Post-fit photon $E_\text{T}$ distribution in the zero lepton signal region with the $\mathcal{B}_\text{inv}$ signal normalization set to zero in the fit.
Post-fit photon centrality distribution in the zero lepton signal plus control region resulting from the fit to the $m_\text{jj}$ distribution for EW $Z \gamma + \text{jets}$. The post-fit uncertainties include statistical, experimental, and theory contributions.
Post-fit photon $E_\text{T}$ distribution in the zero lepton signal region resulting from the fit to the $m_\text{jj}$ distribution for EW $Z \gamma + \text{jets}$. The post-fit uncertainties include statistical, experimental, and theory contributions.
Post-fit DNN output score distribution in the one lepton control region.
Yields for the EW $Z \gamma + \text{jets}$ process are shown after each selection along with relative and absolute signal acceptance efficiencies.
Yields for the 125 GeV Higgs boson with $\mathcal{B}_\text{inv.} =$ 1 signal produced by the vector boson fusion process in association with a final state photon are shown after each selection along with relative and absolute signal acceptance efficiencies.
Yields for the 125 GeV Higgs boson with $\mathcal{B}(H \to \gamma \gamma_\text{d}) =$ 1 signal produced by the vector boson fusion process are shown after each selection along with relative and absolute signal acceptance efficiencies.
This paper presents a search for decays of the Higgs boson with a mass of 125 GeV into a pair of new pseudoscalar particles, $H\rightarrow aa$, where one $a$-boson decays into a $b$-quark pair and the other into a muon pair. The search uses 139 fb$^{-1}$ of proton-proton collision data at a center-of-mass energy of $\sqrt{s}=13$ TeV recorded between 2015 and 2018 by the ATLAS experiment at the LHC. A narrow dimuon resonance is searched for in the invariant mass spectrum between 16 GeV and 62 GeV. The largest excess of events above the Standard Model backgrounds is observed at a dimuon invariant mass of 52 GeV and corresponds to a local (global) significance of $3.3 \sigma$ ($1.7 \sigma$). Upper limits at 95% confidence level are placed on the branching ratio of the Higgs boson to the $bb\mu\mu$ final state, $\mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$, and are in the range $\text{(0.2-4.0)} \times 10^{-4}$, depending on the signal mass hypothesis.
Post-fit number of background events in all SR bins (after applying the BDT cuts) that are tested for the presence of signal. The bins are 2 GeV (3 GeV) wide in mmumu for ma ≤ 45 GeV (ma > 45 GeV). Events in neighbouring bins partially overlap. Discontinuities in the background predictions appear when the BDT discriminant used for the selection changes from the one trained in the lower mass range to the one trained in the higher mass range.
Post-fit number of background events in all SR bins without applying the BDT cuts that are tested for the presence of signal. The bins are 2 GeV (3 GeV) wide in mµµ for $m_a$ ≤ 45 GeV ($m_a$ > 45 GeV). Events in neighbouring bins partially overlap. Discontinuities in the background predictions appear when the BDT discriminant used for the selection changes from the one trained in the lower mass range to the one trained in the higher mass range.
Probability that the observed spectrum is compatible with the background-only hypothesis. The local $p_0$-values are quantified in standard deviations $\sigma$.
Upper limits on $\mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ at 95% CL including the BDT cut as a function of the signal mass.
Upper limits on $\mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ at 95% CL without the BDT cut as a function of the signal mass.
The number of events when applying each cut in the analysis for $m_a$ = 16 GeV. The first row shows the approximate total number of events scaled to the theoretical signal cross-section and luminosity of the full Run 2 dataset, assuming $ \mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ = 0.16%.
The number of events when applying each cut in the analysis for $m_a$ = 20 GeV. The first row shows the approximate total number of events scaled to the theoretical signal cross-section and luminosity of the full Run 2 dataset, assuming $ \mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ = 0.16%.
The number of events when applying each cut in the analysis for $m_a$ = 30 GeV. The first row shows the approximate total number of events scaled to the theoretical signal cross-section and luminosity of the full Run 2 dataset, assuming $ \mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ = 0.16%.
The number of events when applying each cut in the analysis for $m_a$ = 40 GeV. The first row shows the approximate total number of events scaled to the theoretical signal cross-section and luminosity of the full Run 2 dataset, assuming $ \mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ = 0.16%.
The number of events when applying each cut in the analysis for $m_a$ = 50 GeV. The first row shows the approximate total number of events scaled to the theoretical signal cross-section and luminosity of the full Run 2 dataset, assuming $ \mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ = 0.16%.
The number of events when applying each cut in the analysis for $m_a$ = 60 GeV. The first row shows the approximate total number of events scaled to the theoretical signal cross-section and luminosity of the full Run 2 dataset, assuming $ \mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ = 0.16%.
A measurement of novel event shapes quantifying the isotropy of collider events is performed in 140 fb$^{-1}$ of proton-proton collisions with $\sqrt s=13$ TeV centre-of-mass energy recorded with the ATLAS detector at CERN's Large Hadron Collider. These event shapes are defined as the Wasserstein distance between collider events and isotropic reference geometries. This distance is evaluated by solving optimal transport problems, using the 'Energy-Mover's Distance'. Isotropic references with cylindrical and circular symmetries are studied, to probe the symmetries of interest at hadron colliders. The novel event-shape observables defined in this way are infrared- and collinear-safe, have improved dynamic range and have greater sensitivity to isotropic radiation patterns than other event shapes. The measured event-shape variables are corrected for detector effects, and presented in inclusive bins of jet multiplicity and the scalar sum of the two leading jets' transverse momenta. The measured distributions are provided as inputs to future Monte Carlo tuning campaigns and other studies probing fundamental properties of QCD and the production of hadronic final states up to the TeV-scale.
IRing2 for HT2>=500 GeV, NJets>=2
IRing2 for HT2>=500 GeV, NJets>=3
IRing2 for HT2>=500 GeV, NJets>=4
IRing2 for HT2>=500 GeV, NJets>=5
IRing2 for HT2>=1000 GeV, NJets>=2
IRing2 for HT2>=1000 GeV, NJets>=3
IRing2 for HT2>=1000 GeV, NJets>=4
IRing2 for HT2>=1000 GeV, NJets>=5
IRing2 for HT2>=1500 GeV, NJets>=2
IRing2 for HT2>=1500 GeV, NJets>=3
IRing2 for HT2>=1500 GeV, NJets>=4
IRing2 for HT2>=1500 GeV, NJets>=5
IRing128 for HT2>=500 GeV, NJets>=2
IRing128 for HT2>=500 GeV, NJets>=3
IRing128 for HT2>=500 GeV, NJets>=4
IRing128 for HT2>=500 GeV, NJets>=5
IRing128 for HT2>=1000 GeV, NJets>=2
IRing128 for HT2>=1000 GeV, NJets>=3
IRing128 for HT2>=1000 GeV, NJets>=4
IRing128 for HT2>=1000 GeV, NJets>=5
IRing128 for HT2>=1500 GeV, NJets>=2
IRing128 for HT2>=1500 GeV, NJets>=3
IRing128 for HT2>=1500 GeV, NJets>=4
IRing128 for HT2>=1500 GeV, NJets>=5
ICyl16 for HT2>=500 GeV, NJets>=2
ICyl16 for HT2>=500 GeV, NJets>=3
ICyl16 for HT2>=500 GeV, NJets>=4
ICyl16 for HT2>=500 GeV, NJets>=5
ICyl16 for HT2>=1000 GeV, NJets>=2
ICyl16 for HT2>=1000 GeV, NJets>=3
ICyl16 for HT2>=1000 GeV, NJets>=4
ICyl16 for HT2>=1000 GeV, NJets>=5
ICyl16 for HT2>=1500 GeV, NJets>=2
ICyl16 for HT2>=1500 GeV, NJets>=3
ICyl16 for HT2>=1500 GeV, NJets>=4
ICyl16 for HT2>=1500 GeV, NJets>=5
IRing2 covariance for HT2>=500 GeV, NJets>=2 (Table 1)
IRing2 covariance for HT2>=500 GeV, NJets>=3 (Table 2)
IRing2 covariance for HT2>=500 GeV, NJets>=4 (Table 3)
IRing2 covariance for HT2>=500 GeV, NJets>=5 (Table 4)
IRing2 covariance for HT2>=1000 GeV, NJets>=2 (Table 5)
IRing2 covariance for HT2>=1000 GeV, NJets>=3 (Table 6)
IRing2 covariance for HT2>=1000 GeV, NJets>=4 (Table 7)
IRing2 covariance for HT2>=1000 GeV, NJets>=5 (Table 8)
IRing2 covariance for HT2>=1500 GeV, NJets>=2 (Table 9)
IRing2 covariance for HT2>=1500 GeV, NJets>=3 (Table 10)
IRing2 covariance for HT2>=1500 GeV, NJets>=4 (Table 11)
IRing2 covariance for HT2>=1500 GeV, NJets>=5 (Table 12)
IRing128 covariance for HT2>=500 GeV, NJets>=2 (Table 13)
IRing128 covariance for HT2>=500 GeV, NJets>=3 (Table 14)
IRing128 covariance for HT2>=500 GeV, NJets>=4 (Table 15)
IRing128 covariance for HT2>=500 GeV, NJets>=5 (Table 16)
IRing128 covariance for HT2>=1000 GeV, NJets>=2 (Table 17)
IRing128 covariance for HT2>=1000 GeV, NJets>=3 (Table 18)
IRing128 covariance for HT2>=1000 GeV, NJets>=4 (Table 19)
IRing128 covariance for HT2>=1000 GeV, NJets>=5 (Table 20)
IRing128 covariance for HT2>=1500 GeV, NJets>=2 (Table 21)
IRing128 covariance for HT2>=1500 GeV, NJets>=3 (Table 22)
IRing128 covariance for HT2>=1500 GeV, NJets>=4 (Table 23)
IRing128 covariance for HT2>=1500 GeV, NJets>=5 (Table 24)
ICyl16 covariance for HT2>=500 GeV, NJets>=2 (Table 25)
ICyl16 covariance for HT2>=500 GeV, NJets>=3 (Table 26)
ICyl16 covariance for HT2>=500 GeV, NJets>=4 (Table 27)
ICyl16 covariance for HT2>=500 GeV, NJets>=5 (Table 28)
ICyl16 covariance for HT2>=1000 GeV, NJets>=2 (Table 29)
ICyl16 covariance for HT2>=1000 GeV, NJets>=3 (Table 30)
ICyl16 covariance for HT2>=1000 GeV, NJets>=4 (Table 31)
ICyl16 covariance for HT2>=1000 GeV, NJets>=5 (Table 32)
ICyl16 covariance for HT2>=1500 GeV, NJets>=2 (Table 33)
ICyl16 covariance for HT2>=1500 GeV, NJets>=3 (Table 34)
ICyl16 covariance for HT2>=1500 GeV, NJets>=4 (Table 35)
ICyl16 covariance for HT2>=1500 GeV, NJets>=5 (Table 36)
IRing2 covariance, complete
1-IRing128 covariance, complete
1-ICyl16 covariance, complete
A measurement of prompt photon-pair production in proton-proton collisions at $\sqrt{s}=13$ TeV is presented. The data were recorded by the ATLAS detector at the LHC with an integrated luminosity of 139 fb$^{-1}$. Events with two photons in the well-instrumented region of the detector are selected. The photons are required to be isolated and have a transverse momentum of $p_\mathrm{T,\gamma_{1(2)}} > 40(30)$ GeV for the leading (sub-leading) photon. The differential cross sections as functions of several observables for the diphoton system are measured and compared with theoretical predictions from state-of-the-art Monte Carlo and fixed-order calculations. The QCD predictions from next-to-next-to-leading-order calculations and multi-leg merged calculations are able to describe the measured integrated and differential cross sections within uncertainties, whereas lower-order calculations show significant deviations, demonstrating that higher-order perturbative QCD corrections are crucial for this process. The resummed predictions with parton showers additionally provide an excellent description of the low transverse-momentum regime of the diphoton system.
Differential cross section as a function of $p_{T,\gamma_{1}}$. The table contains the values measured in data and theory predictions from SHERPA, DIPHOX and NNLOJET.
Differential cross section as a function of $p_{T,\gamma_{2}}$. The table contains the values measured in data and theory predictions from SHERPA, DIPHOX and NNLOJET.
Integrated fiducial cross section measured in data and from different predictions.
Differential cross section as a function of $m_{\gamma\gamma}$. The table contains the values measured in data and theory predictions from SHERPA, DIPHOX and NNLOJET.
Differential cross section as a function of $p_{T,\gamma\gamma}$. The table contains the values measured in data and theory predictions from SHERPA, DIPHOX and NNLOJET.
Differential cross section as a function of $a_{T,\gamma\gamma}$. The table contains the values measured in data and theory predictions from SHERPA, DIPHOX and NNLOJET.
Differential cross section as a function of $\phi_{\eta}*$. The table contains the values measured in data and theory predictions from SHERPA, DIPHOX and NNLOJET.
Differential cross section as a function of $\pi-\Delta\phi_{\gamma\gamma}$. The table contains the values measured in data and theory predictions from SHERPA, DIPHOX and NNLOJET.
Differential cross section as a function of $|cos\theta*|^{(CS)}$. The table contains the values measured in data and theory predictions from SHERPA, DIPHOX and NNLOJET.
A measurement of four-top-quark production using proton-proton collision data at a centre-of-mass energy of 13 TeV collected by the ATLAS detector at the Large Hadron Collider corresponding to an integrated luminosity of 139 fb$^{-1}$ is presented. Events are selected if they contain a single lepton (electron or muon) or an opposite-sign lepton pair, in association with multiple jets. The events are categorised according to the number of jets and how likely these are to contain $b$-hadrons. A multivariate technique is then used to discriminate between signal and background events. The measured four-top-quark production cross section is found to be 26$^{+17}_{-15}$ fb, with a corresponding observed (expected) significance of 1.9 (1.0) standard deviations over the background-only hypothesis. The result is combined with the previous measurement performed by the ATLAS Collaboration in the multilepton final state. The combined four-top-quark production cross section is measured to be 24$^{+7}_{-6}$ fb, with a corresponding observed (expected) signal significance of 4.7 (2.6) standard deviations over the background-only predictions. It is consistent within 2.0 standard deviations with the Standard Model expectation of 12.0$\pm$2.4 fb.
The results of the fitted signal strength $\mu$ in the 1L/2LOS channel
The results of fitted inclusive ${t\bar{t}t\bar{t}}$ cross-section in the 1L/2LOS channel
Ranking of the nuisance parameters included in the fit according to their impact on the signal strength $\mu$. The impact of each nuisance parameter, $\Delta\mu$, is computed by comparing the nominal best-fit value of $\mu$ with the result of the fit when fixing the nuisance parameter to its best-fit value, $\hat{\theta}$, shifted by its pre-fit (post-fit) uncertainties $\pm \Delta\theta$ ($\pm \Delta\hat{\theta}$).
The contribution from different systematic uncertainties to the measured $t\bar{t}t\bar{t}$ production cross section, grouped in categories.
The results of the fitted signal strength $\mu$ in the 1L/2LOS and 2LSS/3L combined channel.
The results of fitted inclusive ${t\bar{t}t\bar{t}}$ cross-section in the 1L/2LOS and 2LSS/3L combined channel.
Comparison between data and prediction for the distribution of the sum of the pseudo-continuous b-tagging score over the six jets with the highest score in the 1L,$\geq$9j,$\geq$3b region before the fit.
Comparison between data and prediction for the distribution of the sum of the pseudo-continuous b-tagging score over the six jets with the highest score in the 1L,$\geq$9j,$\geq$3b region after the fit.
Comparison between data and prediction for the distribution of the sum of the pseudo-continuous b-tagging score over the six jets with the highest score in the 2LOS,$\geq$7j,$\geq$3b region before the fit.
Comparison between data and prediction for the distribution of the sum of the pseudo-continuous b-tagging score over the six jets with the highest score in the 2LOS,$\geq$7j,$\geq$3b region after the fit.
Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,$\geq$8j,$\geq$3b region before the fit.
Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,$\geq$8j,$\geq$3b region after the fit.
Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 2LOS,$\geq$6j,$\geq$3b region before the fit.
Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 2LOS,$\geq$6j,$\geq$3b region after the fit.
Comparison between data and prediction for the distribution of number of jets in the 1L,$\geq$8j,$\geq$3b region before the fit.
Comparison between data and prediction for the distribution of number of jets in the 1L,$\geq$8j,$\geq$3b region after the fit.
Comparison between data and prediction for the distribution of number of jets in the 2LOS,$\geq$6j,$\geq$3b region before the fit.
Comparison between data and prediction for the distribution of number of jets in the 2LOS,$\geq$6j,$\geq$3b region after the fit.
Comparison between data and prediction for the distribution of b-jets multiplicity in the 1L,$\geq$8j,$\geq$3b region before the fit.
Comparison between data and prediction for the distribution of b-jets multiplicity in the 1L,$\geq$8j,$\geq$3b region after the fit.
Comparison between data and prediction for the distribution of b-jets multiplicity in the 2LOS,$\geq$6j,$\geq$3b region before the fit.
Comparison between data and prediction for the distribution of b-jets multiplicity in the 2LOS,$\geq$6j,$\geq$3b region after the fit.
Comparison between data and prediction for the distribution of the BDT score in the 1L,9j,4b signal region before the fit.
Comparison between data and prediction for the distribution of the BDT score in the 1L,9j,4b signal region after the fit.
Comparison between data and prediction for the distribution of the BDT score in the 1L,9j,$\geq$5b signal region before the fit.
Comparison between data and prediction for the distribution of the BDT score in the 1L,9j,$\geq$5b signal region after the fit.
Comparison between data and prediction for the distribution of the BDT score in the 1L,$\geq$10j,3bL signal region before the fit.
Comparison between data and prediction for the distribution of the BDT score in the 1L,$\geq$10j,3bL signal region after the fit.
Comparison between data and prediction for the distribution of the BDT score in the 1L,$\geq$10j,3bH signal region before the fit.
Comparison between data and prediction for the distribution of the BDT score in the 1L,$\geq$10j,3bH signal region after the fit.
Comparison between data and prediction for the distribution of the BDT score in the 1L,$\geq$10j,4b signal region before the fit.
Comparison between data and prediction for the distribution of the BDT score in the 1L,$\geq$10j,4b signal region after the fit.
Comparison between data and prediction for the distribution of the BDT score in the 1L,$\geq$10j,$\geq$5b signal region before the fit.
Comparison between data and prediction for the distribution of the BDT score in the 1L,$\geq$10j,$\geq$5b signal region after the fit.
Comparison between data and prediction for the distribution of the BDT score in the 2LOS,7j,$\geq$4b signal region before the fit.
Comparison between data and prediction for the distribution of the BDT score in the 2LOS,7j,$\geq$4b signal region after the fit.
Comparison between data and prediction for the distribution of the BDT score in the 2LOS,$\geq$8j,3bL signal region before the fit.
Comparison between data and prediction for the distribution of the BDT score in the 2LOS,$\geq$8j,3bL signal region after the fit.
Comparison between data and prediction for the distribution of the BDT score in the 2LOS,$\geq$8j,3bH signal region before the fit.
Comparison between data and prediction for the distribution of the BDT score in the 2LOS,$\geq$8j,3bH signal region after the fit.
Comparison between data and prediction for the distribution of the BDT score in the 2LOS,$\geq$8j,$\geq$4b signal region before the fit.
Comparison between data and prediction for the distribution of the BDT score in the 2LOS,$\geq$8j,$\geq$4b signal region after the fit.
Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,8j,3bV validation region before the fit.
Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,8j,3bV validation region after the fit.
Comparison between data and prediction for the distribution of the BDT score in the 1L,9j,3bV validation region before the fit.
Comparison between data and prediction for the distribution of the BDT score in the 1L,9j,3bV validation region after the fit.
Comparison between data and prediction for the distribution of the BDT score in the 1L,$\geq$10j,3bV validation region before the fit.
Comparison between data and prediction for the distribution of the BDT score in the 1L,$\geq$10j,3bV validation region after the fit.
Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 2LOS,6j,3bV validation region before the fit.
Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 2LOS,6j,3bV validation region after the fit.
Comparison between data and prediction for the distribution of the BDT score in the 2LOS,7j,3bV validation region before the fit.
Comparison between data and prediction for the distribution of the BDT score in the 2LOS,7j,3bV validation region after the fit.
Comparison between data and prediction for the distribution of the BDT score in the 2LOS,$\geq$8j,3bV validation region before the fit.
Comparison between data and prediction for the distribution of the BDT score in the 2LOS,$\geq$8j,3bV validation region after the fit.
Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,8j,3bL control region before the fit.
Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,8j,3bL control region after the fit.
Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,8j,3bH control region before the fit.
Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,8j,3bH control region after the fit.
Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,9j,3bL control region before the fit.
Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,9j,3bL control region after the fit.
Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,9j,3bH control region before the fit.
Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,9j,3bH control region after the fit.
Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,8j,4b control region before the fit.
Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,8j,4b control region after the fit.
Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,8j,$\geq$5b control region before the fit.
Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,8j,$\geq$5b control region after the fit.
Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 2LOS,6j,3bL control region before the fit.
Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 2LOS,6j,3bL control region after the fit.
Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 2LOS,6j,3bH control region before the fit.
Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 2LOS,6j,3bH control region after the fit.
Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 2LOS,7j,3bL control region before the fit.
Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 2LOS,7j,3bL control region after the fit.
Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 2LOS,7j,3bH control region before the fit.
Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 2LOS,7j,3bH control region after the fit.
Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 2LOS,6j,$\geq$4b control region before the fit.
Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 2LOS,6j,$\geq$4b control region after the fit.
A search for the pair production of heavy leptons as predicted by the type-III seesaw mechanism is presented. The search uses proton-proton collision data at a centre-of-mass energy of 13 TeV, corresponding to 139 fb$^{-1}$ of integrated luminosity recorded by the ATLAS detector during Run 2 of the Large Hadron Collider. The analysis focuses on final states with three or four electrons or muons from the possible decays of new heavy leptons via intermediate electroweak bosons. No significant deviations above the Standard Model expectation are observed; upper and lower limits on the heavy lepton production cross-section and masses are derived respectively. These results are then combined for the first time with the ones already published by ATLAS using the channel with two leptons in the final state. The observed lower limit on the mass of the type-III seesaw heavy leptons combining two, three and four lepton channels together is 910 GeV at the 95% confidence level.
Expected background yields and observed data after the background-only fit in the SRs.
Distribution of $m_{\mathrm{T},3l}$ in the ZL SR after the background-only fit. The uncertainty on the expected number of background events includes all statistical and systematic post-fit uncertainties with the correlations between various background sources taken into account.
Distribution of $m_{\mathrm{T},3l}$ in the ZL Veto SR after the background-only fit. The uncertainty on the expected number of background events includes all statistical and systematic post-fit uncertainties with the correlations between various background sources taken into account.
Distribution of $m_{\mathrm{T},3l}$ in the JNLow SR after the background-only fit. The uncertainty on the expected number of background events includes all statistical and systematic post-fit uncertainties with the correlations between various background sources taken into account.
Distribution of $H_\text{T} + E_\text{T}^\text{miss}$ in the Q0 SR after the background-only fit. The uncertainty on the expected number of background events includes all statistical and systematic post-fit uncertainties with the correlations between various background sources taken into account.
Distribution of $H_\text{T} + E_\text{T}^\text{miss}$ in the Q2 SR after the background-only fit. The uncertainty on the expected number of background events includes all statistical and systematic post-fit uncertainties with the correlations between various background sources taken into account.
Distribution of $m_{\mathrm{T},3l}$ in the ZL-CR after the background-only fit.
Distribution of $m_{\mathrm{T},3l}$ in the Fake-CR after the background-only fit.
Distribution of $H_\text{T} + E_\text{T}^\text{miss}$ in the Q0 DB-CR after the background-only fit.
Distribution of $H_\text{T} + E_\text{T}^\text{miss}$ in the Q0 RT-CR after the background-only fit.
Expected and observed exclusion limit for the combination of the two- (from Ref. EXOT-2018-33), three- and four-lepton channels, for the type-III seesaw process with the corresponding one- and two-standard-deviation uncertainty bands, showing the 95% CL upper limit on the cross-section.
Expected and observed 95% ( $CL_s$ ) exclusion limits in the three lepton channel for the type-III seesaw process with the corresponding one- and two-standard-deviation bands, showing the 95% CL upper limit on the cross-section.
Expected and observed 95% ( $CL_s$ ) exclusion limits in the four lepton channel for the type-III seesaw process with the corresponding one- and two-standard-deviation bands, showing the 95% CL upper limit on the cross-section.
Cross-sections of signal Monte Carlo samples for each mass point considered in this analysis. Leading order cross-sections ( $\sigma_{LO}$ ) are computed by the generator and then rescaled to next-to-leading cross-sections ( $\sigma_{NLO+NLL}$ ), with their corresponding uncertainties, using information taken from Refs. C1C1 and N2C1.
Expected signal and background yields after each of the analysis selection cuts for the 800 GeV mass hypothesis in the ZL SR. Preselection represents events with at least three leptons.
Expected signal and background yields after each of the analysis selection cuts for the 800 GeV mass hypothesis in the ZLVeto SR. Preselection represents events with at least three leptons.
Expected signal and background yields after each of the analysis selection cuts for the 800 GeV mass hypothesis in the JNLow SR. Preselection represents events with at least three leptons.
Expected signal and background yields after each of the analysis selection cuts for the 800 GeV mass hypothesis in the Q0 SR. Preselection represents events with at least three leptons.
Expected signal and background yields after each of the analysis selection cuts for the 800 GeV mass hypothesis in the Q2 SR. Preselection represents events with at least three leptons.
Expected signal and background yields after each of the analysis selection cuts for the 800 GeV mass hypothesis in the ZL CR. Preselection represents events with at least three leptons.
Expected signal and background yields after each of the analysis selection cuts for the 800 GeV mass hypothesis in the Q0-DB CR. Preselection represents events with at least three leptons.
Expected signal and background yields after each of the analysis selection cuts for the 800 GeV mass hypothesis in the Q0-RT CR. Preselection represents events with at least three leptons.
Expected background yields and observed data after the background-only fit, in the three-lepton CRs and VRs.
Expected background yields and observed data after the background-only fit, in the four-lepton CRs and VRs.
Expected and observed 95% ( $CL_s$ ) exclusion limits in the three and four lepton channels for the type-III seesaw process with the corresponding one- and two-standard-deviation bands, showing the 95% CL upper limit on the cross-section.
A search for new phenomena in final states with hadronically decaying tau leptons, $b$-jets, and missing transverse momentum is presented. The analyzed dataset comprises $pp$~collision data at a center-of-mass energy of $\sqrt s = 13$ TeV with an integrated luminosity of 139/fb, delivered by the Large Hadron Collider and recorded with the ATLAS detector from 2015 to 2018. The observed data are compatible with the expected Standard Model background. The results are interpreted in simplified models for two different scenarios. The first model is based on supersymmetry and considers pair production of top squarks, each of which decays into a $b$-quark, a neutrino and a tau slepton. Each tau slepton in turn decays into a tau lepton and a nearly massless gravitino. Within this model, top-squark masses up to 1.4 TeV can be excluded at the 95% confidence level over a wide range of tau-slepton masses. The second model considers pair production of leptoquarks with decays into third-generation leptons and quarks. Depending on the branching fraction into charged leptons, leptoquarks with masses up to around 1.25 TeV can be excluded at the 95% confidence level for the case of scalar leptoquarks and up to 1.8 TeV (1.5 TeV) for vector leptoquarks in a Yang--Mills (minimal-coupling) scenario. In addition, model-independent upper limits are set on the cross section of processes beyond the Standard Model.
Relative systematic uncertainties in the estimated number of background events in the signal regions. In the lower part of the table, a breakdown of the total uncertainty into different categories is given. For the multi-bin SR, the breakdown refers to the integral over all three $p_{\text{T}}(\tau)$ bins. As the individual uncertainties are correlated, they do not add in quadrature to equal the total background uncertainty.
Distributions of $m_{\text{T}2}(\tau_{1},\tau_{2})$ in the di-tau SR. The stacked histograms show the various SM background contributions. The hatched band indicates the total statistical and systematic uncertainty of the SM background. The $t\bar{t}$ (2 real $\tau$) and $t\bar{t}$ (1 real $\tau$) as well as the single-top background contributions are scaled with the normalization factors obtained from the background-only fit. Minor backgrounds are grouped together and denoted as 'Other'. This includes $t\bar{t}$-fake, single top, and other top (di-tau channel) or $t\bar{t}$-fake, $t\bar{t}+H$, multiboson, and other top (single-tau channel). The overlaid dotted lines show the additional contributions for signal scenarios close to the expected exclusion contour with the particle type and the mass and $\beta$ parameters for the simplified models indicated in the legend. For the leptoquark signal model the shapes of the distributions for $\text{LQ}_{3}^{\text{d}}$ and $\text{LQ}_{3}^{\text{v}}$ (not shown) are similar to that of $\text{LQ}_{3}^{\text{u}}$. The rightmost bin includes the overflow.
Distributions of $E_{\text{T}}^{\text{miss}}$ in the di-tau SR. The stacked histograms show the various SM background contributions. The hatched band indicates the total statistical and systematic uncertainty of the SM background. The $t\bar{t}$ (2 real $\tau$) and $t\bar{t}$ (1 real $\tau$) as well as the single-top background contributions are scaled with the normalization factors obtained from the background-only fit. Minor backgrounds are grouped together and denoted as 'Other'. This includes $t\bar{t}$-fake, single top, and other top (di-tau channel) or $t\bar{t}$-fake, $t\bar{t}+H$, multiboson, and other top (single-tau channel). The overlaid dotted lines show the additional contributions for signal scenarios close to the expected exclusion contour with the particle type and the mass and $\beta$ parameters for the simplified models indicated in the legend. For the leptoquark signal model the shapes of the distributions for $\text{LQ}_{3}^{\text{d}}$ and $\text{LQ}_{3}^{\text{v}}$ (not shown) are similar to that of $\text{LQ}_{3}^{\text{u}}$. The rightmost bin includes the overflow.
Distributions of $s_{\text{T}}$ in the single-tau one-bin SR. The stacked histograms show the various SM background contributions. The hatched band indicates the total statistical and systematic uncertainty of the SM background. The $t\bar{t}$ (2 real $\tau$) and $t\bar{t}$ (1 real $\tau$) as well as the single-top background contributions are scaled with the normalization factors obtained from the background-only fit. Minor backgrounds are grouped together and denoted as 'Other'. This includes $t\bar{t}$-fake, single top, and other top (di-tau channel) or $t\bar{t}$-fake, $t\bar{t}+H$, multiboson, and other top (single-tau channel). The overlaid dotted lines show the additional contributions for signal scenarios close to the expected exclusion contour with the particle type and the mass and $\beta$ parameters for the simplified models indicated in the legend. For the leptoquark signal model the shapes of the distributions for $\text{LQ}_{3}^{\text{d}}$ and $\text{LQ}_{3}^{\text{v}}$ (not shown) are similar to that of $\text{LQ}_{3}^{\text{u}}$. The rightmost bin includes the overflow.
Distributions of $m_{\text{T}}(\tau)$ in the single-tau one-bin SR. The stacked histograms show the various SM background contributions. The hatched band indicates the total statistical and systematic uncertainty of the SM background. The $t\bar{t}$ (2 real $\tau$) and $t\bar{t}$ (1 real $\tau$) as well as the single-top background contributions are scaled with the normalization factors obtained from the background-only fit. Minor backgrounds are grouped together and denoted as 'Other'. This includes $t\bar{t}$-fake, single top, and other top (di-tau channel) or $t\bar{t}$-fake, $t\bar{t}+H$, multiboson, and other top (single-tau channel). The overlaid dotted lines show the additional contributions for signal scenarios close to the expected exclusion contour with the particle type and the mass and $\beta$ parameters for the simplified models indicated in the legend. For the leptoquark signal model the shapes of the distributions for $\text{LQ}_{3}^{\text{d}}$ and $\text{LQ}_{3}^{\text{v}}$ (not shown) are similar to that of $\text{LQ}_{3}^{\text{u}}$. The rightmost bin includes the overflow.
Distributions of $\Sigma m_{\text{T}}(b_{1,2})$ in the single-tau $p_{\text{T}}(\tau)$-binned SR. The stacked histograms show the various SM background contributions. The hatched band indicates the total statistical and systematic uncertainty of the SM background. The $t\bar{t}$ (2 real $\tau$) and $t\bar{t}$ (1 real $\tau$) as well as the single-top background contributions are scaled with the normalization factors obtained from the background-only fit. Minor backgrounds are grouped together and denoted as 'Other'. This includes $t\bar{t}$-fake, single top, and other top (di-tau channel) or $t\bar{t}$-fake, $t\bar{t}+H$, multiboson, and other top (single-tau channel). The overlaid dotted lines show the additional contributions for signal scenarios close to the expected exclusion contour with the particle type and the mass and $\beta$ parameters for the simplified models indicated in the legend. For the leptoquark signal model the shapes of the distributions for $\text{LQ}_{3}^{\text{d}}$ and $\text{LQ}_{3}^{\text{v}}$ (not shown) are similar to that of $\text{LQ}_{3}^{\text{u}}$. The rightmost bin includes the overflow.
Distributions of $p_{\text{T}}(\tau)$ in the single-tau $p_{\text{T}}(\tau)$-binned SR. The stacked histograms show the various SM background contributions. The hatched band indicates the total statistical and systematic uncertainty of the SM background. The $t\bar{t}$ (2 real $\tau$) and $t\bar{t}$ (1 real $\tau$) as well as the single-top background contributions are scaled with the normalization factors obtained from the background-only fit. Minor backgrounds are grouped together and denoted as 'Other'. This includes $t\bar{t}$-fake, single top, and other top (di-tau channel) or $t\bar{t}$-fake, $t\bar{t}+H$, multiboson, and other top (single-tau channel). The overlaid dotted lines show the additional contributions for signal scenarios close to the expected exclusion contour with the particle type and the mass and $\beta$ parameters for the simplified models indicated in the legend. For the leptoquark signal model the shapes of the distributions for $\text{LQ}_{3}^{\text{d}}$ and $\text{LQ}_{3}^{\text{v}}$ (not shown) are similar to that of $\text{LQ}_{3}^{\text{u}}$. The rightmost bin includes the overflow.
Expected and observed exclusion contours at the 95% confidence level for the vector third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{v}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ into a quark and a charged lepton. The plot shows the exclusion contour for the minimal-coupling scenario. The limits are derived from the binned single-tau signal region.
Expected and observed exclusion contours at the 95% confidence level for the vector third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{v}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ into a quark and a charged lepton. The plot shows the exclusion contour for the minimal-coupling scenario. The limits are derived from the binned single-tau signal region.
Expected and observed exclusion contours at the 95% confidence level for the vector third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{v}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ into a quark and a charged lepton. The plot shows the exclusion contour for vector leptoquarks with additional gauge couplings. The limits are derived from the binned single-tau signal region.
Expected and observed exclusion contours at the 95% confidence level for the vector third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{v}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ into a quark and a charged lepton. The plot shows the exclusion contour for vector leptoquarks with additional gauge couplings. The limits are derived from the binned single-tau signal region.
Exclusion contours at the 95% confidence level for the stop-stau signal model as a function of the masses of the top squark $m(\tilde{t}_{1})$ and of the tau slepton $m(\tilde{\tau}_{1})$. Expected and observed limits are shown for the present search in comparison to observed limits from previous ATLAS analyses based on data from Run-1 of the LHC at $\sqrt{s} = 8$ TeV [Eur. Phys. J. C 76 (2016)] and on a partial dataset from Run 2 at $\sqrt{s} = 13$ TeV [Phys. Rev. D 98 (2018) 032008]. The green band indicates the limit on the mass of the tau slepton (for a massless LSP) from the LEP experiments.
Exclusion contours at the 95% confidence level for the stop-stau signal model as a function of the masses of the top squark $m(\tilde{t}_{1})$ and of the tau slepton $m(\tilde{\tau}_{1})$. Expected and observed limits are shown for the present search in comparison to observed limits from previous ATLAS analyses based on data from Run-1 of the LHC at $\sqrt{s} = 8$ TeV [Eur. Phys. J. C 76 (2016)] and on a partial dataset from Run 2 at $\sqrt{s} = 13$ TeV [Phys. Rev. D 98 (2018) 032008]. The green band indicates the limit on the mass of the tau slepton (for a massless LSP) from the LEP experiments.
Expected and observed exclusion contours at the 95% confidence level for the scalar third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{u}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow q\ell)$ into a quark and a charged lepton. The plot shows the exclusion contour for up-type leptoquarks $\text{LQ}_{3}^{\text{u}})$ with charge $+2/3e$. The limits are derived from the binned single-tau signal region. Shown in gray for comparison are the observed exclusion-limit contours from the previous ATLAS publication that targets the same leptoquark models but is based on a subset of the Run-2 data [JHEP 06 (2019) 144]. In this previous publication five different analyses are considered that target not only the final state studied here but also the final states that correspond to a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow q\ell)$ of 0 or 1, leading to the concave shapes of the gray exclusion contours.
Expected and observed exclusion contours at the 95% confidence level for the scalar third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{u}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow q\ell)$ into a quark and a charged lepton. The plot shows the exclusion contour for up-type leptoquarks $\text{LQ}_{3}^{\text{u}})$ with charge $+2/3e$. The limits are derived from the binned single-tau signal region. Shown in gray for comparison are the observed exclusion-limit contours from the previous ATLAS publication that targets the same leptoquark models but is based on a subset of the Run-2 data [JHEP 06 (2019) 144]. In this previous publication five different analyses are considered that target not only the final state studied here but also the final states that correspond to a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow q\ell)$ of 0 or 1, leading to the concave shapes of the gray exclusion contours.
Expected and observed exclusion contours at the 95% confidence level for the scalar third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{d}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow q\ell)$ into a quark and a charged lepton. The plot shows the exclusion contour for down-type leptoquarks $\text{LQ}_{3}^{\text{d}})$ with charge $-1/3e$. The limits are derived from the binned single-tau signal region. Shown in gray for comparison are the observed exclusion-limit contours from the previous ATLAS publication that targets the same leptoquark models but is based on a subset of the Run-2 data [JHEP 06 (2019) 144]. In this previous publication five different analyses are considered that target not only the final state studied here but also the final states that correspond to a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow q\ell)$ of 0 or 1, leading to the concave shapes of the gray exclusion contours.
Expected and observed exclusion contours at the 95% confidence level for the scalar third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{d}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow q\ell)$ into a quark and a charged lepton. The plot shows the exclusion contour for down-type leptoquarks $\text{LQ}_{3}^{\text{d}})$ with charge $-1/3e$. The limits are derived from the binned single-tau signal region. Shown in gray for comparison are the observed exclusion-limit contours from the previous ATLAS publication that targets the same leptoquark models but is based on a subset of the Run-2 data [JHEP 06 (2019) 144]. In this previous publication five different analyses are considered that target not only the final state studied here but also the final states that correspond to a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow q\ell)$ of 0 or 1, leading to the concave shapes of the gray exclusion contours.
Upper limits on the signal cross section at the 95 % confidence level for the stop-stau signal model.
Upper limits on the signal cross section at the 95 % confidence level for the scalar third-generation leptoquark signal model with up-type leptoquarks.
Upper limits on the signal cross section at the 95 % confidence level for the scalar third-generation leptoquark signal model with down-type leptoquarks.
Upper limits on the signal cross section at the 95 % confidence level for the vector third-generation leptoquark signal model with minimal coupling (MC).
Upper limits on the signal cross section at the 95 % confidence level for the vector third-generation leptoquark signal model with additional gauge couplings (YM).
Acceptance of the one-bin signal region of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$.
Efficiency of the one-bin signal region of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$.
Efficiency of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$.
Efficiency of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$.
Efficiency of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the signal region of the di-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$.
Efficiency of the signal region of the di-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow b\tau)$ of 0 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the one-bin signal region of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$.
Efficiency of the one-bin signal region of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow t\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$.
Efficiency of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow t\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$.
Efficiency of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow t\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$.
Efficiency of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow t\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the signal region of the di-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$.
Efficiency of the signal region of the di-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow t\tau)$ of 0 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the one-bin signal region of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario.
Efficiency of the one-bin signal region of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario.
Efficiency of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario.
Efficiency of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario.
Efficiency of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the signal region of the di-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario.
Efficiency of the signal region of the di-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the one-bin signal region of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings.
Efficiency of the one-bin signal region of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings.
Efficiency of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings.
Efficiency of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings.
Efficiency of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the signal region of the di-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings.
Efficiency of the signal region of the di-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the one-bin signal region of the single-tau channel for pair production of top squarks with decays via tau sleptons.
Efficiency of the one-bin signal region of the single-tau channel for pair production of top squarks with decays via tau sleptons.
Acceptance of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of top squarks with decays via tau sleptons.
Efficiency of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of top squarks with decays via tau sleptons.
Acceptance of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of top squarks with decays via tau sleptons.
Efficiency of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of top squarks with decays via tau sleptons.
Acceptance of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of top squarks with decays via tau sleptons.
Efficiency of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of top squarks with decays via tau sleptons.
Acceptance of the signal region of the di-tau channel for pair production of top squarks with decays via tau sleptons.
Efficiency of the signal region of the di-tau channel for pair production of top squarks with decays via tau sleptons.
Cutflow for the benchmark signal model $m(\tilde{t}_{1}) = 1350$ GeV, $m(\tilde{\tau}_{1}) = 1090$ GeV for the di-tau SR. The simulated sample contains 30,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the di-tau channel.
Cutflow for the benchmark signal model $m(\tilde{t}_{1}) = 1350$ GeV, $m(\tilde{\tau}_{1}) = 1090$ GeV for the single-tau one-bin SR. The simulated sample contains 30,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.
Cutflow for the benchmark signal model $m(\tilde{t}_{1}) = 1350$ GeV, $m(\tilde{\tau}_{1}) = 1090$ GeV for the single-tau multi-bin SR. The simulated sample contains 30,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{u}}) = 1.2$ TeV, $\beta = 0.5$ for the di-tau SR. The simulated sample contains 210,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the di-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{u}}) = 1.2$ TeV, $\beta = 0.5$ for the single-tau one-bin SR. The simulated sample contains 210,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{u}}) = 1.2$ TeV, $\beta = 0.5$ for the single-tau multi-bin SR. The simulated sample contains 210,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{d}}) = 1.2$ TeV, $\beta = 0.5$ for the di-tau SR. The simulated sample contains 210,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the di-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{d}}) = 1.2$ TeV, $\beta = 0.5$ for the single-tau one-bin SR. The simulated sample contains 210,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{d}}) = 1.2$ TeV, $\beta = 0.5$ for the single-tau multi-bin SR. The simulated sample contains 210,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{v}}) = 1.4$ TeV, $\beta = 0.5$ in the minimal-coupling scenario for the di-tau SR. The simulated sample contains 50,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the di-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{v}}) = 1.4$ TeV, $\beta = 0.5$ in the minimal-coupling scenario for the single-tau one-bin SR. The simulated sample contains 50,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{v}}) = 1.4$ TeV, $\beta = 0.5$ in the minimal-coupling scenario for the single-tau multi-bin SR. The simulated sample contains 50,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{v}}) = 1.4$ TeV, $\beta = 0.5$ in the Yang--Mills scenario for the di-tau SR. The simulated sample contains 50,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the di-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{v}}) = 1.4$ TeV, $\beta = 0.5$ in the Yang--Mills scenario for the single-tau one-bin SR. The simulated sample contains 50,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{v}}) = 1.4$ TeV, $\beta = 0.5$ in the Yang--Mills scenario for the single-tau multi-bin SR. The simulated sample contains 50,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.
The production of dark matter in association with Higgs bosons is predicted in several extensions of the Standard Model. An exploration of such scenarios is presented, considering final states with missing transverse momentum and $b$-tagged jets consistent with a Higgs boson. The analysis uses proton-proton collision data at a centre-of-mass energy of 13 TeV recorded by the ATLAS experiment at the LHC during Run 2, amounting to an integrated luminosity of 139 fb$^{-1}$. The analysis, when compared with previous searches, benefits from a larger dataset, but also has further improvements providing sensitivity to a wider spectrum of signal scenarios. These improvements include both an optimised event selection and advances in the object identification, such as the use of the likelihood-based significance of the missing transverse momentum and variable-radius track-jets. No significant deviation from Standard Model expectations is observed. Limits are set, at 95% confidence level, in two benchmark models with two Higgs doublets extended by either a heavy vector boson $Z'$ or a pseudoscalar singlet $a$ and which both provide a dark matter candidate $\chi$. In the case of the two-Higgs-doublet model with an additional vector boson $Z'$, the observed limits extend up to a $Z'$ mass of 3 TeV for a mass of 100 GeV for the dark matter candidate. The two-Higgs-doublet model with a dark matter particle mass of 10 GeV and an additional pseudoscalar $a$ is excluded for masses of the $a$ up to 520 GeV and 240 GeV for $\tan \beta = 1$ and $\tan \beta = 10$ respectively. Limits on the visible cross-sections are set and range from 0.05 fb to 3.26 fb, depending on the missing transverse momentum and $b$-quark jet multiplicity requirements.
Observed 95% CL exclusion limit for the Zprime-2HDM model.
Expected 95% CL exclusion limit for the Zprime-2HDM model.
Expected +- 1 sigma 95% CL exclusion limit for the Zprime-2HDM model.
Expected +- 2 sigma 95% CL exclusion limit for the Zprime-2HDM model.
Observed 95% CL exclusion limit for the 2HDM+a model ggF production.
Expected 95% CL exclusion limit for the 2HDM+a model ggF production.
Expected +- 1 sigma 95% CL exclusion limit for the 2HDM+a model ggF production.
Expected +- 2 sigma 95% CL exclusion limit for the 2HDM+a model ggF production.
Observed 95% CL exclusion limit for the 2HDM+a model bbA production.
Expected 95% CL exclusion limit for the 2HDM+a model bbA production.
Expected +- 1 sigma 95% CL exclusion limit for the 2HDM+a model bbA production.
Expected +- 2 sigma 95% CL exclusion limit for the 2HDM+a model bbA production.
Observed 95% CL exclusion limit for the Zprime-2HDM model with the benchmark used in arXiv:1707.01302.
Expected 95% CL exclusion limit for the Zprime-2HDM model with the benchmark used in arXiv:1707.01302.
Expected +- 1 sigma 95% CL exclusion limit for the Zprime-2HDM model with the benchmark used in arXiv:1707.01302.
Expected +- 2 sigma 95% CL exclusion limit for the Zprime-2HDM model with the benchmark used in arXiv:1707.01302.
Expected and observed upper limits at 95% CL on cross-section for Zprime-2HDM model.
Expected and observed upper limits at 95% CL on cross-section for ggF producton in the 2HDM+a model.
Expected and observed upper limits at 95% CL on cross-section for bbA producton in the 2HDM+a model.
Model-independent upper limits on the visible cross-section $σ_{vis, $h(\bar{b})+DM} ≡ σ_{h+DM} \times B(h \to b\bar{b}) \times \mathcal{A} \times \epsilon$ in the different signal regions.
Theory cross-section for Zprime-2HDM model.
Theory cross-section for bbA production in the 2HDM+a model.
Theory cross-section for ggF production in the 2HDM+a model.
Distribution of Higgs boson candidate mass in 2b region with MET=150-200 GeV.
Distribution of Higgs boson candidate mass in 2b region with MET=200-350 GeV.
Distribution of Higgs boson candidate mass in 2b region with MET=350-500 GeV.
Distribution of Higgs boson candidate mass in 2b region with MET=500-750 GeV.
Distribution of Higgs boson candidate mass in 2b region with MET > 750 GeV.
Distribution of Higgs boson candidate mass in 3b region with MET=150-200 GeV.
Distribution of Higgs boson candidate mass in 3b region with MET=200-350 GeV.
Distribution of Higgs boson candidate mass in 3b region with MET=350-500 GeV.
Distribution of Higgs boson candidate mass in 3b region with MET > 500 GeV.
Yields in 1-lepton control region.
Yields in 2-lepton control region.
MET distribution in 2b region of the 0-lepton channel.
MET distribution in 3b region of the 0-lepton channel.
Expected signal yields after certain selection cuts in 2b region with MET=150-200 GeV.
Expected signal yields after certain selection cuts in 2b region with MET=200-350 GeV.
Expected signal yields after certain selection cuts in 2b region with MET=350-500 GeV.
Expected signal yields after certain selection cuts in 2b region with MET=500-750 GeV.
Expected signal yields after certain selection cuts in 2b region with MET > 750 GeV.
Expected signal yields after certain selection cuts in 3b region with MET=150-200 GeV.
Expected signal yields after certain selection cuts in 3b region with MET=200-350 GeV.
Expected signal yields after certain selection cuts in 3b region with MET=350-500 GeV.
Expected signal yields after certain selection cuts in 3b region with MET > 500 GeV.
Acceptance times efficiency for bbA production in the 2HDM+a model - 2b region with MET=150-200 GeV.
Acceptance times efficiency for bbA production in the 2HDM+a model - 2b region with MET=200-350 GeV.
Acceptance times efficiency for bbA production in the 2HDM+a model - 2b region with MET=350-500 GeV.
Acceptance times efficiency for bbA production in the 2HDM+a model - 2b region with MET=500-750 GeV.
Acceptance times efficiency for bbA production in the 2HDM+a model - 2b region with MET > 750 GeV.
Acceptance times efficiency for bbA production in the 2HDM+a model - 3b region with MET=150-200 GeV.
Acceptance times efficiency for bbA production in the 2HDM+a model - 3b region with MET=200-350 GeV.
Acceptance times efficiency for bbA production in the 2HDM+a model - 3b region with MET=350-500 GeV.
Acceptance times efficiency for bbA production in the 2HDM+a model - 3b region with MET>500 GeV.
Acceptance times efficiency for ggF production in the 2HDM+a model - 2b region with MET=150-200 GeV.
Acceptance times efficiency for ggF production in the 2HDM+a model - 2b region with MET=200-350 GeV.
Acceptance times efficiency for ggF production in the 2HDM+a model - 2b region with MET=350-500 GeV.
Acceptance times efficiency for ggF production in the 2HDM+a model - 2b region with MET=500-750 GeV.
Acceptance times efficiency for ggF production in the 2HDM+a model - 2b region with MET > 750 GeV.
Acceptance times efficiency for ggF production in the 2HDM+a model - 3b region with MET=150-200 GeV.
Acceptance times efficiency for ggF production in the 2HDM+a model - 3b region with MET=200-350 GeV.
Acceptance times efficiency for ggF production in the 2HDM+a model - 3b region with MET=350-500 GeV.
Acceptance times efficiency for ggF production in the 2HDM+a model - 3b region with MET > 500 GeV.
Acceptance times efficiency for ggF production in the Zprime-2HDM model - 2b region with MET=150-200 GeV.
Acceptance times efficiency for ggF production in the Zprime-2HDM model - 2b region with MET=200-350 GeV.
Acceptance times efficiency for ggF production in the Zprime-2HDM model - 2b region with MET=350-500 GeV.
Acceptance times efficiency for ggF production in the Zprime-2HDM model - 2b region with MET=500-750 GeV.
Acceptance times efficiency for ggF production in the Zprime-2HDM model - 2b region with MET > 750 GeV.
Acceptance times efficiency for ggF production in the Zprime-2HDM model - 3b region with MET=150-200 GeV.
Acceptance times efficiency for ggF production in the Zprime-2HDM model - 3b region with MET=200-350 GeV.
Acceptance times efficiency for ggF production in the Zprime-2HDM model - 3b region with MET=350-500 GeV.
Acceptance times efficiency for ggF production in the Zprime-2HDM model - 3b region with MET > 500 GeV.
Measurements of both the inclusive and differential production cross sections of a top-quark-antiquark pair in association with a $Z$ boson ($t\bar{t}Z$) are presented. The measurements are performed by targeting final states with three or four isolated leptons (electrons or muons) and are based on $\sqrt{s} = 13$ TeV proton-proton collision data with an integrated luminosity of 139 fb$^{-1}$, recorded from 2015 to 2018 with the ATLAS detector at the CERN Large Hadron Collider. The inclusive cross section is measured to be $\sigma_{t\bar{t}Z} = 0.99 \pm 0.05$ (stat.) $\pm 0.08$ (syst.) pb, in agreement with the most precise theoretical predictions. The differential measurements are presented as a function of a number of kinematic variables which probe the kinematics of the $t\bar{t}Z$ system. Both absolute and normalised differential cross-section measurements are performed at particle and parton levels for specific fiducial volumes and are compared with theoretical predictions at different levels of precision, based on a $\chi^{2}/$ndf and $p$-value computation. Overall, good agreement is observed between the unfolded data and the predictions.
The measured $t\bar{t}\text{Z}$ cross-section value and its uncertainty based on the fit results from the combined trilepton and tetralepton channels. The value corresponds to the phase-space region where the difermion mass from the Z boson decay lies in the range $70 < m_{f\bar{f}} < 110$ GeV.
The measured $t\bar{t}\text{Z}$ cross-section value and its uncertainty based on the fit results from the combined trilepton and tetralepton channels. The value corresponds to the phase-space region where the difermion mass from the Z boson decay lies in the range $70 < m_{f\bar{f}} < 110$ GeV.
List of relative uncertainties of the measured inclusive $t\bar{t}\text{Z}$ cross section from the combined fit. The uncertainties are symmetrised for presentation and grouped into the categories described in the text. The quadratic sum of the individual uncertainties is not equal to the total uncertainty due to correlations introduced by the fit.
List of relative uncertainties of the measured inclusive $t\bar{t}\text{Z}$ cross section from the combined fit. The uncertainties are symmetrised for presentation and grouped into the categories described in the text. The quadratic sum of the individual uncertainties is not equal to the total uncertainty due to correlations introduced by the fit.
The definitions of the trilepton signal regions: for the inclusive measurement, a combination of the regions with pseudo-continuous $b$-tagging 3$\ell$-Z-1$b$4$j$-PCBT and 3$\ell$-Z-2$b$3$j$-PCBT is used, whereas for the differential measurement, only the region 3$\ell$-Z-2$b$3$j$, with a fixed $b$-tagging WP is employed.
The definitions of the trilepton signal regions: for the inclusive measurement, a combination of the regions with pseudo-continuous $b$-tagging 3$\ell$-Z-1$b$4$j$-PCBT and 3$\ell$-Z-2$b$3$j$-PCBT is used, whereas for the differential measurement, only the region 3$\ell$-Z-2$b$3$j$, with a fixed $b$-tagging WP is employed.
The definitions of the four tetralepton signal regions. The regions are defined to target different $b$-jet multiplicities and flavour combinations of the non-Z leptons.
The definitions of the four tetralepton signal regions. The regions are defined to target different $b$-jet multiplicities and flavour combinations of the non-Z leptons.
The absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}$ of the $Z$ boson in the 3$\ell$+4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}$ of the $Z$ boson in the 3$\ell$+4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}$ of the $Z$ boson in the 3$\ell$+4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}$ of the $Z$ boson in the 3$\ell$+4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}$ of the $Z$ boson in the 3$\ell$+4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}$ of the $Z$ boson in the 3$\ell$+4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}$ of the $Z$ boson in the 3$\ell$+4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}$ of the $Z$ boson in the 3$\ell$+4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the absolute value of rapidity of the $Z$ boson in the 3$\ell$+4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the absolute value of rapidity of the $Z$ boson in the 3$\ell$+4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the number of jets in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the number of jets in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the number of jets in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the number of jets in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{l \textrm{non-}Z}$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{l \textrm{non-}Z}$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta y (Z, t_{\textrm{lep}})|$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta y (Z, t_{\textrm{lep}})|$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (t\bar{t}, Z)|/\pi$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (t\bar{t}, Z)|/\pi$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{t\bar{t}}$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{t\bar{t}}$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{l \textrm{non-}Z}$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{l \textrm{non-}Z}$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta y (Z, t_{\textrm{lep}})|$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta y (Z, t_{\textrm{lep}})|$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (t\bar{t}, Z)|/\pi$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (t\bar{t}, Z)|/\pi$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{t\bar{t}}$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{t\bar{t}}$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the absolute value of rapidity of the $Z$ boson in the 3$\ell$+4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the absolute value of rapidity of the $Z$ boson in the 3$\ell$+4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{l \textrm{non-}Z}$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{l \textrm{non-}Z}$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta y (Z, t_{\textrm{lep}})|$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta y (Z, t_{\textrm{lep}})|$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (t\bar{t}, Z)|/\pi$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (t\bar{t}, Z)|/\pi$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{t\bar{t}}$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{t\bar{t}}$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the absolute value of rapidity of the $Z$ boson in the 3$\ell$+4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the absolute value of rapidity of the $Z$ boson in the 3$\ell$+4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{l \textrm{non-}Z}$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{l \textrm{non-}Z}$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta y (Z, t_{\textrm{lep}})|$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta y (Z, t_{\textrm{lep}})|$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (t\bar{t}, Z)|/\pi$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (t\bar{t}, Z)|/\pi$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{t\bar{t}}$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{t\bar{t}}$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the absolute value of rapidity of the $Z$ boson in the 3$\ell$+4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the absolute value of rapidity of the $Z$ boson in the 3$\ell$+4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the number of jets in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the number of jets in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the number of jets in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the number of jets in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.
The total correlation matrix of the absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}$ of the $Z$ boson in the 3$\ell$+4$\ell$ channel.
The total correlation matrix of the absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}$ of the $Z$ boson in the 3$\ell$+4$\ell$ channel.
The total correlation matrix of the absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the absolute value of rapidity of the $Z$ boson in the 3$\ell$+4$\ell$ channel.
The total correlation matrix of the absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the absolute value of rapidity of the $Z$ boson in the 3$\ell$+4$\ell$ channel.
The total correlation matrix of the absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{l \textrm{non-}Z}$ in the 3$\ell$ channel.
The total correlation matrix of the absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{l \textrm{non-}Z}$ in the 3$\ell$ channel.
The total correlation matrix of the absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel.
The total correlation matrix of the absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel.
The total correlation matrix of the absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta y (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel.
The total correlation matrix of the absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta y (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel.
The total correlation matrix of the absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the 4$\ell$ channel.
The total correlation matrix of the absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the 4$\ell$ channel.
The total correlation matrix of the absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (t\bar{t}, Z)|/\pi$ in the 4$\ell$ channel.
The total correlation matrix of the absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (t\bar{t}, Z)|/\pi$ in the 4$\ell$ channel.
The total correlation matrix of the absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{t\bar{t}}$ in the 4$\ell$ channel.
The total correlation matrix of the absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{t\bar{t}}$ in the 4$\ell$ channel.
The total correlation matrix of the normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}$ of the $Z$ boson in the 3$\ell$+4$\ell$ channel.
The total correlation matrix of the normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}$ of the $Z$ boson in the 3$\ell$+4$\ell$ channel.
The total correlation matrix of the normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the absolute value of rapidity of the $Z$ boson in the 3$\ell$+4$\ell$ channel.
The total correlation matrix of the normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the absolute value of rapidity of the $Z$ boson in the 3$\ell$+4$\ell$ channel.
The total correlation matrix of the normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{l \textrm{non-}Z}$ in the 3$\ell$ channel.
The total correlation matrix of the normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{l \textrm{non-}Z}$ in the 3$\ell$ channel.
The total correlation matrix of the normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel.
The total correlation matrix of the normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel.
The total correlation matrix of the normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta y (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel.
The total correlation matrix of the normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta y (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel.
The total correlation matrix of the normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the 4$\ell$ channel.
The total correlation matrix of the normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the 4$\ell$ channel.
The total correlation matrix of the normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (t\bar{t}, Z)|/\pi$ in the 4$\ell$ channel.
The total correlation matrix of the normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (t\bar{t}, Z)|/\pi$ in the 4$\ell$ channel.
The total correlation matrix of the normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{t\bar{t}}$ in the 4$\ell$ channel.
The total correlation matrix of the normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{t\bar{t}}$ in the 4$\ell$ channel.
The total correlation matrix of the absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}$ of the $Z$ boson in the 3$\ell$+4$\ell$ channel.
The total correlation matrix of the absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}$ of the $Z$ boson in the 3$\ell$+4$\ell$ channel.
The total correlation matrix of the absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the absolute value of rapidity of the $Z$ boson in the 3$\ell$+4$\ell$ channel.
The total correlation matrix of the absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the absolute value of rapidity of the $Z$ boson in the 3$\ell$+4$\ell$ channel.
The total correlation matrix of the absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{l \textrm{non-}Z}$ in the 3$\ell$ channel.
The total correlation matrix of the absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{l \textrm{non-}Z}$ in the 3$\ell$ channel.
The total correlation matrix of the absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel.
The total correlation matrix of the absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel.
The total correlation matrix of the absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta y (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel.
The total correlation matrix of the absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta y (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel.
The total correlation matrix of the absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the number of jets in the 3$\ell$ channel.
The total correlation matrix of the absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the number of jets in the 3$\ell$ channel.
The total correlation matrix of the absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the 4$\ell$ channel.
The total correlation matrix of the absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the 4$\ell$ channel.
The total correlation matrix of the absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (t\bar{t}, Z)|/\pi$ in the 4$\ell$ channel.
The total correlation matrix of the absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (t\bar{t}, Z)|/\pi$ in the 4$\ell$ channel.
The total correlation matrix of the absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{t\bar{t}}$ in the 4$\ell$ channel.
The total correlation matrix of the absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{t\bar{t}}$ in the 4$\ell$ channel.
The total correlation matrix of the absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the number of jets in the 4$\ell$ channel.
The total correlation matrix of the absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the number of jets in the 4$\ell$ channel.
The total correlation matrix of the normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}$ of the $Z$ boson in the 3$\ell$+4$\ell$ channel.
The total correlation matrix of the normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}$ of the $Z$ boson in the 3$\ell$+4$\ell$ channel.
The total correlation matrix of the normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the absolute value of rapidity of the $Z$ boson in the 3$\ell$+4$\ell$ channel.
The total correlation matrix of the normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the absolute value of rapidity of the $Z$ boson in the 3$\ell$+4$\ell$ channel.
The total correlation matrix of the normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{l \textrm{non-}Z}$ in the 3$\ell$ channel.
The total correlation matrix of the normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{l \textrm{non-}Z}$ in the 3$\ell$ channel.
The total correlation matrix of the normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel.
The total correlation matrix of the normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel.
The total correlation matrix of the normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta y (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel.
The total correlation matrix of the normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta y (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel.
The total correlation matrix of the normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the number of jets in the 3$\ell$ channel.
The total correlation matrix of the normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the number of jets in the 3$\ell$ channel.
The total correlation matrix of the normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the 4$\ell$ channel.
The total correlation matrix of the normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the 4$\ell$ channel.
The total correlation matrix of the normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (t\bar{t}, Z)|/\pi$ in the 4$\ell$ channel.
The total correlation matrix of the normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (t\bar{t}, Z)|/\pi$ in the 4$\ell$ channel.
The total correlation matrix of the normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{t\bar{t}}$ in the 4$\ell$ channel.
The total correlation matrix of the normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{t\bar{t}}$ in the 4$\ell$ channel.
The total correlation matrix of the normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the number of jets in the 4$\ell$ channel.
The total correlation matrix of the normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the number of jets in the 4$\ell$ channel.
A search for supersymmetry in events with four or more charged leptons (electrons, muons and $\tau$-leptons) is presented. The analysis uses a data sample corresponding to $139\,\mbox{fb\(^{-1}\)}$ of proton-proton collisions delivered by the Large Hadron Collider at $\sqrt{s}=13$ TeV and recorded by the ATLAS detector. Four-lepton signal regions with up to two hadronically decaying $\tau$-leptons are designed to target several supersymmetric models, while a general five-lepton signal region targets any new physics phenomena leading to a final state with five charged leptons. Data yields are consistent with Standard Model expectations and results are used to set upper limits on contributions from processes beyond the Standard Model. Exclusion limits are set at the 95% confidence level in simplified models of general gauge-mediated supersymmetry, excluding higgsino masses up to $540$ GeV. In $R$-parity-violating simplified models with decays of the lightest supersymmetric particle to charged leptons, lower limits of $1.6$ TeV, $1.2$ TeV, and $2.5$ TeV are placed on wino, slepton and gluino masses, respectively.
The $E_{\mathrm{T}}^{\mathrm{miss}}$ distribution in SR0-ZZ$^{\mathrm{loose}}$ and SR0-ZZ$^{\mathrm{tight}}$ for events passing the signal region requirements except the $E_{\mathrm{T}}^{\mathrm{miss}}$ requirement. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band. The red arrows indicate the $E_{\mathrm{T}}^{\mathrm{miss}}$ selections in the signal regions.
The $E_{\mathrm{T}}^{\mathrm{miss}}$ distribution in SR0-ZZ$_{\mathrm{bveto}}^{\mathrm{loose}}$ and SR0-ZZ$_{\mathrm{bveto}}^{\mathrm{tight}}$ for events passing the signal region requirements except the $E_{\mathrm{T}}^{\mathrm{miss}}$ requirement. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band. The red arrows indicate the $E_{\mathrm{T}}^{\mathrm{miss}}$ selections in the signal regions.
The $E_{\mathrm{T}}^{\mathrm{miss}}$ distribution in SR5L. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The $m_{\mathrm{eff}}$ distribution in SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$ and SR0$_{\mathrm{bveto}}^{\mathrm{tight}}$ for events passing the signal region requirements except the $m_{\mathrm{eff}}$ requirement. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band. The red arrows indicate the $m_{\mathrm{eff}}$ selections in the signal regions.
The $m_{\mathrm{eff}}$ distribution in SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$ and SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$ for events passing the signal region requirements except the $m_{\mathrm{eff}}$ requirement. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band. The red arrows indicate the $m_{\mathrm{eff}}$ selections in the signal regions.
The $m_{\mathrm{eff}}$ distribution in SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$ and SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$ for events passing the signal region requirements except the $m_{\mathrm{eff}}$ requirement. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band. The red arrows indicate the $m_{\mathrm{eff}}$ selections in the signal regions.
The $m_{\mathrm{eff}}$ distribution in SR0$_{\mathrm{breq}}$ for events passing the signal region requirements except the $m_{\mathrm{eff}}$ requirement. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band. The red arrows indicate the $m_{\mathrm{eff}}$ selections in the signal regions.
The $m_{\mathrm{eff}}$ distribution in SR1$_{\mathrm{breq}}$ for events passing the signal region requirements except the $m_{\mathrm{eff}}$ requirement. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band. The red arrows indicate the $m_{\mathrm{eff}}$ selections in the signal regions.
The $m_{\mathrm{eff}}$ distribution in SR2$_{\mathrm{breq}}$ for events passing the signal region requirements except the $m_{\mathrm{eff}}$ requirement. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band. The red arrows indicate the $m_{\mathrm{eff}}$ selections in the signal regions.
Expected 95% CL exclusion limits on the higgsino GGM models. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$+1\sigma$ expected 95% CL exclusion limits on the higgsino GGM models. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$-1\sigma$ expected 95% CL exclusion limits on the higgsino GGM models. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
Observed 95% CL exclusion limits on the higgsino GGM models. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$+1\sigma$ observed 95% CL exclusion limits on the higgsino GGM models. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$-1\sigma$ observed 95% CL exclusion limits on the higgsino GGM models. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
Expected 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$+1\sigma$ expected 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$-1\sigma$ expected 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
Observed 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$+1\sigma$ bserved 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$-1\sigma$ observed 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
Expected 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$+1\sigma$ expected 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$-1\sigma$ expected 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
Observed 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$+1\sigma$ observed 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$-1\sigma$ observed 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
Expected 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$+1\sigma$ expected 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$-1\sigma$ expected 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
Observed 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$+1\sigma$ observed 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$-1\sigma$ observed 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
Expected 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$+1\sigma$ expected 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$-1\sigma$ expected 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
Observed 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$+1\sigma$ observed 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$-1\sigma$ observed 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
Expected 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$+1\sigma$ expected 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$-1\sigma$ expected 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
Observed 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$+1\sigma$ observed 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$-1\sigma$ observed 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
Expected 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$+1\sigma$ expected 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$-1\sigma$ expected 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
Observed 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$+1\sigma$ observed 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$-1\sigma$ observed 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
Observed upper limit on the signal cross section in fb for the wino NLSP models with RPV LSP decays via $\lambda_{12k}$ where $k \in{1,2}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Observed upper limit on the signal cross section in fb for the wino NLSP models with RPV LSP decays via $\lambda_{i33}$ where $i \in{1,2}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Observed upper limit on the signal cross section in fb for the slepton/sneutrino NLSP models with RPV LSP decays via $\lambda_{12k}$ where $k \in{1,2}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Observed upper limit on the signal cross section in fb for the slepton/sneutrino NLSP models with RPV LSP decays via $\lambda_{i33}$ where $i \in{1,2}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Observed upper limit on the signal cross section in fb for the gluino NLSP models with RPV LSP decays via $\lambda_{12k}$ where $k \in{1,2}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Observed upper limit on the signal cross section in fb for the gluino NLSP models with RPV LSP decays via $\lambda_{i33}$ where $i \in{1,2}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Observed upper limit on the signal cross section in fb for the higgsino GGM models. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Best expected SR for the wino NLSP models with RPV LSP decays via $\lambda_{12k}$ where $k \in{1,2}$. A value of 1 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 2 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, 3 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 4 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, and 5 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{tight}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$.
Best expected SR for the wino NLSP models with RPV LSP decays via $\lambda_{i33}$ where $i \in{1,2}$. A value of 1 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 2 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, 3 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 4 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, and 5 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{tight}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$.
Best expected SR for the slepton/sneutrino NLSP models with RPV LSP decays via $\lambda_{12k}$ where $k \in{1,2}$. A value of 1 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 2 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, 3 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 4 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, and 5 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{tight}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$.
Best expected SR for the slepton/sneutrino NLSP models with RPV LSP decays via $\lambda_{i33}$ where $i \in{1,2}$. A value of 1 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 2 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, 3 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 4 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, and 5 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{tight}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$.
Best expected SR for the gluino NLSP models with RPV LSP decays via $\lambda_{12k}$ where $k \in{1,2}$. A value of 1 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 2 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, 3 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 4 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, and 5 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{tight}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$.
Best expected SR for the gluino NLSP models with RPV LSP decays via $\lambda_{i33}$ where $i \in{1,2}$. A value of 1 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 2 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, 3 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 4 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, and 5 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{tight}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$.
Best expected SR for the higgsino GGM models. A value of 6 corresponds to SR0-ZZ$^{\mathrm{loose}}$, 7 corresponds to SR0-ZZ$^{\mathrm{tight}}$, 8 corresponds to SR0-ZZ$^{\mathrm{loose}}_{\mathrm{bveto}}$, and 9 corresponds to SR0-ZZ$^{\mathrm{tight}}_{\mathrm{bveto}}$.
Acceptance across the wino NLSP $\lambda_{12k}\neq 0$ models for SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Efficiency across the wino NLSP $\lambda_{12k}\neq 0$ models for SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Acceptance across the wino NLSP $\lambda_{12k}\neq 0$ models for SR0$_{\mathrm{bveto}}^{\mathrm{tight}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Efficiency across the wino NLSP $\lambda_{12k}\neq 0$ models for SR0$_{\mathrm{bveto}}^{\mathrm{tight}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Acceptance across the wino NLSP $\lambda_{12k}\neq 0$ models for SR0$_{\mathrm{breq}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Efficiency across the wino NLSP $\lambda_{12k}\neq 0$ models for SR0$_{\mathrm{breq}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Acceptance across the wino NLSP $\lambda_{i33}\neq 0$ models for SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Efficiency across the wino NLSP $\lambda_{i33}\neq 0$ models for SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Acceptance across the wino NLSP $\lambda_{i33}\neq 0$ models for SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Efficiency across the wino NLSP $\lambda_{i33}\neq 0$ models for SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Acceptance across the wino NLSP $\lambda_{i33}\neq 0$ models for SR1$_{\mathrm{breq}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Efficiency across the wino NLSP $\lambda_{i33}\neq 0$ models for SR1$_{\mathrm{breq}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Acceptance across the wino NLSP $\lambda_{i33}\neq 0$ models for SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Efficiency across the wino NLSP $\lambda_{i33}\neq 0$ models for SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Acceptance across the wino NLSP $\lambda_{i33}\neq 0$ models for SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Efficiency across the wino NLSP $\lambda_{i33}\neq 0$ models for SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Acceptance across the wino NLSP $\lambda_{i33}\neq 0$ models for SR2$_{\mathrm{breq}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Efficiency across the wino NLSP $\lambda_{i33}\neq 0$ models for SR2$_{\mathrm{breq}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Acceptance across the GGM Higgsino grid for SR0-ZZ$^{\mathrm{loose}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Efficiency across the GGM Higgsino grid for SR0-ZZ$^{\mathrm{loose}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Acceptance across the GGM Higgsino grid for SR0-ZZ$^{\mathrm{tight}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Efficiency across the GGM Higgsino grid for SR0-ZZ$^{\mathrm{tight}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Acceptance across the GGM Higgsino grid for SR0-ZZ$_{\mathrm{bveto}}^{\mathrm{loose}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Efficiency across the GGM Higgsino grid for SR0-ZZ$_{\mathrm{bveto}}^{\mathrm{loose}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Acceptance across the GGM Higgsino grid for SR0-ZZ$_{\mathrm{bveto}}^{\mathrm{tight}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Efficiency across the GGM Higgsino grid for SR0-ZZ$_{\mathrm{bveto}}^{\mathrm{tight}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
The $p_{\mathrm{T}}$ of the light leptons in distribution in SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The $p_{\mathrm{T}}$ of the light leptons in distribution in SR0-ZZ$^{\mathrm{loose}}$. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The $p_{\mathrm{T}}$ of the light leptons in distribution in SR0-ZZ$^{\mathrm{tight}}$. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The $p_{\mathrm{T}}$ of the light leptons in distribution in SR0-ZZ$_{\mathrm{bveto}}^{\mathrm{loose}}$. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The $p_{\mathrm{T}}$ of the light leptons in distribution in SR5L. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The $p_{\mathrm{T}}$ of the light leptons in distribution in SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The $p_{\mathrm{T}}$ of the taus leptons in distribution in SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The $p_{\mathrm{T}}$ of the light taus in distribution in SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The lepton flavour and multiplicities in events with four light leptons and a Z veto. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The lepton flavour and multiplicities in events with four light leptons and one Z candidate. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The lepton flavour and multiplicities in events with four light leptons and two Z candidates. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The lepton flavour and multiplicities in events with exactly five light leptons. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The lepton flavour and multiplicities in events with three light leptons and one tau and a Z veto. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The lepton flavour and multiplicities in events with three light leptons and one tau and one Z candidate. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The lepton flavour and multiplicities in events with two light leptons and two taus and a Z veto. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The lepton flavour and multiplicities in events with two light leptons and two taus and one Z candidate. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
Cutflow event yields in regions SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$, SR0$_{\mathrm{bveto}}^{\mathrm{tight}}$, SR0$_{\mathrm{breq}}$, and SR5L for RPV models with the $\lambda_{12k}\neq 0$ coupling. All yields correspond to weighted events, so that effects from lepton reconstruction efficiencies, trigger corrections, pileup reweighting, etc., are included. They are normalized to the integrated luminosity of the data sample, $\int L dt = 139\,\mbox{fb\(^{-1}\)}$. The preliminary event reduction is a centralized stage where at least two electrons/muons with uncalibrated $p_{\mathrm{T}} >$ 9 GeV are required.
Cutflow event yields in regions SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$, SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$, and SR1$_{\mathrm{breq}}$ for RPV models with the $\lambda_{i33}\neq 0$ coupling. All yields correspond to weighted events, so that effects from lepton reconstruction efficiencies, trigger corrections, pileup reweighting, etc., are included. They are normalized to the integrated luminosity of the data sample, $\int L dt = 139\,\mbox{fb\(^{-1}\)}$. The preliminary event reduction is a centralized stage where at least two electrons/muons with uncalibrated $p_{\mathrm{T}} >$ 9 GeV are required.
Cutflow event yields in regions SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, and SR2$_{\mathrm{breq}}$ for RPV models with the $\lambda_{i33}\neq 0$ coupling. All yields correspond to weighted events, so that effects from lepton reconstruction efficiencies, trigger corrections, pileup reweighting, etc., are included. They are normalized to the integrated luminosity of the data sample, $\int L dt = 139\,\mbox{fb\(^{-1}\)}$. The preliminary event reduction is a centralized stage where at least two electrons/muons with uncalibrated $p_{\mathrm{T}} >$ 9 GeV are required.
Cutflow event yields in regions SR0-ZZ$^{\mathrm{loose}}$, SR0-ZZ$^{\mathrm{tight}}$, SR0-ZZ$_{\mathrm{bveto}}^{\mathrm{loose}}$, SR0-ZZ$_{\mathrm{bveto}}^{\mathrm{tight}}$, and SR5L the higgsino GGM RPC model with BR($\tilde{\chi}^{0}_1 \rightarrow Z \tilde{G}$) = 50% and higgsino masses of 200 GeV, or BR($\tilde{\chi}^{0}_1 \rightarrow Z \tilde{G}$) = 100% and higgsino masses of 300 GeV. All yields correspond to weighted events, so that effects from lepton reconstruction efficiencies, trigger corrections, pileup reweighting, etc., are included. They are normalized to the integrated luminosity of the data sample, $\int L dt = 139\,\mbox{fb\(^{-1}\)}$. The generator filter is a selection of $\geq$4e/$\mu$/$\tau_{\mathrm{had-vis}}$ leptons with $p_{\mathrm{T}}(e,\mu)>4$GeV, $p_{\mathrm{T}}(\tau_{\mathrm{had-vis}})>15$GeV and $|\eta|<2.8$ and is applied during the MC generation of the simulated events. The preliminary event reduction is a centralized stage where at least two electrons/muons with uncalibrated $p_{\mathrm{T}} > 9$ GeV are required.
A search for R-parity violating supersymmetry in final states characterised by high jet multiplicity, at least one isolated light lepton and either zero or at least three $b$-tagged jets is presented. The search uses 139 fb$^{-1}$ of $\sqrt{s} = 13$ TeV proton-proton collision data collected by the ATLAS experiment during Run 2 of the Large Hadron Collider. The results are interpreted in the context of R-parity-violating supersymmetry models that feature gluino production, top-squark production, or electroweakino production. The dominant sources of background are estimated using a data-driven model, based on observables at medium jet multiplicity, to predict the $b$-tagged jet multiplicity distribution at the higher jet multiplicities used in the search. Machine learning techniques are used to reach sensitivity to electroweakino production, extending the data-driven background estimation to the shape of the machine learning discriminant. No significant excess over the Standard Model expectation is observed and exclusion limits at the 95% confidence-level are extracted, reaching as high as 2.4 TeV in gluino mass, 1.35 TeV in top-squark mass, and 320 (365) GeV in higgsino (wino) mass.
The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 20 GeV jet $p_{\mathrm{T}}$ threshold regions defined for the EWK analysis in the $1\ell$ category for 4 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 20 GeV jet $p_{\mathrm{T}}$ threshold regions defined for the EWK analysis in the $1\ell$ category for 5 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 20 GeV jet $p_{\mathrm{T}}$ threshold regions defined for the EWK analysis in the $1\ell$ category for 6 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 20 GeV jet $p_{\mathrm{T}}$ threshold regions defined for the EWK analysis in the $1\ell$ category for 7 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 20 GeV jet $p_{\mathrm{T}}$ threshold regions defined for the EWK analysis in the $1\ell$ category for 8 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 20 GeV jet $p_{\mathrm{T}}$ threshold regions defined for the EWK analysis in the $1\ell$ category for 9 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 20 GeV jet $p_{\mathrm{T}}$ threshold regions defined for the EWK analysis in the $1\ell$ category for 10 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 20 GeV jet $p_{\mathrm{T}}$ threshold regions defined for the EWK analysis in the $1\ell$ category for 11 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 20 GeV jet $p_{\mathrm{T}}$ threshold regions defined for the EWK analysis in the $1\ell$ category for 12 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 20 GeV jet $p_{\mathrm{T}}$ threshold regions defined for the EWK analysis in the $1\ell$ category for 13 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 20 GeV jet $p_{\mathrm{T}}$ threshold regions defined for the EWK analysis in the $1\ell$ category for 14 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 20 GeV jet $p_{\mathrm{T}}$ threshold regions defined for the EWK analysis in the $1\ell$ category for at least 15 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 20 GeV jet $p_{\mathrm{T}}$ threshold regions defined for the EWK analysis in the $2\ell^{\mathrm{sc}}$ category for 4 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 20 GeV jet $p_{\mathrm{T}}$ threshold regions defined for the EWK analysis in the $2\ell^{\mathrm{sc}}$ category for 5 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 20 GeV jet $p_{\mathrm{T}}$ threshold regions defined for the EWK analysis in the $2\ell^{\mathrm{sc}}$ category for 6 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 20 GeV jet $p_{\mathrm{T}}$ threshold regions defined for the EWK analysis in the $2\ell^{\mathrm{sc}}$ category for 7 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 20 GeV jet $p_{\mathrm{T}}$ threshold regions defined for the EWK analysis in the $2\ell^{\mathrm{sc}}$ category for 8 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 20 GeV jet $p_{\mathrm{T}}$ threshold regions defined for the EWK analysis in the $2\ell^{\mathrm{sc}}$ category for 9 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 20 GeV jet $p_{\mathrm{T}}$ threshold regions defined for the EWK analysis in the $2\ell^{\mathrm{sc}}$ category for at least 10 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 20 GeV jet $p_{\mathrm{T}}$ threshold region in the $1\ell$ category for at least 15 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 40 GeV jet $p_{\mathrm{T}}$ threshold region in the $1\ell$ category for at least 12 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 60 GeV jet $p_{\mathrm{T}}$ threshold region in the $1\ell$ category for at least 11 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 80 GeV jet $p_{\mathrm{T}}$ threshold region in the $1\ell$ category for at least 10 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 100 GeV jet $p_{\mathrm{T}}$ threshold region in the $1\ell$ category for at least 8 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 20 GeV jet $p_{\mathrm{T}}$ threshold region in the $2\ell^{\mathrm{sc}}$ category for at least 10 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 40 GeV jet $p_{\mathrm{T}}$ threshold region in the $2\ell^{\mathrm{sc}}$ category for at least 8 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 60 GeV jet $p_{\mathrm{T}}$ threshold region in the $2\ell^{\mathrm{sc}}$ category for at least 7 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 80 GeV jet $p_{\mathrm{T}}$ threshold region in the $2\ell^{\mathrm{sc}}$ category for at least 7 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 100 GeV jet $p_{\mathrm{T}}$ threshold region in the $2\ell^{\mathrm{sc}}$ category for at least 6 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
Data event yields compared with the expected contributions from relevant background sources, in the discovery signal regions defined for the $1\ell$ category, as well as the observed and expected 95% CL model-independent upper limits on product of cross-section, acceptance and efficiency (in fb). The parameters of the model are determined in a fit to a reduced set of bins, corresponding to the model-independent fit discussed in the text.
Data event yields compared with the expected contributions from relevant background sources, in the discovery signal regions defined for the $2\ell^{\mathrm{sc}}$ category, as well as the observed and expected 95% CL model-independent upper limits on product of cross-section, acceptance and efficiency (in fb). The parameters of the model are determined in a fit to a reduced set of bins, corresponding to the model-independent fit discussed in the text.
Expected 95% CL exclusion contour for the gluino $\tilde{g}\rightarrow q\bar{q}\tilde{\chi}^0_1\rightarrow q\bar{q}q\bar{q} \ell\nu$ model.
Observed 95% CL exclusion contour for the gluino $\tilde{g}\rightarrow q\bar{q}\tilde{\chi}^0_1\rightarrow q\bar{q}q\bar{q} \ell\nu$ model.
Expected 95% CL exclusion contour for the gluino $\tilde{g}\rightarrow \bar{t}\tilde{t} \rightarrow \bar{t}\bar{b}\bar{s}$ model.
Observed 95% CL exclusion contour for the gluino $\tilde{g}\rightarrow \bar{t}\tilde{t} \rightarrow \bar{t}\bar{b}\bar{s}$ model.
Expected 95% CL exclusion contour for the gluino $\tilde{g}\rightarrow t\bar{t}\tilde{\chi}^0_1 \rightarrow t\bar{t} tbs$ model with bino LSP.
Observed 95% CL exclusion contour for the gluino $\tilde{g}\rightarrow t\bar{t}\tilde{\chi}^0_1 \rightarrow t\bar{t} tbs$ model with bino LSP.
Expected 95% CL exclusion contour for the gluino $\tilde{g}\rightarrow t\bar{t}\tilde{\chi}^0_1 \rightarrow t\bar{t} tbs$ model with higgsino LSP.
Observed 95% CL exclusion contour for the gluino $\tilde{g}\rightarrow t\bar{t}\tilde{\chi}^0_1 \rightarrow t\bar{t} tbs$ model with higgsino LSP.
Expected 95% CL exclusion contour for the gluino $\tilde{g}\rightarrow t\bar{t}\tilde{\chi}^0_1 \rightarrow t\bar{t} tbs$ model with wino LSP.
Observed 95% CL exclusion contour for the gluino $\tilde{g}\rightarrow t\bar{t}\tilde{\chi}^0_1 \rightarrow t\bar{t} tbs$ model with wino LSP.
Expected 95% CL exclusion contour for the stop pair production model with bino LSP.
Observed 95% CL exclusion contour for the stop pair production model with bino LSP.
Expected 95% CL exclusion contour for the stop pair production model with higgsino LSP.
Observed 95% CL exclusion contour for the stop pair production model with higgsino LSP.
Expected 95% CL exclusion contour for the stop pair production model with wino LSP.
Observed 95% CL exclusion contour for the stop pair production model with wino LSP.
Expected 95% CL excluded cross section for the RPV model with electroweakino prodiction with higgsino LSP hypothesis.
Observed 95% CL excluded cross section for the RPV model with electroweakino prodiction with higgsino LSP hypothesis.
Expected 95% CL excluded cross section for the RPV model with electroweakino prodiction with wino LSP hypothesis.
Observed 95% CL excluded cross section for the RPV model with electroweakino prodiction with wino LSP hypothesis.
Data event yields compared with the expected contributions from relevant background sources, in the discovery signal regions defined for the $1\ell$ category with 20 and 40 GeV jet $p_{\mathrm{T}}$ thresholds. The uncertainties across backgrounds can exhibit strong anticorrelations.
Data event yields compared with the expected contributions from relevant background sources, in the discovery signal regions defined for the $1\ell$ category with 60, 80 and 100 GeV jet $p_{\mathrm{T}}$ thresholds. The uncertainties across backgrounds can exhibit strong anticorrelations.
Data event yields compared with the expected contributions from relevant background sources, in the discovery signal regions defined for the $2\ell^{\mathrm{sc}}$ category with 20 and 40 GeV jet $p_{\mathrm{T}}$ thresholds. The uncertainties across backgrounds can exhibit strong anticorrelations.
Data event yields compared with the expected contributions from relevant background sources, in the discovery signal regions defined for the $2\ell^{\mathrm{sc}}$ category with 60, 80 and 100 GeV jet $p_{\mathrm{T}}$ thresholds. The uncertainties across backgrounds can exhibit strong anticorrelations.
Expected 95% CL excluded cross section for the gluino $\tilde{g}\rightarrow q\bar{q}\tilde{\chi}^0_1\rightarrow q\bar{q}q\bar{q} \ell\nu$ model.
Observed 95% CL excluded cross section for the gluino $\tilde{g}\rightarrow q\bar{q}\tilde{\chi}^0_1\rightarrow q\bar{q}q\bar{q} \ell\nu$ model.
Expected 95% CL excluded cross section for the gluino $\tilde{g}\rightarrow \bar{t}\tilde{t} \rightarrow \bar{t}\bar{b}\bar{s}$ model.
Observed 95% CL excluded cross section for the gluino $\tilde{g}\rightarrow \bar{t}\tilde{t} \rightarrow \bar{t}\bar{b}\bar{s}$ model.
Expected 95% CL excluded cross section for the gluino $\tilde{g}\rightarrow t\bar{t}\tilde{\chi}^0_1 \rightarrow t\bar{t} tbs$ model with bino LSP.
Observed 95% CL excluded cross section for the gluino $\tilde{g}\rightarrow t\bar{t}\tilde{\chi}^0_1 \rightarrow t\bar{t} tbs$ model with bino LSP.
Expected 95% CL excluded cross section for the gluino $\tilde{g}\rightarrow t\bar{t}\tilde{\chi}^0_1 \rightarrow t\bar{t} tbs$ model with wino LSP.
Observed 95% CL excluded cross section for the gluino $\tilde{g}\rightarrow t\bar{t}\tilde{\chi}^0_1 \rightarrow t\bar{t} tbs$ model with wino LSP.
Expected 95% CL excluded cross section for the gluino $\tilde{g}\rightarrow t\bar{t}\tilde{\chi}^0_1 \rightarrow t\bar{t} tbs$ model with higgsino LSP.
Observed 95% CL excluded cross section for the gluino $\tilde{g}\rightarrow t\bar{t}\tilde{\chi}^0_1 \rightarrow t\bar{t} tbs$ model with higgsino LSP.
Expected 95% CL excluded cross section for the stop pair production model with bino LSP.
Observed 95% CL excluded cross section for the stop pair production model with bino LSP.
Expected 95% CL excluded cross section for the stop pair production model with wino LSP.
Observed 95% CL excluded cross section for the stop pair production model with wino LSP.
Expected 95% CL excluded cross section for the stop pair production model with higgsino LSP.
Observed 95% CL excluded cross section for the stop pair production model with higgsino LSP.
Acceptance and efficiency for the gluino $\tilde{g}\rightarrow q\bar{q}\tilde{\chi}^0_1\rightarrow q\bar{q}q\bar{q} \ell\nu$ model in the $1\ell$ category.
Acceptance and efficiency for the gluino $\tilde{g}\rightarrow q\bar{q}\tilde{\chi}^0_1\rightarrow q\bar{q}q\bar{q} \ell\nu$ model in the $2\ell^{\mathrm{sc}}$ category.
Acceptance and efficiency for the gluino $\tilde{g}\rightarrow \bar{t}\tilde{t} \rightarrow \bar{t}\bar{b}\bar{s}$ model in the $1\ell$ category.
Acceptance and efficiency for the gluino $\tilde{g}\rightarrow \bar{t}\tilde{t} \rightarrow \bar{t}\bar{b}\bar{s}$ model in the $2\ell^{\mathrm{sc}}$ category.
Acceptance and efficiency for the gluino $\tilde{g}\rightarrow t\bar{t}\tilde{\chi}^0_1 \rightarrow t\bar{t} tbs$ model with higgsino LSP in the $1\ell$ category.
Acceptance and efficiency for the gluino $\tilde{g}\rightarrow t\bar{t}\tilde{\chi}^0_1 \rightarrow t\bar{t} tbs$ model with higgsino LSP in the $2\ell^{\mathrm{sc}}$ category.
Acceptance and efficiency for the stop model with higgsino LSP in the $1\ell$ category.
Acceptance and efficiency for the stop model with higgsino LSP in the $2\ell^{\mathrm{sc}}$ category.
Acceptance and efficiency for the or the electroweakino production model in the EWK analysis discovery SR for the $1\ell$ category with 4 jets, considering $\tilde{\chi}^{\pm}_1 \tilde{\chi}^0_1$ production.
Acceptance and efficiency for the or the electroweakino production model in the EWK analysis discovery SR for the $1\ell$ category with 5 jets, considering $\tilde{\chi}^{\pm}_1 \tilde{\chi}^0_1$ production.
Acceptance and efficiency for the or the electroweakino production model in the EWK analysis discovery SR for the $1\ell$ category with 6 jets, considering $\tilde{\chi}^{\pm}_1 \tilde{\chi}^0_1$ production.
Acceptance and efficiency for the or the electroweakino production model in the EWK analysis discovery SR for the $1\ell$ category with 7 jets, considering $\tilde{\chi}^{\pm}_1 \tilde{\chi}^0_1$ production.
Acceptance and efficiency for the or the electroweakino production model in the EWK analysis discovery SR for the $1\ell$ category with 8 jets, considering $\tilde{\chi}^{\pm}_1 \tilde{\chi}^0_1$ production.
Acceptance and efficiency for the or the electroweakino production model in the EWK analysis discovery SR for the $2\ell^{\mathrm{sc}}$ category, considering $\tilde{\chi}^{\pm}_1 \tilde{\chi}^0_1$ production.
Acceptance and efficiency for the or the electroweakino production model in the EWK analysis discovery SR for the $1\ell$ category with 4 jets, considering $\tilde{\chi}^0_1 \tilde{\chi}^0_2$ production.
Acceptance and efficiency for the or the electroweakino production model in the EWK analysis discovery SR for the $1\ell$ category with 5 jets, considering $\tilde{\chi}^0_1 \tilde{\chi}^0_2$ production.
Acceptance and efficiency for the or the electroweakino production model in the EWK analysis discovery SR for the $1\ell$ category with 6 jets, considering $\tilde{\chi}^0_1 \tilde{\chi}^0_2$ production.
Acceptance and efficiency for the or the electroweakino production model in the EWK analysis discovery SR for the $1\ell$ category with 7 jets, considering $\tilde{\chi}^0_1 \tilde{\chi}^0_2$ production.
Acceptance and efficiency for the or the electroweakino production model in the EWK analysis discovery SR for the $1\ell$ category with 8 jets, considering $\tilde{\chi}^0_1 \tilde{\chi}^0_2$ production.
Acceptance and efficiency for the or the electroweakino production model in the EWK analysis discovery SR for the $2\ell^{\mathrm{sc}}$ category, considering $\tilde{\chi}^0_1 \tilde{\chi}^0_2$ production.
Cut flow for the gluino $\tilde{g}\rightarrow q\bar{q}\tilde{\chi}^0_1\rightarrow q\bar{q}q\bar{q} \ell\nu$ model with $m_{\tilde{g}} = 2$ TeV and $m_{\tilde{\chi}^0_1} = 1$ TeV. The column labelled $\mathrm{N}_{\mathrm{raw}}$ shows the number of generated events, while $\mathrm{N}_{\mathrm{events}}$ shows the expected number of events with a luminosity of 139fb$^{−1}$. The last column shows the cut flow efficiency with respect to all weighted events. The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies $p_{\mathrm{T}} > 25$ GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed. Selections that have not been evaluated in the analysis or are not applicable are denoted with a dash (--).
Cut flow for the gluino $\tilde{g}\rightarrow \bar{t}\tilde{t} \rightarrow \bar{t}\bar{b}\bar{s}$ model with with $m_{\tilde{g}} = 1.6$ TeV and $m_{\tilde{t}} = 1$ TeV. The column labelled $\mathrm{N}_{\mathrm{raw}}$ shows the number of generated events, while $\mathrm{N}_{\mathrm{events}}$ shows the expected number of events with a luminosity of 139fb$^{−1}$. The last column shows the cut flow efficiency with respect to all weighted events. The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies $p_{\mathrm{T}} > 25$ GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed. Selections that have not been evaluated in the analysis or are not applicable are denoted with a dash (--).
Cut flow for the gluino $\tilde{g}\rightarrow t\bar{t}\tilde{\chi}^0_1 \rightarrow t\bar{t} tbs$ model with $m_{\tilde{g}} = 2.2$ TeV and $m_{\tilde{\chi}^0_1} = 1.05$ TeV. The column labelled $\mathrm{N}_{\mathrm{raw}}$ shows the number of generated events, while $\mathrm{N}_{\mathrm{events}}$ shows the expected number of events with a luminosity of 139fb$^{−1}$. The last column shows the cut flow efficiency with respect to all weighted events. The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies $p_{\mathrm{T}} > 25$ GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed. Selections that have not been evaluated in the analysis or are not applicable are denoted with a dash (--).
Cut flow for the stop model with $m_{\tilde{t}} = 1.175$ TeV and $m_{\tilde{\chi}^0_1} = 0.7$ TeV. The column labelled $\mathrm{N}_{\mathrm{raw}}$ shows the number of generated events, while $\mathrm{N}_{\mathrm{events}}$ shows the expected number of events with a luminosity of 139fb$^{−1}$. The last column shows the cut flow efficiency with respect to all weighted events. The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies $p_{\mathrm{T}} > 25$ GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed. Selections that have not been evaluated in the analysis or are not applicable are denoted with a dash (--).
Cut flow for the electroweakino production model, considering only the production of $\tilde{\chi}^{\pm}_1 \tilde{\chi}^0_1$, with $m(\tilde{\chi}^{\pm}_1,\tilde{\chi}^0_1)= 250$ GeV. The column labelled $\mathrm{N}_{\mathrm{raw}}$ shows the number of generated events, while $\mathrm{N}_{\mathrm{events}}$ shows the expected number of events with a luminosity of 139fb$^{−1}$. The last column shows the cut flow efficiency with respect to all weighted events. The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies $p_{\mathrm{T}} > 25$ GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed. In the $2\ell^{\mathrm{sc}}$ category no events are expected, as only one lepton is expected to be produced in the decay.Selections that have not been evaluated in the analysis or are not applicable are denoted with a dash (--).
Cut flow for the electroweakino production model, considering only the production of $\tilde{\chi}^0_1 \tilde{\chi}^0_2$, with $m(\tilde{\chi}^0_1,\tilde{\chi}^0_2)= 250$ GeV. The column labelled $\mathrm{N}_{\mathrm{raw}}$ shows the number of generated events, while $\mathrm{N}_{\mathrm{events}}$ shows the expected number of events with a luminosity of 139fb$^{−1}$. The last column shows the cut flow efficiency with respect to all weighted events. The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies $p_{\mathrm{T}} > 25$ GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed. Selections that have not been evaluated in the analysis or are not applicable are denoted with a dash (--).
This paper presents a statistical combination of searches targeting final states with two top quarks and invisible particles, characterised by the presence of zero, one or two leptons, at least one jet originating from a $b$-quark and missing transverse momentum. The analyses are searches for phenomena beyond the Standard Model consistent with the direct production of dark matter in $pp$ collisions at the LHC, using 139 fb$^{-\text{1}}$ of data collected with the ATLAS detector at a centre-of-mass energy of 13 TeV. The results are interpreted in terms of simplified dark matter models with a spin-0 scalar or pseudoscalar mediator particle. In addition, the results are interpreted in terms of upper limits on the Higgs boson invisible branching ratio, where the Higgs boson is produced according to the Standard Model in association with a pair of top quarks. For scalar (pseudoscalar) dark matter models, with all couplings set to unity, the statistical combination extends the mass range excluded by the best of the individual channels by 50 (25) GeV, excluding mediator masses up to 370 GeV. In addition, the statistical combination improves the expected coupling exclusion reach by 14% (24%), assuming a scalar (pseudoscalar) mediator mass of 10 GeV. An upper limit on the Higgs boson invisible branching ratio of 0.38 (0.30$^{+\text{0.13}}_{-\text{0.09}}$) is observed (expected) at 95% confidence level.
Post-fit signal region yields for the tt0L-high and the tt0L-low analyses. The bottom panel shows the statistical significance of the difference between the SM prediction and the observed data in each region. '$t\bar{t}$ (other)' represents $t\bar{t}$ events without extra jets or events with extra light-flavour jets. 'Other' includes contributions from $t\bar{t}W$, $tZ$ and $tWZ$ processes. The total uncertainty in the SM expectation is represented with hatched bands and the expected distributions for selected signal models are shown as dashed lines.
Representative fit distribution in the signal region for the tt1L analysis: each bin of such distribution corresponds to a single SR included in the fit. 'Other' includes contributions from $t\bar{t}W$, $tZ$, $tWZ$ and $t\bar{t}$ (semileptonic) processes. The total uncertainty in the SM expectation is represented with hatched bands and the expected distributions for selected signal models are shown as dashed lines.
Representative fit distribution in the same flavour leptons signal region for the tt2L analysis: each bin of such distribution, starting from the red arrow, corresponds to a single SR included in the fit. 'FNP' includes the contribution from fake/non-prompt lepton background arising from jets (mainly $\pi/K$, heavy-flavour hadron decays and photon conversion) misidentified as leptons, estimated in a purely data-driven way. 'Other' includes contributions from $t\bar{t}W$, $tZ$ and $tWZ$ processes. The total uncertainty in the SM expectation is represented with hatched bands and the expected distributions for selected signal models are shown as dashed lines.
Summary of the total uncertainty in the background prediction for each SR of the tt0L-low, tt0L-high, tt1L and tt2L analysis channels in the statistical combination. Their dominant contributions are indicated by individual lines. Individual uncertainties can be correlated, and do not necessarily add up in quadrature to the total background uncertainty.
Exclusion limits for colour-neutral scalar mediator dark matter models as a function of the mediator mass $m(\phi)$ for a DM mass $m_{\chi} = 1$ GeV. Associated production of DM with both single top quarks ($tW$ and $tj$ channels) and top quark pairs is considered. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross section to the cross section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines show the observed (expected) exclusion limits for each individual channel and their statistical combination.
Exclusion limits for colour-neutral pseudoscalar mediator dark matter models as a function of the mediator mass $m(a)$ for a DM mass $m_{\chi} = 1$ GeV. Associated production of DM with both single top quarks ($tW$ and $tj$ channels) and top quark pairs is considered. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross section to the cross section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines show the observed (expected) exclusion limits for each individual channel and their statistical combination.
$E_{\text{T}}^{\text{miss}}$ distribution in SR0X for the tt0L-low analysis. The contributions from all SM backgrounds are shown after the profile likelihood simultaneous fit to all tt0L-low CRs, with the hatched bands representing the total uncertainty. The category '$t\bar{t}$ (other)' represents $t\bar{t}$ events without extra jets or events with extra light-flavour jets. 'Other' includes contributions from $t\bar{t}W$, $tZ$ and $tWZ$ processes. The expected distributions for selected signal models are shown as dashed lines. The overflow events are included in the last bin. The bottom panels show the ratio of the observed data to the total SM background prediction, with the hatched area representing the total uncertainty in the background prediction and the red arrows marking data outside the vertical-axis range.
$E_{\text{T}}^{\text{miss}}$ distribution in SRWX for the tt0L-low analysis. The contributions from all SM backgrounds are shown after the profile likelihood simultaneous fit to all tt0L-low CRs, with the hatched bands representing the total uncertainty. The category '$t\bar{t}$ (other)' represents $t\bar{t}$ events without extra jets or events with extra light-flavour jets. 'Other' includes contributions from $t\bar{t}W$, $tZ$ and $tWZ$ processes. The expected distributions for selected signal models are shown as dashed lines. The overflow events are included in the last bin. The bottom panels show the ratio of the observed data to the total SM background prediction, with the hatched area representing the total uncertainty in the background prediction and the red arrows marking data outside the vertical-axis range.
$E_{\text{T}}^{\text{miss}}$ distribution in SRTX for the tt0L-low analysis. The contributions from all SM backgrounds are shown after the profile likelihood simultaneous fit to all tt0L-low CRs, with the hatched bands representing the total uncertainty. The category '$t\bar{t}$ (other)' represents $t\bar{t}$ events without extra jets or events with extra light-flavour jets. 'Other' includes contributions from $t\bar{t}W$, $tZ$ and $tWZ$ processes. The expected distributions for selected signal models are shown as dashed lines. The overflow events are included in the last bin. The bottom panels show the ratio of the observed data to the total SM background prediction, with the hatched area representing the total uncertainty in the background prediction and the red arrows marking data outside the vertical-axis range.
Exclusion limits for colour-neutral scalar mediator dark matter models as a function of the mediator mass $m(\phi)$ for a DM mass $m_{\chi} = 1$ GeV. Associated production of DM with both single top quarks ($tW$ and $tj$ channels) and top quark pairs is considered. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross section to the nominal cross section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines show the observed (expected) exclusion limits for the tt0L-high and tt0L-low analyses and their statistical combination.
Exclusion limits for colour-neutral pseudoscalar mediator dark matter models as a function of the mediator mass $m(a)$ for a DM mass $m_{\chi} = 1$ GeV. Associated production of DM with both single top quarks ($tW$ and $tj$ channels) and top quark pairs is considered. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross section to the nominal cross section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines show the observed (expected) exclusion limits for the tt0L-high and tt0L-low analyses and their statistical combination.
Exclusion limits for colour-neutral scalar mediator dark matter models as a function of the mediator mass $m(\phi)$ for a DM mass $m_{\chi} = 1$ GeV. Only associated production of DM with top quark pairs is considered for this interpretation. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross section to the cross section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines show the observed (expected) exclusion limits for each individual channel and their statistical combination.
Exclusion limits for colour-neutral pseudoscalar mediator dark matter models as a function of the mediator mass $m(a)$ for a DM mass $m_{\chi} = 1$ GeV. Only associated production of DM with top quark pairs is considered for this interpretation. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross section to the cross section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines show the observed (expected) exclusion limits for each individual channel and their statistical combination.
Exclusion limits for colour-neutral scalar mediator dark matter models as a function of the mediator mass $m(\phi)$ for a DM mass $m_{\chi} = 1$ GeV. Only associated production of DM with top quark pairs is considered for this interpretation. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross section to the nominal cross section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines show the observed (expected) exclusion limits for the tt0L-high and tt0L-low analyses and their statistical combination.
Exclusion limits for colour-neutral pseudoscalar mediator dark matter models as a function of the mediator mass $m(a)$ for a DM mass $m_{\chi} = 1$ GeV. Only associated production of DM with top quark pairs is considered for this interpretation. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross section to the nominal cross section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines show the observed (expected) exclusion limits for the tt0L-high and tt0L-low analyses and their statistical combination.
Representative fit distribution in the different flavour leptons signal region for the tt2L analysis: each bin of such distribution, starting from the red arrow, corresponds to a single SR included in the fit. 'FNP' includes the contribution from fake/non-prompt lepton background arising from jets (mainly $\pi/K$, heavy-flavour hadron decays and photon conversion) misidentified as leptons, estimated in a purely data-driven way. 'Other' includes contributions from $t\bar{t}W$, $tZ$ and $tWZ$ processes. The total uncertainty in the SM expectation is represented with hatched bands and the expected distributions for selected signal models are shown as dashed lines.
Signal acceptance in SR0X, SRWX and SRTX for simplified DM+$t\bar{t}$ model, defined as the number of accepted events at generator level in signal Monte Carlo simulation divided by the total number of events in the sample.
Signal acceptance in SR0X, SRWX and SRTX for simplified DM+$tW$ model, defined as the number of accepted events at generator level in signal Monte Carlo simulation divided by the total number of events in the sample.
Signal acceptance in SR0X, SRWX and SRTX for simplified DM+$tj$ model, defined as the number of accepted events at generator level in signal Monte Carlo simulation divided by the total number of events in the sample.
Signal efficiency in SR0X, SRWX and SRTX for simplified DM+$t\bar{t}$ model, defined as the number of selected reconstructed events divided by the acceptance.
Signal efficiency in SR0X, SRWX and SRTX for simplified DM+$tW$ model, defined as the number of selected reconstructed events divided by the acceptance.
Signal efficiency in SR0X, SRWX and SRTX for simplified DM+$tj$ model, defined as the number of selected reconstructed events divided by the acceptance.
Cutflow for the reference point DM+$t\bar{t}$ $m(\phi, \chi) = (10, 1)$ GeV in signal region SR0X. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 2045000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$t\bar{t}$ $m(\phi, \chi) = (10, 1)$ GeV in signal region SRWX. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 2045000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$t\bar{t}$ $m(\phi, \chi) = (10, 1)$ GeV in signal region SRTX. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 2045000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$t\bar{t}$ $m(a, \chi) = (10, 1)$ GeV in signal region SR0X. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 400000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$t\bar{t}$ $m(a, \chi) = (10, 1)$ GeV in signal region SRWX. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 400000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$t\bar{t}$ $m(a, \chi) = (10, 1)$ GeV in signal region SRTX. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 400000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$tW$ $m(\phi, \chi) = (10, 1)$ GeV in signal region SR0X. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 120000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$tW$ $m(\phi, \chi) = (10, 1)$ GeV in signal region SRWX. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 120000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$tW$ $m(\phi, \chi) = (10, 1)$ GeV in signal region SRTX. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 120000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$tW$ $m(a, \chi) = (10, 1)$ GeV in signal region SR0X. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 100000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$tW$ $m(a, \chi) = (10, 1)$ GeV in signal region SRWX. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 100000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$tW$ $m(a, \chi) = (10, 1)$ GeV in signal region SRTX. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 100000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$tj$ $m(\phi, \chi) = (10, 1)$ GeV in signal region SR0X. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 169000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$tj$ $m(\phi, \chi) = (10, 1)$ GeV in signal region SRWX. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 169000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$tj$ $m(\phi, \chi) = (10, 1)$ GeV in signal region SRTX. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 169000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$tj$ $m(a, \chi) = (10, 1)$ GeV in signal region SR0X. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 140000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$tj$ $m(a, \chi) = (10, 1)$ GeV in signal region SRWX. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 140000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$tj$ $m(a, \chi) = (10, 1)$ GeV in signal region SRTX. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 140000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Measurements of Higgs boson production cross-sections are carried out in the diphoton decay channel using 139 fb$^{-1}$ of $pp$ collision data at $\sqrt{s} = 13$ TeV collected by the ATLAS experiment at the LHC. The analysis is based on the definition of 101 distinct signal regions using machine-learning techniques. The inclusive Higgs boson signal strength in the diphoton channel is measured to be $1.04^{+0.10}_{-0.09}$. Cross-sections for gluon-gluon fusion, vector-boson fusion, associated production with a $W$ or $Z$ boson, and top associated production processes are reported. An upper limit of 10 times the Standard Model prediction is set for the associated production process of a Higgs boson with a single top quark, which has a unique sensitivity to the sign of the top quark Yukawa coupling. Higgs boson production is further characterized through measurements of Simplified Template Cross-Sections (STXS). In total, cross-sections of 28 STXS regions are measured. The measured STXS cross-sections are compatible with their Standard Model predictions, with a $p$-value of $93\%$. The measurements are also used to set constraints on Higgs boson coupling strengths, as well as on new interactions beyond the Standard Model in an effective field theory approach. No significant deviations from the Standard Model predictions are observed in these measurements, which provide significant sensitivity improvements compared to the previous ATLAS results.
Cross-sections times H->yy branching ratio for ggF +bbH, VBF, VH, ttH, and tH production, normalized to their SM predictions. The values are obtained from a simultaneous fit to all categories. The theory uncertainties in the predictions include uncertainties due to missing higher-order terms in the perturbative QCD calculations and choices of parton distribution functions and value of alpha_s, as well as the H->yy branching ratio uncertainty.
Correlation matrix for the measurement of production cross-sections of the Higgs boson times the H->yy branching ratio.
Best-fit values and uncertainties for STXS parameters in each of the 28 regions considered, normalized to their SM predictions. The values for the gg->H process also include the contributions from bbH production.
Correlation matrix for the measurement of STXS parameters in each of the 28 regions considered.
Fitted values for kappa_g and kappa_y.
Correlation matrix for the measurement of kappa_g and kappa_y.
Summary of the 68% CL confidence intervals for individual measurements of SMEFT parameters observed in data. In each case, SMEFT parameters other than the one measured are fixed to 0.
Results of the EV parameter measurement in data, in the linear and linear+quadratic parameterizations of the SMEFT. All the EVs parameters are free to vary in the fits. The ranges correspond to 68% CL confidence intervals.
Observed linear correlation coefficients of the EVs parameters in the linear parameterization.
Observed linear correlation coefficients of the EVs parameters in the linear+quadratic parameterization.
Cross-sections times H->yy branching ratio for ggF +bbH, VBF, VH, ttH, and tH production. The values are obtained from a simultaneous fit to all categories. The theory uncertainties in the predictions include uncertainties due to missing higher-order terms in the perturbative QCD calculations and choices of parton distribution functions and value of alpha_s, as well as the H->yy branching ratio uncertainty.
Best-fit values and uncertainties for STXS parameters in each of the 28 regions considered. The values for the gg->H process also include the contributions from bbH production.
Correlation matrix for the measurement of STXS parameters in each of the 33 regions considered.
This article presents the results of two studies of Higgs boson properties using the $WW^*(\rightarrow e\nu\mu\nu)jj$ final state, based on a dataset corresponding to 36.1/fb of $\sqrt{s}$=13 TeV proton$-$proton collisions recorded by the ATLAS experiment at the Large Hadron Collider. The first study targets Higgs boson production via gluon$-$gluon fusion and constrains the CP properties of the effective Higgs$-$gluon interaction. Using angular distributions and the overall rate, a value of $\tan(\alpha) = 0.0 \pm 0.4$ stat. $ \pm 0.3$ syst is obtained for the tangent of the mixing angle for CP-even and CP-odd contributions. The second study exploits the vector-boson fusion production mechanism to probe the Higgs boson couplings to longitudinally and transversely polarised $W$ and $Z$ bosons in both the production and the decay of the Higgs boson; these couplings have not been directly constrained previously. The polarisation-dependent coupling-strength scale factors are defined as the ratios of the measured polarisation-dependent coupling strengths to those predicted by the Standard Model, and are determined using rate and kinematic information to be $a_L=0.91^{+0.10}_{-0.18}$(stat.)$^{+0.09}_{-0.17}$(syst.) and $a_{T}=1.2 \pm 0.4 $(stat.)$ ^{+0.2}_{-0.3} $(syst.). These coupling strengths are translated into pseudo-observables, resulting in $\kappa_{VV}= 0.91^{+0.10}_{-0.18}$(stat.)$^{+0.09}_{-0.17}$(syst.) and $\epsilon_{VV} =0.13^{+0.28}_{-0.20}$ (stat.)$^{+0.08}_{-0.10}$(syst.). All results are consistent with the Standard Model predictions.
Post-fit NFs and their uncertainties for the Z+jets, top and WW backgrounds. Both sets of normalisation factors differ slightly depending on which (B)SM model is tested, but are consistent within their total uncertainties.
Post-fit event yields in the signal and control regions obtained from the study of the signal strength parameter $\mu^{\text{ggF+2jets}}$. The quoted uncertainties include the theoretical and experimental systematic sources and those due to sample statistics. The fit constrains the total expected yield to the observed yield. The diboson background is split into $W W$ and non-$W W$ contributions.
Breakdown of the main contributions to the total uncertainty on $\tan \alpha$ based on the fit that exploits both shape and rate information. Individual sources of systematic uncertainty are grouped into either the theoretical or the experimental uncertainty. The sum in quadrature of the individual components differs from the total uncertainty due to correlations between the components.
Post-fit event yields in the signal and control regions obtained from a scan over $\epsilon_{VV}$ exploiting both shape and rate information. The quoted uncertainties include the theoretical and experimental systematic sources and those due to sample statistics. The fit constrains the total expected yield to the observed yield. The diboson background is split into $W W$ and non-$W W$ contributions.
Best-fit values and their uncertainties as obtained from the shape-only and shape-plus-rate likelihood fits to the Asimov dataset and to ATLAS data. Results of both shape-only and shape+rate fits for $a_L$ and $a_T$ are shown. Results of fits to one parameter with the other one fixed or profiled are presented.
Best-fit values and their uncertainties as obtained from the shape-only and shape-plus-rate likelihood fits to the Asimov dataset and to ATLAS data. Results of both shape-only and shape+rate fits for $\epsilon_{VV}$ and $\kappa_{VV}$ are shown. Results of fits to one parameter with the other one fixed or profiled are presented.
The contributions of the leading individual systematic uncertainties together with the data statistical uncertainties, in the one dimensional fit for the pseudo-observables $\kappa_{VV}$ (a) and $\epsilon_{VV}$ (b) for electroweak-boson polarisation in the VBF $H\to WW$ channel. Both shape and rate informations are exploited in the fit. The theoretical and experimental uncertainties are subdivided further into categories.
The contributions of the leading individual systematic uncertainties together with the data statistical uncertainties, in the one dimensional fit for the pseudo-observables $\kappa_{VV}$ (a) and $\epsilon_{VV}$ (b) for electroweak-boson polarisation in the VBF $H\to WW$ channel. Both shape and rate informations are exploited in the fit. The theoretical and experimental uncertainties are subdivided further into categories.
Post-fit distribution of the BDT response observable presented in the four $|\Delta \eta jj|$ categories of the ggF +2 jets signal region, with signal and background yields fixed from the fit for $\mu^{\text{ggF+2jets}}$. The distributions of the ggF + 2 jets and VBF processes are overlaid with their respective contributions multiplied by 50.
The weighted $\Delta \Phi_{jj}$ post-fit distribution in the ggF +2 jets signal region, with signal and background yields fixed from the fit to $\tan \alpha$ using shape and rate information.
Expected and observed likelihood curves for scans over $\tan \alpha$ where only the shape is taken into account in the fit, $\mu_{VBF}$ is fixed.
Expected and observed likelihood curves for scans over $\tan \alpha$ where both shape and normalisation are taken into account in the fit, $\mu_{VBF}$ is fixed.
68% and 95% CL two-dimensional likelihood contours of the CP-even and CP-odd coupling parameters $K_{gg} \cos(\alpha)$ and $K_{gg} \sin(\alpha)$. The minima are represented by black stars, while the SM value is shown as a red star.
The weighted $\Delta \Phi jj$ distribution in the VBF signal region, with signal and background yields fixed from the fit for $\epsilon_{VV}$ using shape and rate information.
Likelihood scans over the transversally polarised couplings. The fit is using shape-only information. All relevant experimental and modelling systematic uncertainties are considered in the fit.
Likelihood scans over the transversally polarised couplings. The fit is using shape + rate information. All relevant experimental and modelling systematic uncertainties are considered in the fit.
Likelihood scans over the longitudinally polarised couplings. The fit is using shape + rate information. All relevant experimental and modelling systematic uncertainties are considered in the fit.
Likelihood scans over $\kappa_{VV}$ with the $\epsilon_{VV}$ profiled. The fit is performed using both shape and rate information. All relevant experimental and theoretical systematic uncertainties are considered in the fit.
Likelihood scans over $\epsilon_{VV}$ with the $\kappa_{VV}$ profiled. The fit is performed using both shape and rate information. All relevant experimental and theoretical systematic uncertainties are considered in the fit.
The contributions of the leading individual systematic uncertainties together with the data statistical uncertainties, in the one dimensional fit for electroweak-boson polarisation in the VBF $H\to WW$ channel, using (aL, aT) parametrisation. Both shape and rate informations are exploited in the fit. The theoretical and experimental uncertainties are subdivided further into categories.
The contributions of the leading individual systematic uncertainties together with the data statistical uncertainties, in the one dimensional fit for electroweak-boson polarisation in the VBF $H\to WW$ channel, using (aL, aT) parametrisation.. Both shape and rate informations are exploited in the fit. The theoretical and experimental uncertainties are subdivided further into categories.
A search for Higgs boson pair production in events with two $b$-jets and two $\tau$-leptons is presented, using a proton-proton collision dataset with an integrated luminosity of 139 fb$^{-1}$ collected at $\sqrt{s}=13$ TeV by the ATLAS experiment at the LHC. Higgs boson pairs produced non-resonantly or in the decay of a narrow scalar resonance in the mass range from 251 to 1600 GeV are targeted. Events in which at least one $\tau$-lepton decays hadronically are considered, and multivariate discriminants are used to reject the backgrounds. No significant excess of events above the expected background is observed in the non-resonant search. The largest excess in the resonant search is observed at a resonance mass of 1 TeV, with a local (global) significance of $3.1\sigma$ ($2.0\sigma$). Observed (expected) 95% confidence-level upper limits are set on the non-resonant Higgs boson pair-production cross-section at 4.7 (3.9) times the Standard Model prediction, assuming Standard Model kinematics, and on the resonant Higgs boson pair-production cross-section at between 21 and 900 fb (12 and 840 fb), depending on the mass of the narrow scalar resonance.
Breakdown of the relative contributions to the uncertainty in the extracted signal cross-sections, as determined in the likelihood fit (described in Section 8) to data. These are obtained by fixing the relevant nuisance parameters in the likelihood fit, and subtracting the obtained uncertainty on the fitted signal cross-sections in quadrature from the total uncertainty, and then dividing the result by the total uncertainty. The sum in quadrature of the individual components differs from the total uncertainty due to correlations between uncertainties in the different groups.
Post-fit expected number of signal and background events and observed number of data events in the last two bins of the non-resonant BDT score distribution of the SM signal after applying the selection criteria and requiring exactly 2 b-tagged jets and assuming a background-only hypothesis
Observed and expected upper limits at 95% CL on the cross-section of non-resonant HH production according to SM-like kinematics, and on the cross-section of non-resonant HH production divided by the SM prediction. The 1 sigma and 2 sigma variations around the expected limit are also shown.
Cumulative efficiency for simulated signal events to pass each stage of the event selection in the hadhad category. The efficiencies are calculated with respect to HH to bbtautau decays in which both tau-leptons decay hadronically. The ‘Pre-selection’ consists of basic requirements, including that at least two tau-had-vis pass loose kinematic requirements, at least one of the tau-had-vis candidate passes identification requirement, and that events do not contain an electron or muon. The ‘Object selections’ require exactly two tau-had-vis candidates, and at least two jets with pT > 25 GeV and abs(eta) < 2.5. The ‘Loose tau ID’ requires that both tau-had-vis candidates pass identification requirements. The ‘DTT offline jet cuts’ are cuts placed on the pT of the reconstructed jet or tau-had-vis that are geometrically matched to the HLT objects, to ensure the efficiencies of the HLT objects reach the plateau region.
Cumulative efficiency for simulated signal events to pass each stage of the event selection in the lephad SLT category. The efficiencies are calculated with respect to HH to bbtautau decays in which one tau-lepton decays hadronically and one decays leptonically. The ‘Pre-selection’ consists of basic requirements, including that at least one tau-had-vis candidate and one lepton pass loose kinematic requirements. The ‘Object selections’ require exactly one tau-had-vis candidate, and at least two jets with pT > 25 GeV and abs(eta) < 2.5. The ‘Trigger specific offline pT cuts’ are cuts placed on the pT of the reconstructed jet or tau-had-vis that are geometrically matched to the HLT objects, to ensure the efficiencies of the HLT objects reach the plateau region.
Cumulative efficiency for simulated signal events to pass each stage of the event selection in the lephad LTT category. The efficiencies are calculated with respect to HH to bbtautau decays in which one tau-lepton decays hadronically and one decays leptonically. The ‘Pre-selection’ consists of basic requirements, including that at least one tau-had-vis candidate and one lepton pass loose kinematic requirements. The ‘Object selections’ require exactly one tau-had-vis candidate, and at least two jets with pT > 25 GeV and abs(eta) < 2.5. The ‘Trigger specific offline pT cuts’ are cuts placed on the pT of the reconstructed jet or tau-had-vis that are geometrically matched to the HLT objects, to ensure the efficiencies of the HLT objects reach the plateau region.
Post-fit expected number of signal and background events and observed number of data events after applying the selection criteria and requiring exactly 2 b-tagged jets and assuming a background-only hypothesis.
Observed and expected limits at 95% CL on the cross-section of HH production, for the non-resonant ggF+VBF HH search, and the resonant HH search for four values of the resonance mass mX.
Acceptance times efficiency for the full analysis selections as a function of the resonance mass mX in the hadhad, lephad SLT and lephad LTT trigger categories, and the combined lephad. The acceptance times efficiency is evaluated for HH to bbtautau decays, with respect to the targeted tau-lepton decay modes (lephad or hadhad).
Post-fit distribution of mHH in the hadhad channel.
Post-fit distribution of mHH in the lephad SLT channel.
Post-fit distribution of mHH in the lephad LTT channel.
Post-fit distribution of mtautau MMC in the hadhad channel.
Post-fit distribution of mtautau MMC in the hadhad channel.
Post-fit distribution of mtautau MMC in the hadhad channel.
Post-fit distribution of of di-b-jet mass in the hadhad channel.
Post-fit distribution of di-b-jet mass in the LTT lephad channel.
Post-fit distribution of di-b-jet mass in the LTT lephad channel.
BDT for SM HH in the hadhad channel
NN for SM HH in the lephad SLT channel
NN for SM HH in the lephad LTT channel
PNN for mX = 500 GeV resonant HH in the hadhad channel
PNN for mX = 500 GeV resonant HH in the lephad SLT channel
PNN for mX = 500 GeV resonant HH in the lephad LTT channel
PNN for mX = 1000 GeV resonant HH in the hadhad channel
PNN for mX = 1000 GeV resonant HH in the lephad SLT channel
PNN for mX = 1000 GeV resonant HH in the lephad LTT channel
Event yields as a function of log10(S/B) for data, background and non-resonant HH signal. Final discriminant bins from the hadhad, lephad SLT and lephad LTT categories are combined into bins of log10(S/B). The B is the fitted background yield assuming background-only hypothesis, and the signal S is scaled to the SM expected cross-section.
Observed and expected limits at 95% CL on the cross-section of the resonant HH production as a function of the scalar resonance mass mX.
Post-fit distribution of delta-R between the taus in the hadhad channel.
Post-fit distribution of delta-R between the b-tagged jets in the hadhad channel.
Post-fit distribution of delta-R between the taus in the lephad SLT channel.
Post-fit distribution of delta-R between the b-tagged jets in the lephad SLT channel.
Post-fit distribution of delta-pT between the tau and lepton in the lephad SLT channel.
Post-fit distribution of pT of the subleading b-tagged jet in the lephad SLT channel.
Post-fit distribution of MTW in the lephad SLT channel.
Post-fit distribution of missing transverse momentum in the lephad SLT channel.
Post-fit distribution of missing transverse momentum centrality in the lephad SLT channel.
Post-fit distribution of delta-phi between the Higgs boson candidates in the lephad SLT channel.
Post-fit distribution of delta-pT between the tau and lepton in the lephad LTT channel.
Post-fit distribution of delta-R between the taus in the lephad LTT channel.
Post-fit distribution of delta-phi between the lepton and the missing transverse momentum in the lephad LTT channel.
Post-fit distribution of delta-phi between the Higgs boson candidates in the lephad LTT channel.
Post-fit distribution of the total transverse momentum s in the lephad LTT channel.
PNN for mX = 300 GeV resonant HH in the hadhad channel
PNN for mX = 300 GeV resonant HH in the lephad SLT channel
PNN for mX = 300 GeV resonant HH in the lephad LTT channel
PNN for mX = 1600 GeV resonant HH in the hadhad channel
PNN for mX = 1600 GeV resonant HH in the lephad SLT channel
PNN for mX = 1600 GeV resonant HH in the lephad LTT channel
Local p-value of the background-only hypothesis as a function of the resonance mass.
Cross-section measurements for a $Z$ boson produced in association with high-transverse-momentum jets ($p_{\mathrm{T}} \geq 100$ GeV) and decaying into a charged-lepton pair ($e^+e^-,\mu^+\mu^-$) are presented. The measurements are performed using proton-proton collisions at $\sqrt{s}=13$ TeV corresponding to an integrated luminosity of $139$ fb$^{-1}$ collected by the ATLAS experiment at the LHC. Measurements of angular correlations between the $Z$ boson and the closest jet are performed in events with at least one jet with $p_{\mathrm{T}} \geq 500$ GeV. Event topologies of particular interest are the collinear emission of a $Z$ boson in dijet events and a boosted $Z$ boson recoiling against a jet. Fiducial cross sections are compared with state-of-the-art theoretical predictions. The data are found to agree with next-to-next-to-leading-order predictions by NNLOjet and with the next-to-leading-order multi-leg generators MadGraph5_aMC@NLO and Sherpa.
Measured fiducial differential cross sections for the Z boson p$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the leading jet p$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the jet multiplicity in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the jet multiplicity in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the $\Delta R_{Z,j}^{min}$ in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the $r_{Z,j}$ in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the $r_{Z,j}$ in the collinear region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the $r_{Z,j}$ in the back-to-back region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the jet multiplicity in the collinear region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the jet multiplicity in the back-to-back region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the H$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the $\Delta R_{Z,j}^{min}$ in the high-S$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the jet multiplicity in the high-S$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The statistical, systematic, and luminosity uncertainties are given.
Systematic uncertainties for the Z boson p$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the leading jet p$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the jet multiplicity in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the jet multiplicity in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the $\Delta R_{Z,j}^{min}$ in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the $r_{Z,j}$ in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the $r_{Z,j}$ in the collinear region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the $r_{Z,j}$ in the back-to-back region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the jet multiplicity in the collinear region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the jet multiplicity in the back-to-back region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the H$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the $\Delta R_{Z,j}^{min}$ in the high-S$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the jet multiplicity in the high-S$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Correction scale factor from the cross section calculated with leptons at the Born-level to the cross section calculated with dressed leptons as a function of the Z boson p$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with leptons at the Born-level to the cross section calculated with dressed leptons as a function of the leading jet p$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with leptons at the Born-level to the cross section calculated with dressed leptons as a function of the jet multiplicity in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with leptons at the Born-level to the cross section calculated with dressed leptons as a function of the jet multiplicity in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with leptons at the Born-level to the cross section calculated with dressed leptons as a function of the $\Delta R_{Z,j}^{min}$ in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with leptons at the Born-level to the cross section calculated with dressed leptons as a function of the $r_{Z,j}$ in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with leptons at the Born-level to the cross section calculated with dressed leptons as a function of the $r_{Z,j}$ in the collinear region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with leptons at the Born-level to the cross section calculated with dressed leptons as a function of the $r_{Z,j}$ in the back-to-back region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with leptons at the Born-level to the cross section calculated with dressed leptons as a function of the jet multiplicity in the collinear region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with leptons at the Born-level to the cross section calculated with dressed leptons as a function of the jet multiplicity in the back-to-back region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with leptons at the Born-level to the cross section calculated with dressed leptons as a function of the H$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with leptons at the Born-level to the cross section calculated with dressed leptons as a function of the $\Delta R_{Z,j}^{min}$ in the high-S$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with leptons at the Born-level to the cross section calculated with dressed leptons as a function of the jet multiplicity in the high-S$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with an overlap removal with jets of pT greater than 100 GeV to the cross section calculated with an overlap removal with jets of pT greater than 30 GeV as a function of the Z boson p$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with an overlap removal with jets of pT greater than 100 GeV to the cross section calculated with an overlap removal with jets of pT greater than 30 GeV as a function of the leading jet p$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with an overlap removal with jets of pT greater than 100 GeV to the cross section calculated with an overlap removal with jets of pT greater than 30 GeV as a function of the jet multiplicity in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with an overlap removal with jets of pT greater than 100 GeV to the cross section calculated with an overlap removal with jets of pT greater than 30 GeV as a function of the jet multiplicity in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with an overlap removal with jets of pT greater than 100 GeV to the cross section calculated with an overlap removal with jets of pT greater than 30 GeV as a function of the $\Delta R_{Z,j}^{min}$ in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with an overlap removal with jets of pT greater than 100 GeV to the cross section calculated with an overlap removal with jets of pT greater than 30 GeV as a function of the $r_{Z,j}$ in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with an overlap removal with jets of pT greater than 100 GeV to the cross section calculated with an overlap removal with jets of pT greater than 30 GeV as a function of the $r_{Z,j}$ in the collinear region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with an overlap removal with jets of pT greater than 100 GeV to the cross section calculated with an overlap removal with jets of pT greater than 30 GeV as a function of the $r_{Z,j}$ in the back-to-back region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with an overlap removal with jets of pT greater than 100 GeV to the cross section calculated with an overlap removal with jets of pT greater than 30 GeV as a function of the jet multiplicity in the collinear region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with an overlap removal with jets of pT greater than 100 GeV to the cross section calculated with an overlap removal with jets of pT greater than 30 GeV as a function of the jet multiplicity in the back-to-back region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with an overlap removal with jets of pT greater than 100 GeV to the cross section calculated with an overlap removal with jets of pT greater than 30 GeV as a function of the H$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with an overlap removal with jets of pT greater than 100 GeV to the cross section calculated with an overlap removal with jets of pT greater than 30 GeV as a function of the $\Delta R_{Z,j}^{min}$ in the high-S$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with an overlap removal with jets of pT greater than 100 GeV to the cross section calculated with an overlap removal with jets of pT greater than 30 GeV as a function of the jet multiplicity in the high-S$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Measured fiducial differential cross sections for the Z boson p$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the leading jet p$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the jet multiplicity in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the jet multiplicity in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the $\Delta R_{Z,j}^{min}$ in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the $r_{Z,j}$ in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the $r_{Z,j}$ in the collinear region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the $r_{Z,j}$ in the back-to-back region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the jet multiplicity in the collinear region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the jet multiplicity in the back-to-back region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the H$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the $\Delta R_{Z,j}^{min}$ in the high-S$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the jet multiplicity in the high-S$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The statistical, systematic, and luminosity uncertainties are given.
Systematic uncertainties for the Z boson p$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the leading jet p$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the jet multiplicity in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the jet multiplicity in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the $\Delta R_{Z,j}^{min}$ in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the $r_{Z,j}$ in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the $r_{Z,j}$ in the collinear region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the $r_{Z,j}$ in the back-to-back region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the jet multiplicity in the collinear region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the jet multiplicity in the back-to-back region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the H$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the $\Delta R_{Z,j}^{min}$ in the high-S$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the jet multiplicity in the high-S$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
A measurement of single top-quark production in the s-channel is performed in proton$-$proton collisions at a centre-of-mass energy of 13 TeV with the ATLAS detector at the CERN Large Hadron Collider. The dataset corresponds to an integrated luminosity of 139 fb$^{-1}$. The analysis is performed on events with an electron or muon, missing transverse momentum and exactly two $b$-tagged jets in the final state. A discriminant based on matrix element calculations is used to separate single-top-quark s-channel events from the main background contributions, which are top-quark pair production and $W$-boson production in association with jets. The observed (expected) signal significance over the background-only hypothesis is 3.3 (3.9) standard deviations, and the measured cross-section is $\sigma=8.2^{+3.5}_{-2.9}$ pb, consistent with the Standard Model prediction of $\sigma^{\mathrm{SM}}=10.32^{+0.40}_{-0.36}$ pb.
Result of the s-channel single-top cross-section measurement, in pb. The statistical and systematic uncertainties are given, as well as the total uncertainty. The normalisation factors for the $t\bar{t}$ and $W$+jets backgrounds are also shown, with their total uncertainties.
Distribution of ${E}_{T}^{miss}$ after the fit of the multijet backgrounds, in the electron channel, in the signal region, without applying the cut on ${E}_{T}^{miss}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.
Distribution of ${E}_{T}^{miss}$ after the fit of the multijet backgrounds, in the electron channel, in the $W$+jets VR, without applying the cut on ${E}_{T}^{miss}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.
Distribution of ${E}_{T}^{miss}$ after the fit of the multijet backgrounds, in the electron channel, in the $t\bar{t}$ 3-jets VR, without applying the cut on ${E}_{T}^{miss}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.
Distribution of ${E}_{T}^{miss}$ after the fit of the multijet backgrounds, in the electron channel, in the $t\bar{t}$ 4-jets VR, without applying the cut on ${E}_{T}^{miss}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.
Distribution of $m_{T}^{W}$ after the fit of the multijet backgrounds, in the muon channel, in the signal region, without applying the cut on $m_{T}^{W}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.
Distribution of $m_{T}^{W}$ after the fit of the multijet backgrounds, in the muon channel, in the $W$+jets VR, without applying the cut on $m_{T}^{W}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.
Distribution of $m_{T}^{W}$ after the fit of the multijet backgrounds, in the muon channel, in the $t\bar{t}$ 3-jets VR, without applying the cut on $m_{T}^{W}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.
Distribution of $m_{T}^{W}$ after the fit of the multijet backgrounds, in the muon channel, in the $t\bar{t}$ 4-jets VR, without applying the cut on $m_{T}^{W}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.
Expected distributions of the MEM discriminant $P(S|X)$ in the SR, for the s-channel single-top signal, and for the $t\bar{t}$ and $W$+jets backgrounds, for MEM discriminant values larger than $2.0\times10^{-4}$. Each distribution is normalised to unity. The binning is the same as the optimised binning used in the signal extraction fit, resulting in a non-linear horizontal scale.
Distribution of the MEM discriminant $P(S|X)$ in the $W$+jets VR. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit presented in Section 5 in the paper. The uncertainty band indicates the simulation's statistical uncertainty and the normalisation uncertainties for the various processes in each bin, summed in quadrature. The ratio of the observed number to the predicted number of events in each bin is shown in the lower panel of the figure, with different vertical axis ranges. The binning is the same as the optimised binning used in the signal extraction fit described in Section 8 in the paper, resulting in a non-linear horizontal scale.
Distribution of the MEM discriminant $P(S|X)$ in the $t\bar{t}$ 3-jets VR. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit presented in Section 5 in the paper. The uncertainty band indicates the simulation's statistical uncertainty and the normalisation uncertainties for the various processes in each bin, summed in quadrature. The ratio of the observed number to the predicted number of events in each bin is shown in the lower panel of the figure, with different vertical axis ranges. The binning is the same as the optimised binning used in the signal extraction fit described in Section 8 in the paper, resulting in a non-linear horizontal scale.
Distribution of the MEM discriminant $P(S|X)$ in the $t\bar{t}$ 4-jets VR. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit presented in Section 5 in the paper. The uncertainty bands indicate the simulation's statistical uncertainty and the normalisation uncertainties for the various processes in each bin, summed in quadrature. The ratio of the observed number to the predicted number of events in each bin is shown in the lower panel of the figure, with different vertical axis ranges. The binning is the same as the optimised binning used in the signal extraction fit described in Section 8 in the paper, resulting in a non-linear horizontal scale.
Distribution of the MEM discriminant $P(S|X)$ in the SR before the fit to data, for MEM discriminant values larger than $2.0\times10^{-4}$. The lower panel of the figure shows the ratio of the data to the prediction, with different vertical axis ranges. The uncertainty band indicates the total uncertainties and their correlations in each bin. The uncertainties in the $t\bar{t}$ and $W$+jets normalisation factors, as well as in the s-channel signal cross-section, are not defined pre-fit and therefore not included. The binning is the same as the optimised binning used in the fit, resulting in a non-linear horizontal scale.
Distribution of the MEM discriminant $P(S|X)$ in the SR after the fit to data, for MEM discriminant values larger than $2.0\times10^{-4}$. The lower panel of the figure shows the ratio of the data to the prediction, with different vertical axis ranges. The uncertainty band indicates the total uncertainties and their correlations in each bin. The binning is the same as the optimised binning used in the fit, resulting in a non-linear horizontal scale.
Distribution of the MEM discriminant $P(S|X)$ in the SR after the fit to data, for MEM discriminant values larger than $2.0\times10^{-4}$, after subtraction of all backgrounds. The fitted distribution for the simulation of the signal is shown together with the post-fit uncertainty in the backgrounds. The binning is the same as the optimised binning used in the fit, resulting in a non-linear horizontal scale.
Pre-fit and post-fit event yields in the SR, for MEM discriminant values larger than $2.0\times10^{-4}$. The central value of the event yield for each process is calculated by summing the values of the discriminant bin contents, using the nominal expected yield for the pre-fit value, and the best-fit estimate for the post-fit value. The error includes statistical and systematic uncertainties summed in quadrature. All sources of systematic uncertainties are included, taking into account correlations and anti-correlations in the post-fit case. The uncertainties in the $t\bar{t}$ and $W$+jets normalisation factors, as well as in the s-channel signal cross-section, are not defined pre-fit and therefore only included in the post-fit uncertainties.
Observed impact of the different sources of uncertainty on the measured s-channel signal cross-section, grouped by categories. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root. The 'Systematic uncertainties' category combines all sources of systematic uncertainties. The statistical uncertainty is obtained by repeating the fit after having fixed all nuisance parameters, including the $t\bar{t}$ and $W$+jets normalisation factors. 'Total' gives the total uncertainty on the measurement.
Observed impact of the different sources of $t\bar{t}$ modelling uncertainty on the measured s-channel signal cross-section. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root. 'PS & had.' refers to the parton shower and hadronisation model, and 'ME/PS matching' to the matching of the ME to the parton shower.
Observed impact of the different sources of s-channel modelling uncertainty on the measured s-channel signal cross-section. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root. 'PS & had.' refers to the parton shower and hadronisation model, as described in Section 7 in the paper.
Observed impact of the different sources of t-channel modelling uncertainty on the measured s-channel signal cross-section. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root. 'PS & had.' refers to the parton shower and hadronisation model, as described in Section 7 in the paper.
Observed impact of the different sources of $tW$ modelling uncertainty on the measured s-channel signal cross-section, grouped by categories. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root. 'PS & had.' refers to the parton shower and hadronisation model, and '$t\bar{t}$ overlap' to the algorithm removing the overlap between $tW$ and $t\bar{t}$ production at NLO, as described in Section 7 in the paper.
Observed impact of the different sources of PDF uncertainties on the measured s-channel signal cross-section, grouped by categories. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root.
Comparison between data and prediction after the fit to data in the signal region for the leading-jet $p_{T}$. The last bin includes the overflow. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.
Comparison between data and prediction after the fit to data in the signal region for the leading-jet $\eta$. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.
Comparison between data and prediction after the fit to data in the signal region for the subleading-jet $p_{T}$. The last bin includes the overflow. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.
Comparison between data and prediction after the fit to data in the signal region for the subleading-jet $\eta$. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.
Comparison between data and prediction after the fit to data in the signal region for the lepton $p_{T}$. The last bin includes the overflow. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.
Comparison between data and prediction after the fit to data in the signal region for the lepton $\eta$. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.
Comparison between data and prediction after the fit to data in the signal region for the ${E}_{T}^{miss}$. The last bin includes the overflow. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.
Comparison between data and prediction after the fit to data in the signal region for the $m_{T}^{W}$. The last bin includes the overflow. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.
Nuisance parameters ranked according to their post-fit impacts on the best-fit value of the ratio $\mu$ of the measured cross-section to the predicted cross-section. In the figure, only the 20 nuisance parameters with the largest post-fit impacts are shown. The empty (solid) blue rectangles illustrate the pre-fit (post-fit) impact on $\mu$, corresponding to the upper axis. The pre-fit (post-fit) impact of each nuisance parameter, $\Delta\mu$, is calculated as the difference in the fitted value of $\mu$ between the nominal fit and the fit when fixing the corresponding nuisance parameter to $\hat{\theta}\pm\Delta\theta$ ($\hat{\theta}\pm\Delta\hat{\theta}$), where $\hat{\theta}$ is the best-fit value of the nuisance parameter and $\Delta\theta$ ($\Delta\hat{\theta}$) is its pre-fit (post-fit) uncertainty. Several systematic uncertainties are split into different nuisance parameters, which are indicated by NP. JES (JER) indicates jet energy scale (resolution), and $\gamma$ indicates a nuisance parameter associated to the MC statistics in one of the 18 bins numbered from 0 to 17. The black points show the best-fit values of the nuisance parameters, with the error bars representing the post-fit uncertainties. Each nuisance parameter is shown wrt. its nominal value, $\theta_0$, and in units of its pre-fit uncertainty, except the free-floating normalisation factors of the $t\bar{t}$ and $W$+jets backgrounds, and the parameters associated to the MC statistics in each bin, for which the post-fit values and uncertainties are shown.
Correlation matrix of the nuisance parameters and of the ratio $\mu$ of the measured cross-section to the predicted cross-section. The correlations are given after the fit to data. In the figure, only the parameters which have a correlation of at least 0.2 with any other parameter are shown.
Distribution of the MEM discriminant $P(S|X)$ in the SR for MEM discriminant values larger than $2.0\times10^{-4}$, for the collision data used for the measurement, and for 1000 pseudo-data replicas, generated using a bootstrapping technique, in order to assess the statistical correlations between this measurement and others, for the purpose of combinations. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the <a href="https://zenodo.org/record/5361038">BootstrapGenerator</a> software package , which implements a technique described in <a href="https://cds.cern.ch/record/2759945/">ATL-PHYS-PUB-2021-011</a>. The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. Each pseudo-data replica is assigned an index, ranging from 0 to 999, corresponding to the random number index used consistently for each observed data event.
Measured values of the signal cross-section and of the $t\bar{t}$ and $W$+jets normalisation factors, obtained by statistical-only fits to the collision data used for the measurement, and to 1000 pseudo-data replicas, generated using a bootstrapping technique, in order to assess the statistical correlations between this measurement and others, for the purpose of combinations. The central values and their statistical uncertainties are obtained by repeating the fit after having fixed all nuisance parameters, except the $t\bar{t}$ and $W$+jets normalisation factors, which are let free-floating (unlike for the statistical uncertainty on the cross-section quoted in the paper). The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the <a href="https://zenodo.org/record/5361038">BootstrapGenerator</a> software package , which implements a technique described in <a href="https://cds.cern.ch/record/2759945/">ATL-PHYS-PUB-2021-011</a>. The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. Each pseudo-data replica is assigned an index, ranging from 0 to 999, corresponding to the random number index used consistently for each observed data event.
A search for a $WZ$ resonance, in the fully leptonic final state (electrons and muons), is performed using 139 fb$^{-1}$ of data collected at a centre-of-mass energy of 13 TeV by the ATLAS detector at the Large Hadron Collider. The results are interpreted in terms of a singly charged Higgs boson of the Georgi$-$Machacek model, produced by $WZ$ fusion, and of a Heavy Vector Triplet, with the resonance produced by $WZ$ fusion or the Drell$-$Yan process. No significant excess over the Standard Model predictions is observed and limits are set on the production cross-section times branching ratio as a function of the resonance mass for these processes.
Comparisons of the data and the expected background distributions of the WZ invariant mass in the Drell-Yan signal region. The background predictions are obtained through a background-only simultaneous fit to the Drell-Yan signal region and the WZ-QCD Drell-Yan and ZZ Drell-Yan control regions. The yields are normalized to the bin width.
Comparisons of the data and the expected background distributions of the WZ invariant mass in the Drell-Yan signal region. The background predictions are obtained through a background-only simultaneous fit to the Drell-Yan signal region and the WZ-QCD Drell-Yan and ZZ Drell-Yan control regions. The yields are normalized to the bin width.
Comparisons of the data and the expected background distributions of the WZ invariant mass in the ANN-based VBF signal region. The background predictions are obtained through a background-only simultaneous fit to the VBF signal region and the WZ-QCD and ZZ VBF control regions. The yields are normalized to the bin width
Comparisons of the data and the expected background distributions of the WZ invariant mass in the ANN-based VBF signal region. The background predictions are obtained through a background-only simultaneous fit to the VBF signal region and the WZ-QCD and ZZ VBF control regions. The yields are normalized to the bin width
Comparisons of the observed data and the expected background distributions of the WZ invariant mass using the cut-based VBF selection. The background predictions are obtained through a background-only simultaneous fit to the VBF cut-based signal region and the WZ-QCD and ZZ VBF control regions. The yields are normalized to the bin width.
Comparisons of the observed data and the expected background distributions of the WZ invariant mass using the cut-based VBF selection. The background predictions are obtained through a background-only simultaneous fit to the VBF cut-based signal region and the WZ-QCD and ZZ VBF control regions. The yields are normalized to the bin width.
Drell-Yan signal region selection cutflow for a simulated W' in the HVT model A with m_W' = 1 TeV. The unweighted number of events is shown.
Drell-Yan signal region selection cutflow for a simulated W' in the HVT model A with m_W' = 1 TeV. The unweighted number of events is shown.
VBF signal region selection cutflow for a simulated W' in the HVT model C with m_W' = 500 GeV. The unweighted number of events is shown.
VBF signal region selection cutflow for a simulated W' in the HVT model C with m_W' = 500 GeV. The unweighted number of events is shown.
VBF signal region selection cutflow for a simulated H5+ in the GM model with m_H5+ = 450 GeV. The unweighted number of events is shown.
VBF signal region selection cutflow for a simulated H5+ in the GM model with m_H5+ = 450 GeV. The unweighted number of events is shown.
The acceptancetimes efficiencyof the HVT W' in the Drell-Yan signal region for different mass points and for the individual channels and the sum of all channels. The uncertainty includes both statistical and experimental systematic components.
The acceptancetimes efficiencyof the HVT W' in the Drell-Yan signal region for different mass points and for the individual channels and the sum of all channels. The uncertainty includes both statistical and experimental systematic components.
The acceptancetimes efficiencyof VBF H5+ selection after the ANN-based VBF selection at different mass points for the individual channels and the sum of all channels. The uncertainty includes both statistical and experimental systematic components.
The acceptancetimes efficiencyof VBF H5+ selection after the ANN-based VBF selection at different mass points for the individual channels and the sum of all channels. The uncertainty includes both statistical and experimental systematic components.
The acceptancetimes efficiencyof VBF HVT W' selection after the ANN-based VBF selection at different mass points for the individual channels and the sum of all channels. The uncertainty includes both statistical and experimental systematic components.
The acceptancetimes efficiencyof VBF HVT W' selection after the ANN-based VBF selection at different mass points for the individual channels and the sum of all channels. The uncertainty includes both statistical and experimental systematic components.
The acceptancetimes efficiencyof VBF H5+ selection after the cut-based VBF selection at different mass points for the individual channels and the sum of all channels. The uncertainty includes both statistical and experimental systematic components.
The acceptancetimes efficiencyof VBF H5+ selection after the cut-based VBF selection at different mass points for the individual channels and the sum of all channels. The uncertainty includes both statistical and experimental systematic components.
The acceptancetimes efficiencyof VBF HVT W' selection after the cut-based VBF selection at different mass points for the individual channels and the sum of all channels. The uncertainty includes both statistical and experimental systematic components.
The acceptancetimes efficiencyof VBF HVT W' selection after the cut-based VBF selection at different mass points for the individual channels and the sum of all channels. The uncertainty includes both statistical and experimental systematic components.
Observed and expected 95% CL exclusion upper limits on sigma * B(W' -> WZ) for the Drell-Yan production of a W' boson in the HVT model as a function of its mass. The LO theory predictions for HVT Model A with g_V=1 and Model B with g_V=$ are also shown.
Observed and expected 95% CL exclusion upper limits on sigma * B(W' -> WZ) for the Drell-Yan production of a W' boson in the HVT model as a function of its mass. The LO theory predictions for HVT Model A with g_V=1 and Model B with g_V=3 are also shown.
Using the ANN VBF selection, observed and expected 95% CL upper limits on sigma * B(W' -> WZ) for the VBF production of a W' boson in the HVT with parameter c_F=0, as a function of its mass. The LO theory predictions for HVT VBF model with different values of the coupling parameters g_V and c_H are also shown.
Using the ANN VBF selection, observed and expected 95% CL upper limits on sigma * B(W' -> WZ) for the VBF production of a W' boson in the HVT with parameter c_F=0, as a function of its mass. The LO theory predictions for HVT VBF model with different values of the coupling parameters g_V and c_H are also shown.
Using the ANN VBF selection, observed and expected 95% CL upper limits on sigma * B(W' -> WZ) of the GM model as a function of m_H_5.
Using the ANN VBF selection, observed and expected 95% CL upper limits on sigma * B(W' -> WZ) of the GM model as a function of m_H_5.
Using the ANN VBF selection, observed and expected 95% CL upper limits on sin(thetaH) of the GM model as a function of m_H_5.
Using the ANN VBF selection, observed and expected 95% CL upper limits on sin(thetaH) of the GM model as a function of m_H_5.
Using the cut-based VBF selection, observed and expected 95% CL upper limits on sigma * B(W' -> WZ) for the VBF production of a W' boson in the HVT with parameter c_F=0, as a function of its mass. The LO theory predictions for HVT VBF model with different values of the coupling parameters g_V and c_H are also shown.
Using the cut-based VBF selection, observed and expected 95% CL upper limits on sigma * B(W' -> WZ) for the VBF production of a W' boson in the HVT with parameter c_F=0, as a function of its mass. The LO theory predictions for HVT VBF model with different values of the coupling parameters g_V and c_H are also shown.
Using the cut-based VBF selection, observed and expected 95% CL upper limits on sigma * B(W' -> WZ) of the GM model as a function of m_H_5.
Using the cut-based VBF selection, observed and expected 95% CL upper limits on sigma * B(W' -> WZ) of the GM model as a function of m_H_5.
Using the cut-based VBF selection, observed and expected 95% CL upper limits on sin(thetaH) of the GM model as a function of m_H_5.
Using the cut-based VBF selection, observed and expected 95% CL upper limits on sin(thetaH) of the GM model as a function of m_H_5.
A search is presented for displaced production of Higgs bosons or $Z$ bosons, originating from the decay of a neutral long-lived particle (LLP) and reconstructed in the decay modes $H\rightarrow \gamma\gamma$ and $Z\rightarrow ee$. The analysis uses the full Run 2 data set of proton$-$proton collisions delivered by the LHC at an energy of $\sqrt{s}=13$ TeV between 2015 and 2018 and recorded by the ATLAS detector, corresponding to an integrated luminosity of 139 fb$^{-1}$. Exploiting the capabilities of the ATLAS liquid argon calorimeter to precisely measure the arrival times and trajectories of electromagnetic objects, the analysis searches for the signature of pairs of photons or electrons which arise from a common displaced vertex and which arrive after some delay at the calorimeter. The results are interpreted in a gauge-mediated supersymmetry breaking model with pair-produced higgsinos that decay to LLPs, and each LLP subsequently decays into either a Higgs boson or a $Z$ boson. The final state includes at least two particles that escape direct detection, giving rise to missing transverse momentum. No significant excess is observed above the background expectation. The results are used to set upper limits on the cross section for higgsino pair production, up to a $\tilde\chi^0_1$ mass of 369 (704) GeV for decays with 100% branching ratio of $\tilde\chi^0_1$ to Higgs ($Z$) bosons for a $\tilde\chi^0_1$ lifetime of 2 ns. A model-independent limit is also set on the production of pairs of photons or electrons with a significant delay in arrival at the calorimeter.
Average timing distributions for SR data and the estimated background as determined by the background-only fit, in each of the five exclusive $\rho$ categories. For comparison, the expected timing shapes for a few different signal models are superimposed, with each model labeled by the values of the $\tilde\chi^0_1$ mass and lifetime, as well as decay mode. To provide some indication of the variations in signal yield and shape, three signal models are shown for each of the $\tilde\chi^0_1$ decay modes, namely $\tilde\chi^0_1$ $\rightarrow$ $H \tilde G$ and $\tilde\chi^0_1$ $\rightarrow$ $Z \tilde G$. The models shown include a rather low $\tilde\chi^0_1$ mass value of 135 GeV for lifetimes of either 2 ns or 10 ns, and a higher $\tilde\chi^0_1$ mass value which is near the 95% CL exclusion limit for each decay mode for a lifetime of 2 ns. Each signal model is shown with the signal normalization corresponding to a BR value of unity for the decay mode in question.
Average timing distributions for SR data and the estimated background as determined by the background-only fit, in each of the five exclusive $\rho$ categories. For comparison, the expected timing shapes for a few different signal models are superimposed, with each model labeled by the values of the $\tilde\chi^0_1$ mass and lifetime, as well as decay mode. To provide some indication of the variations in signal yield and shape, three signal models are shown for each of the $\tilde\chi^0_1$ decay modes, namely $\tilde\chi^0_1$ $\rightarrow$ $H \tilde G$ and $\tilde\chi^0_1$ $\rightarrow$ $Z \tilde G$. The models shown include a rather low $\tilde\chi^0_1$ mass value of 135 GeV for lifetimes of either 2 ns or 10 ns, and a higher $\tilde\chi^0_1$ mass value which is near the 95% CL exclusion limit for each decay mode for a lifetime of 2 ns. Each signal model is shown with the signal normalization corresponding to a BR value of unity for the decay mode in question.
Average timing distributions for SR data and the estimated background as determined by the background-only fit, in each of the five exclusive $\rho$ categories. For comparison, the expected timing shapes for a few different signal models are superimposed, with each model labeled by the values of the $\tilde\chi^0_1$ mass and lifetime, as well as decay mode. To provide some indication of the variations in signal yield and shape, three signal models are shown for each of the $\tilde\chi^0_1$ decay modes, namely $\tilde\chi^0_1$ $\rightarrow$ $H \tilde G$ and $\tilde\chi^0_1$ $\rightarrow$ $Z \tilde G$. The models shown include a rather low $\tilde\chi^0_1$ mass value of 135 GeV for lifetimes of either 2 ns or 10 ns, and a higher $\tilde\chi^0_1$ mass value which is near the 95% CL exclusion limit for each decay mode for a lifetime of 2 ns. Each signal model is shown with the signal normalization corresponding to a BR value of unity for the decay mode in question.
Average timing distributions for SR data and the estimated background as determined by the background-only fit, in each of the five exclusive $\rho$ categories. For comparison, the expected timing shapes for a few different signal models are superimposed, with each model labeled by the values of the $\tilde\chi^0_1$ mass and lifetime, as well as decay mode. To provide some indication of the variations in signal yield and shape, three signal models are shown for each of the $\tilde\chi^0_1$ decay modes, namely $\tilde\chi^0_1$ $\rightarrow$ $H \tilde G$ and $\tilde\chi^0_1$ $\rightarrow$ $Z \tilde G$. The models shown include a rather low $\tilde\chi^0_1$ mass value of 135 GeV for lifetimes of either 2 ns or 10 ns, and a higher $\tilde\chi^0_1$ mass value which is near the 95% CL exclusion limit for each decay mode for a lifetime of 2 ns. Each signal model is shown with the signal normalization corresponding to a BR value of unity for the decay mode in question.
Average timing distributions for SR data and the estimated background as determined by the background-only fit, in each of the five exclusive $\rho$ categories. For comparison, the expected timing shapes for a few different signal models are superimposed, with each model labeled by the values of the $\tilde\chi^0_1$ mass and lifetime, as well as decay mode. To provide some indication of the variations in signal yield and shape, three signal models are shown for each of the $\tilde\chi^0_1$ decay modes, namely $\tilde\chi^0_1$ $\rightarrow$ $H \tilde G$ and $\tilde\chi^0_1$ $\rightarrow$ $Z \tilde G$. The models shown include a rather low $\tilde\chi^0_1$ mass value of 135 GeV for lifetimes of either 2 ns or 10 ns, and a higher $\tilde\chi^0_1$ mass value which is near the 95% CL exclusion limit for each decay mode for a lifetime of 2 ns. Each signal model is shown with the signal normalization corresponding to a BR value of unity for the decay mode in question.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ branching ratio to the SM Higgs boson, where the assumed cross-section is for higgsino production, and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 - $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$). Several signal hypotheses are overlaid that are labelled by the $\tilde\chi^0_1$ mass, all with a fixed $\tilde\chi^0_1$ lifetime of 2 ns.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ branching ratio to the SM Higgs boson, where the assumed cross-section is for higgsino production, and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 - $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$). Several signal hypotheses are overlaid that are labelled by the $\tilde\chi^0_1$ mass, all with a fixed $\tilde\chi^0_1$ lifetime of 2 ns.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ branching ratio to the SM Higgs boson, where the assumed cross-section is for higgsino production, and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 - $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$). Several signal hypotheses are overlaid that are labelled by the $\tilde\chi^0_1$ mass, all with a fixed $\tilde\chi^0_1$ lifetime of 2 ns.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ branching ratio to the SM Higgs boson, where the assumed cross-section is for higgsino production, and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 - $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$). Several signal hypotheses are overlaid that are labelled by the $\tilde\chi^0_1$ mass, all with a fixed $\tilde\chi^0_1$ lifetime of 2 ns.
The 95% CL exclusion limits on the target signal hypothesis, for $\tilde\chi^0_1$ lifetime in ns as a function of $\tilde\chi^0_1$ mass in GeV. The overlaid curves correspond to different decay hypotheses, where the assumed cross-section is for higgsino production, and the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ or $Z + \tilde{G}$ such that $\mathcal{B}(H + \tilde{G}) + \mathcal{B}(Z + \tilde{G})$ = 100%. The curve shown in red represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $Z + \tilde{G}$ with 100% branching ratio. The curve shown in blue represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ with 100% branching ratio.
The 95% CL exclusion limits on the target signal hypothesis, for $\tilde\chi^0_1$ lifetime in ns as a function of $\tilde\chi^0_1$ mass in GeV. The overlaid curves correspond to different decay hypotheses, where the assumed cross-section is for higgsino production, and the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ or $Z + \tilde{G}$ such that $\mathcal{B}(H + \tilde{G}) + \mathcal{B}(Z + \tilde{G})$ = 100%. The curve shown in red represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $Z + \tilde{G}$ with 100% branching ratio. The curve shown in blue represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ with 100% branching ratio.
The 95% CL exclusion limits on the target signal hypothesis, for $\tilde\chi^0_1$ lifetime in ns as a function of $\tilde\chi^0_1$ mass in GeV. The overlaid curves correspond to different decay hypotheses, where the assumed cross-section is for higgsino production, and the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ or $Z + \tilde{G}$ such that $\mathcal{B}(H + \tilde{G}) + \mathcal{B}(Z + \tilde{G})$ = 100%. The curve shown in red represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $Z + \tilde{G}$ with 100% branching ratio. The curve shown in blue represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ with 100% branching ratio.
The 95% CL exclusion limits on the target signal hypothesis, for $\tilde\chi^0_1$ lifetime in ns as a function of $\tilde\chi^0_1$ mass in GeV. The overlaid curves correspond to different decay hypotheses, where the assumed cross-section is for higgsino production, and the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ or $Z + \tilde{G}$ such that $\mathcal{B}(H + \tilde{G}) + \mathcal{B}(Z + \tilde{G})$ = 100%. The curve shown in red represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $Z + \tilde{G}$ with 100% branching ratio. The curve shown in blue represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ with 100% branching ratio.
The 95% CL exclusion limits on the target signal hypothesis, for $\tilde\chi^0_1$ lifetime in ns as a function of $\tilde\chi^0_1$ mass in GeV. The overlaid curves correspond to different decay hypotheses, where the assumed cross-section is for higgsino production, and the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ or $Z + \tilde{G}$ such that $\mathcal{B}(H + \tilde{G}) + \mathcal{B}(Z + \tilde{G})$ = 100%. The curve shown in red represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $Z + \tilde{G}$ with 100% branching ratio. The curve shown in blue represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ with 100% branching ratio.
The 95% CL exclusion limits on the target signal hypothesis, for $\tilde\chi^0_1$ lifetime in ns as a function of $\tilde\chi^0_1$ mass in GeV. The overlaid curves correspond to different decay hypotheses, where the assumed cross-section is for higgsino production, and the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ or $Z + \tilde{G}$ such that $\mathcal{B}(H + \tilde{G}) + \mathcal{B}(Z + \tilde{G})$ = 100%. The curve shown in red represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $Z + \tilde{G}$ with 100% branching ratio. The curve shown in blue represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ with 100% branching ratio.
The 95% CL exclusion limits on the target signal hypothesis, for $\tilde\chi^0_1$ lifetime in ns as a function of $\tilde\chi^0_1$ mass in GeV. The overlaid curves correspond to different decay hypotheses, where the assumed cross-section is for higgsino production, and the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ or $Z + \tilde{G}$ such that $\mathcal{B}(H + \tilde{G}) + \mathcal{B}(Z + \tilde{G})$ = 100%. The curve shown in red represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $Z + \tilde{G}$ with 100% branching ratio. The curve shown in blue represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ with 100% branching ratio.
The 95% CL exclusion limits on the target signal hypothesis, for $\tilde\chi^0_1$ lifetime in ns as a function of $\tilde\chi^0_1$ mass in GeV. The overlaid curves correspond to different decay hypotheses, where the assumed cross-section is for higgsino production, and the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ or $Z + \tilde{G}$ such that $\mathcal{B}(H + \tilde{G}) + \mathcal{B}(Z + \tilde{G})$ = 100%. The curve shown in red represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $Z + \tilde{G}$ with 100% branching ratio. The curve shown in blue represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ with 100% branching ratio.
The 95% CL exclusion limits on the target signal hypothesis, for $\tilde\chi^0_1$ lifetime in ns as a function of $\tilde\chi^0_1$ mass in GeV. The overlaid curves correspond to different decay hypotheses, where the assumed cross-section is for higgsino production, and the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ or $Z + \tilde{G}$ such that $\mathcal{B}(H + \tilde{G}) + \mathcal{B}(Z + \tilde{G})$ = 100%. The curve shown in red represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $Z + \tilde{G}$ with 100% branching ratio. The curve shown in blue represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ with 100% branching ratio.
The 95% CL exclusion limits on the target signal hypothesis, for $\tilde\chi^0_1$ lifetime in ns as a function of $\tilde\chi^0_1$ mass in GeV. The overlaid curves correspond to different decay hypotheses, where the assumed cross-section is for higgsino production, and the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ or $Z + \tilde{G}$ such that $\mathcal{B}(H + \tilde{G}) + \mathcal{B}(Z + \tilde{G})$ = 100%. The curve shown in red represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $Z + \tilde{G}$ with 100% branching ratio. The curve shown in blue represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ with 100% branching ratio.
The 95% CL exclusion limits on the target signal hypothesis, for $\tilde\chi^0_1$ lifetime in ns as a function of $\tilde\chi^0_1$ mass in GeV. The overlaid curves correspond to different decay hypotheses, where the assumed cross-section is for higgsino production, and the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ or $Z + \tilde{G}$ such that $\mathcal{B}(H + \tilde{G}) + \mathcal{B}(Z + \tilde{G})$ = 100%. The curve shown in red represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $Z + \tilde{G}$ with 100% branching ratio. The curve shown in blue represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ with 100% branching ratio.
The 95% CL exclusion limits on the target signal hypothesis, for $\tilde\chi^0_1$ lifetime in ns as a function of $\tilde\chi^0_1$ mass in GeV. The overlaid curves correspond to different decay hypotheses, where the assumed cross-section is for higgsino production, and the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ or $Z + \tilde{G}$ such that $\mathcal{B}(H + \tilde{G}) + \mathcal{B}(Z + \tilde{G})$ = 100%. The curve shown in red represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $Z + \tilde{G}$ with 100% branching ratio. The curve shown in blue represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ with 100% branching ratio.
Cutflow for an example higgsino signal with mass 225 GeV and lifetime 10 ns, in the H decay mode. Acceptance is defined at truth level, and efficiency compares the events passing at reconstruction level with respect to truth.
Cutflow for an example higgsino signal with mass 225 GeV and lifetime 10 ns, in the Z decay mode. Acceptance is defined at truth level, and efficiency compares the events passing at reconstruction level with respect to truth.
Cutflow for an example higgsino signal with mass 225 GeV and lifetime 2 ns, in the H decay mode. Acceptance is defined at truth level, and efficiency compares the events passing at reconstruction level with respect to truth.
Cutflow for an example higgsino signal with mass 225 GeV and lifetime 2 ns, in the Z decay mode. Acceptance is defined at truth level, and efficiency compares the events passing at reconstruction level with respect to truth.
Acceptance across the H decay mode signal grid, calculated using truth information. The selection applied corresponds to the model-independent signal region (i.e. the standard SR with $t_{\text{avg}$ > 0.9 ns).
Acceptance across the Z decay mode signal grid, calculated using truth information. The selection applied corresponds to the model-independent signal region (i.e. the standard SR with $t_{\text{avg}$ > 0.9 ns).
Efficiency across the H decay mode signal grid, calculated using reco information. The selection applied corresponds to the model-independent signal region (i.e. the standard SR with $t_{\text{avg}$ > 0.9 ns). Here, the numerator is the signal yield passing the reco selection and the denominator is the signal yield passing the truth selection.
Efficiency across the Z decay mode signal grid, calculated using reco information. The selection applied corresponds to the model-independent signal region (i.e. the standard SR with $t_{\text{avg}$ > 0.9 ns). Here, the numerator is the signal yield passing the reco selection and the denominator is the signal yield passing the truth selection.
Measurements of transverse energy$-$energy correlations and their associated azimuthal asymmetries in multijet events are presented. The analysis is performed using a data sample corresponding to 139 $\mbox{fb\(^{-1}\)}$ of proton$-$proton collisions at a centre-of-mass energy of $\sqrt{s} = 13$ TeV, collected with the ATLAS detector at the Large Hadron Collider. The measurements are presented in bins of the scalar sum of the transverse momenta of the two leading jets and unfolded to particle level. They are then compared to next-to-next-to-leading-order perturbative QCD calculations for the first time, which feature a significant reduction in the theoretical uncertainties estimated using variations of the renormalisation and factorisation scales. The agreement between data and theory is good, thus providing a precision test of QCD at large momentum transfers $Q$. The strong coupling constant $\alpha_s$ is extracted differentially as a function of $Q$, showing a good agreement with the renormalisation group equation and with previous analyses. A simultaneous fit to all transverse energy$-$energy correlation distributions across different kinematic regions yields a value of $\alpha_\mathrm{s}(m_Z) = 0.1175 \pm 0.0006 \mbox{ (exp.)} ^{+0.0034}_{-0.0017} \mbox{ (theo.)}$, while the global fit to the asymmetry distributions yields $\alpha_{\mathrm{s}}(m_Z) = 0.1185 \pm 0.0009 \mbox{ (exp.)} ^{+0.0025}_{-0.0012} \mbox{ (theo.)}$.
Particle-level TEEC results
Particle-level TEEC results for the first HT2 bin
Particle-level TEEC results for the second HT2 bin
Particle-level TEEC results for the third HT2 bin
Particle-level TEEC results for the fourth HT2 bin
Particle-level TEEC results for the fifth HT2 bin
Particle-level TEEC results for the sixth HT2 bin
Particle-level TEEC results for the seventh HT2 bin
Particle-level TEEC results for the eighth HT2 bin
Particle-level TEEC results for the ninth HT2 bin
Particle-level TEEC results for the tenth HT2 bin
Particle-level ATEEC results
Particle-level ATEEC results for the first HT2 bin
Particle-level ATEEC results for the second HT2 bin
Particle-level ATEEC results for the third HT2 bin
Particle-level ATEEC results for the fourth HT2 bin
Particle-level ATEEC results for the fifth HT2 bin
Particle-level ATEEC results for the sixth HT2 bin
Particle-level ATEEC results for the seventh HT2 bin
Particle-level ATEEC results for the eighth HT2 bin
Particle-level ATEEC results for the ninth HT2 bin
Particle-level ATEEC results for the tenth HT2 bin
Particle-level TEEC predictions
Particle-level TEEC predictions for the first HT2 bin
Particle-level TEEC predictions for the second HT2 bin
Particle-level TEEC predictions for the third HT2 bin
Particle-level TEEC predictions for the fourth HT2 bin
Particle-level TEEC predictions for the fifth HT2 bin
Particle-level TEEC predictions for the sixth HT2 bin
Particle-level TEEC predictions for the seventh HT2 bin
Particle-level TEEC predictions for the eighth HT2 bin
Particle-level TEEC predictions for the ninth HT2 bin
Particle-level TEEC predictions for the tenth HT2 bin
Particle-level ATEEC predictions
Particle-level ATEEC predictions for the first HT2 bin
Particle-level ATEEC predictions for the second HT2 bin
Particle-level ATEEC predictions for the third HT2 bin
Particle-level ATEEC predictions for the fourth HT2 bin
Particle-level ATEEC predictions for the fifth HT2 bin
Particle-level ATEEC predictions for the sixth HT2 bin
Particle-level ATEEC predictions for the seventh HT2 bin
Particle-level ATEEC predictions for the eighth HT2 bin
Particle-level ATEEC predictions for the ninth HT2 bin
Particle-level ATEEC predictions for the tenth HT2 bin
Fitted values for the strong coupling constant extracted from TEEC with MMHT 2014 PDF
Fitted values for the strong coupling constant extracted from TEEC with NNPDF 3.0
Fitted values for the strong coupling constant extracted from TEEC with CT14 PDF
Fitted values for the strong coupling constant extracted from ATEEC with MMHT 2014 PDF
Fitted values for the strong coupling constant extracted from ATEEC with NNPDF 3.0
Fitted values for the strong coupling constant extracted from ATEEC with CT14 PDF
Measurements of differential cross sections are presented for inclusive isolated-photon production in $pp$ collisions at a centre-of-mass energy of 13 TeV provided by the LHC and using 139 fb$^{-1}$ of data recorded by the ATLAS experiment. The cross sections are measured as functions of the photon transverse energy in different regions of photon pseudorapidity. The photons are required to be isolated by means of a fixed-cone method with two different cone radii. The dependence of the inclusive-photon production on the photon isolation is investigated by measuring the fiducial cross sections as functions of the isolation-cone radius and the ratios of the differential cross sections with different radii in different regions of photon pseudorapidity. The results presented in this paper constitute an improvement with respect to those published by ATLAS earlier: the measurements are provided for different isolation radii and with a more granular segmentation in photon pseudorapidity that can be exploited in improving the determination of the proton parton distribution functions. These improvements provide a more in-depth test of the theoretical predictions. Next-to-leading-order QCD predictions from JETPHOX and SHERPA and next-to-next-to-leading-order QCD predictions from NNLOJET are compared to the measurements, using several parameterisations of the proton parton distribution functions. The measured cross sections are well described by the fixed-order QCD predictions within the experimental and theoretical uncertainties in most of the investigated phase-space region.
Measured cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $|\eta^{\gamma}|<0.6$ and photon isolation cone radius $R=0.4$.
Measured cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $0.6<|\eta^{\gamma}|<0.8$ and photon isolation cone radius $R=0.4$.
Measured cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $0.8<|\eta^{\gamma}|<1.37$ and photon isolation cone radius $R=0.4$.
Measured cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $1.56<|\eta^{\gamma}|<1.81$ and photon isolation cone radius $R=0.4$.
Measured cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $1.81<|\eta^{\gamma}|<2.01$ and photon isolation cone radius $R=0.4$.
Measured cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $2.01<|\eta^{\gamma}|<2.37$ and photon isolation cone radius $R=0.4$.
Measured cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $|\eta^{\gamma}|<0.6$ and photon isolation cone radius $R=0.2$.
Measured cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $0.6<|\eta^{\gamma}|<0.8$ and photon isolation cone radius $R=0.2$.
Measured cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $0.8<|\eta^{\gamma}|<1.37$ and photon isolation cone radius $R=0.2$.
Measured cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $1.56<|\eta^{\gamma}|<1.81$ and photon isolation cone radius $R=0.2$.
Measured cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $1.81<|\eta^{\gamma}|<2.01$ and photon isolation cone radius $R=0.2$.
Measured cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $2.01<|\eta^{\gamma}|<2.37$ and photon isolation cone radius $R=0.2$.
Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $|\eta^{\gamma}|<0.6$ and isolation cone radius $0.4$ at NNLO QCD.
Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $0.6<|\eta^{\gamma}|<0.8$ and isolation cone radius $0.4$ at NNLO QCD.
Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $0.8<|\eta^{\gamma}|<1.37$ and isolation cone radius $0.4$ at NNLO QCD.
Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $1.56<|\eta^{\gamma}|<1.81$ and isolation cone radius $0.4$ at NNLO QCD.
Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $1.81<|\eta^{\gamma}|<2.01$ and isolation cone radius $0.4$ at NNLO QCD.
Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $2.01<|\eta^{\gamma}|<2.37$ and isolation cone radius $0.4$ at NNLO QCD.
Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $|\eta^{\gamma}|<0.6$ and isolation cone radius $0.2$ at NNLO QCD.
Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $0.6<|\eta^{\gamma}|<0.8$ and isolation cone radius $0.2$ at NNLO QCD.
Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $0.8<|\eta^{\gamma}|<1.37$ and isolation cone radius $0.2$ at NNLO QCD.
Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $1.56<|\eta^{\gamma}|<1.81$ and isolation cone radius $0.2$ at NNLO QCD.
Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $1.81<|\eta^{\gamma}|<2.01$ and isolation cone radius $0.2$ at NNLO QCD.
Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $2.01<|\eta^{\gamma}|<2.37$ and isolation cone radius $0.2$ at NNLO QCD.
Measured ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $|\eta^{\gamma}|<0.6$.
Measured ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $0.6<|\eta^{\gamma}|<0.8$.
Measured ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $0.8<|\eta^{\gamma}|<1.37$.
Measured ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $1.56<|\eta^{\gamma}|<1.81$.
Measured ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $1.81<|\eta^{\gamma}|<2.01$.
Measured ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $2.01<|\eta^{\gamma}|<2.37$.
Predicted ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $|\eta^{\gamma}|<0.6$ at NNLO QCD.
Predicted ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $0.6<|\eta^{\gamma}|<0.8$ at NNLO QCD.
Predicted ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $0.8<|\eta^{\gamma}|<1.37$ at NNLO QCD.
Predicted ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $1.56<|\eta^{\gamma}|<1.81$ at NNLO QCD.
Predicted ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $1.81<|\eta^{\gamma}|<2.01$ at NNLO QCD.
Predicted ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $2.01<|\eta^{\gamma}|<2.37$ at NNLO QCD.
Measured fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $|\eta^{\gamma}|<0.6$.
Measured fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $0.6<|\eta^{\gamma}|<0.8$.
Measured fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $0.8<|\eta^{\gamma}|<1.37$.
Measured fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $1.56<|\eta^{\gamma}|<1.81$.
Measured fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $1.81<|\eta^{\gamma}|<2.01$.
Measured fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $2.01<|\eta^{\gamma}|<2.37$.
Predicted fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $|\eta^{\gamma}|<0.6$ at NNLO QCD.
Predicted fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $0.6<|\eta^{\gamma}|<0.8$ at NNLO QCD.
Predicted fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $0.8<|\eta^{\gamma}|<1.37$ at NNLO QCD.
Predicted fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $1.56<|\eta^{\gamma}|<1.81$ at NNLO QCD.
Predicted fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $1.81<|\eta^{\gamma}|<2.01$ at NNLO QCD.
Predicted fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $2.01<|\eta^{\gamma}|<2.37$ at NNLO QCD.
A search for a new heavy scalar particle $X$ decaying into a Standard Model (SM) Higgs boson and a new singlet scalar particle $S$ is presented. The search uses a proton-proton ($pp$) collision data sample with an integrated luminosity of 140 fb$^{-1}$ recorded at a centre-of-mass energy of $\sqrt{s} = 13$ TeV with the ATLAS detector at the Large Hadron Collider. The most sensitive mass parameter space is explored in $X$ mass ranging from 500 to 1500 GeV, with the corresponding $S$ mass in the range 200-500 GeV. The search selects events with two hadronically decaying $\tau$-lepton candidates from $H\to \tau^+\tau^-$ decays and one or two light leptons ($\ell=e,\,\mu$) from $S\to VV$ ($V = W,\,Z$) decays while the remaining $V$ boson decays hadronically or to neutrinos. A multivariate discriminant based on event kinematics is used to separate the signal from the background. No excess is observed beyond the expected SM background and 95% confidence level upper limits between 72 fb and 542 fb are derived on the cross-section $\sigma(pp\to X\to SH)$ assuming the same SM-Higgs boson-like decay branching ratios for the $S\to VV$ decay. Upper limits on the visible cross-sections $\sigma(pp\to X\to SH \to WW\tau\tau)$ and $\sigma(pp\to X\to SH \to ZZ\tau\tau)$ are also set in the ranges 3-26 fb and 6-33 fb, respectively.
Observed and expected 95% CL upper limits are shown for $\sigma(pp\to X\to SH)$ obtained from $WW1\ell2\tau_{\mathrm{had}}$, $WW2\ell2\tau_{\mathrm{had}}$, $ZZ2\ell2\tau_{\mathrm{had}}$, and their combination, as a function of combined $m_{S}$ and $m_{X}$ masses ($m_{S}$+$m_{X}/25$) in GeV.
Observed and expected 95% CL upper limits are shown for $\sigma(pp\to X\to SH\to WW\tau\tau)$ obtained from the combination of $WW1\ell2\tau_{\mathrm{had}}$ and $WW2\ell2\tau_{\mathrm{had}}$ channels, as a function of combined $m_{S}$ and $m_{X}$ masses ($m_{S}$+$m_{X}/25$) in GeV. The NMSSM scans of the allowed cross-sections for $\sigma(pp\to X\to SH\to WW\tau\tau)$ are also compared.
Observed and expected 95% CL upper limits are shown for $\sigma(pp\to X\to SH\to ZZ\tau\tau)$ obtained from $ZZ2\ell2\tau_{\mathrm{had}}$ channel, as a function of combined $m_{S}$ and $m_{X}$ masses ($m_{S}$+$m_{X}/25$) in GeV. The NMSSM scans of the allowed cross-sections for $\sigma(pp\to X\to SH\to ZZ\tau\tau)$ are also compared.
Event yields after a background-only fit and data in the three signal regions. All the backgrounds except the fake $\tau_{\mathrm{had}}$ are estimated using the real $\tau_{\mathrm{had}}$ contributions from MC. The fake $\tau_{\mathrm{had}}$ background contribution is data-driven. The top-quark, $V$+jets, and small backgrounds are included in "Others". The total uncertainties include both systematic and statistical. In the $WW1\ell2\tau_{\mathrm{had}}$ channel, the smaller uncertainty in the total background than the fake $\tau_{\mathrm{had}}$ is due to the anticorrelations between the nuisance parameters of the fake $\tau_{\mathrm{had}}$ and diboson backgrounds obtained in the fit.
Uncertainties on $\sigma(pp\to X\to SH)$ obtained from the combined fit to the data for the least and most sensitive mass points. The uncertainties are symmetrised and grouped into the categories described in the systematic section.
Summary of observed and expected 95\% CL upper limits on the production cross-section of $\sigma(pp\to X\to SH)$ in fb in the combination of $WW$+$ZZ$, and in the $WW$ and $ZZ$ individual channels. The best expected limit is set to 85 fb for $m_{X}$ = 1250 GeV and $_{S}$ = 300 GeV. The combination limits gain about 26--53% over the best individual limit from the $WW1\ell2\tau_{\mathrm{had}}$ channel.
A search for leptoquarks decaying into the $b\tau$ final state is performed using Run 2 proton-proton collision data from the Large Hadron Collider, corresponding to an integrated luminosity of 139 fb$^{-1}$ at $\sqrt{s} = 13$ TeV recorded by the ATLAS detector. The benchmark models considered in this search are vector leptoquarks with electric charge of 2/3e and scalar leptoquarks with an electric charge of 4/3e. No significant excess above the Standard Model prediction is observed, and 95% confidence level upper limits are set on the cross-section times branching fraction of leptoquarks decaying into $b\tau$. For the vector leptoquark production two models are considered: the Yang-Mills and Minimal coupling models. In the Yang-Mills (Minimal coupling) scenario, vector leptoquarks with a mass below 1.58 (1.35) TeV are excluded for a gauge coupling of 1.0 and below 2.05 (1.99) TeV for a gauge coupling of 2.5. In the case of scalar leptoquarks, masses below 1.28 TeV (1.53 TeV) are excluded for a Yukawa coupling of 1.0 (2.5). Finally, an interpretation of the results with minimal model dependence is performed for each of the signal region categories, and limits on the visible cross-section for beyond the Standard Model processes are provided.
Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of single plus non-resonant plus pair vector LQ production from the combination of the high b-jet $p_{T}$ signal region for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$U_1^{YM}$ model ($\kappa$ = 0) with $\lambda$ = 1.0]
Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of single plus non-resonant plus pair vector LQ production from the combination of the high b-jet $p_{T}$ signal region for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$U_1^{YM}$ model ($\kappa$ = 0) with $\lambda$ = 1.7]
Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of single plus non-resonant plus pair vector LQ production from the combination of the high b-jet $p_{T}$ signal region for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$U_1^{YM}$ model ($\kappa$ = 0) with $\lambda$ = 2.5]
Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of single plus non-resonant plus pair vector LQ production from the combination of the high b-jet $p_{T}$ signal region for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$U_1^{MIN}$ model ($\kappa$ = 1) with $\lambda$ = 1.0]
Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of single plus non-resonant plus pair vector LQ production from the combination of the high b-jet $p_{T}$ signal region for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$U_1^{MIN}$ model ($\kappa$ = 1) with $\lambda$ = 1.7]
Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of single plus non-resonant plus pair vector LQ production from the combination of the high b-jet $p_{T}$ signal region for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$U_1^{MIN}$ model ($\kappa$ = 1) with $\lambda$ = 2.5]
The two-dimensional 95% CL exclusion limits in the $\lambda$-$m_{LQ}$ plane for singly plus non-resonant produced vector LQ (green lines) and for the sum, referred as Total, of single plus non-resonant plus pair vector LQ production (blue lines). Regions to the left of the lines are excluded. The dotted area shows the preferred region where the chosen LQ model can explain observed B anomalies. [$\kappa$ = 0]
The two-dimensional 95% CL exclusion limits in the $\lambda$-$m_{LQ}$ plane for singly plus non-resonant produced vector LQ (green lines) and for the sum, referred as Total, of single plus non-resonant plus pair vector LQ production (blue lines). Regions to the left of the lines are excluded. The dotted area shows the preferred region where the chosen LQ model can explain observed B anomalies. [$\kappa$ = 1]
Observed (solid line) and expected (dashed line) 95% CL upper limits for $\lambda$ = 1.0 on the cross-section of single plus non-resonant plus pair $\widetilde{S_{1}}$ production hypotheses from the combination of the high b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels.
Observed (solid line) and expected (dashed line) 95% CL upper limits for $\lambda$ = 1.7 on the cross-section of single plus non-resonant plus pair $\widetilde{S_{1}}$ production hypotheses from the combination of the high b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels.
Observed (solid line) and expected (dashed line) 95% CL upper limits for $\lambda$ = 2.5 on the cross-section of single plus non-resonant plus pair $\widetilde{S_{1}}$ production hypotheses from the combination of the high b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels.
The two-dimensional 95% CL exclusion limits in the $\lambda$-$m_{LQ}$ plane for singly plus non-resonant produced $\widetilde{S_{1}}$ (green lines) and for the sum, referred as Total, of single plus non-resonant plus pair vector LQ production (blue lines). Regions to the left of the lines are excluded.
Observed (solid line) and expected (dashed line) 95% upper limits on the visible cross-section, $\sigma_{\mathrm{vis}}$, obtained from model-independent search by a signal-plus-background fit in the high and low b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels.
Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of singly plus non-resonant produced vector LQ signals from the combination of the high b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$U_1^{YM}$ model ($\kappa$ = 0) with $\lambda$ = 1.0]
Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of singly plus non-resonant produced vector LQ signals from the combination of the high b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$U_1^{YM}$ model ($\kappa$ = 0) with $\lambda$ = 1.7]
Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of singly plus non-resonant produced vector LQ signals from the combination of the high b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$U_1^{YM}$ model ($\kappa$ = 0) with $\lambda$ = 2.5]
Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of singly plus non-resonant produced vector LQ signals from the combination of the high b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$U_1^{MIN}$ model ($\kappa$ = 1) with $\lambda$ = 1.0]
Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of singly plus non-resonant produced vector LQ signals from the combination of the high b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$U_1^{MIN}$ model ($\kappa$ = 1) with $\lambda$ = 1.7]
Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of singly plus non-resonant produced vector LQ signals from the combination of the high b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$U_1^{MIN}$ model ($\kappa$ = 1) with $\lambda$ = 2.5]
Observed (solid line) and expected (dashed line) 95% CL upper limits for $\lambda$ = 1.0 on the cross-section of singly produced $\widetilde{S_{1}}$ signal hypotheses from the combination of the high b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels.
Observed (solid line) and expected (dashed line) 95% CL upper limits for $\lambda$ = 1.7 on the cross-section of singly produced $\widetilde{S_{1}}$ signal hypotheses from the combination of the high b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels.
Observed (solid line) and expected (dashed line) 95% CL upper limits for $\lambda$ = 2.5 on the cross-section of singly produced $\widetilde{S_{1}}$ signal hypotheses from the combination of the high b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels.
The signal acceptance times efficiency for single plus non-resonant produced LQ in the $\widetilde{S_{1}}$ model from the combination of the high and low b-jet $p_{T}$ signal regions for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$\lambda$ = 1.0]
The signal acceptance times efficiency for single plus non-resonant produced LQ in the $\widetilde{S_{1}}$ model from the combination of the high and low b-jet $p_{T}$ signal regions for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$\lambda$ = 1.7]
The signal acceptance times efficiency for single plus non-resonant produced LQ in the $\widetilde{S_{1}}$ model from the combination of the high and low b-jet $p_{T}$ signal regions for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$\lambda$ = 2.5]
The signal acceptance times efficiency for single plus non-resonant produced LQ in the $U_1^{MIN}$ model from the combination of the high and low b-jet $p_{T}$ signal regions for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$\lambda$ = 1.0]
The signal acceptance times efficiency for single plus non-resonant produced LQ in the $U_1^{MIN}$ model from the combination of the high and low b-jet $p_{T}$ signal regions for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$\lambda$ = 1.7]
The signal acceptance times efficiency for single plus non-resonant produced LQ in the $U_1^{MIN}$ model from the combination of the high and low b-jet $p_{T}$ signal regions for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$\lambda$ = 2.5]
The signal acceptance times efficiency for single plus non-resonant produced LQ in the $U_1^{YM}$ model from the combination of the high and low b-jet $p_{T}$ signal regions for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$\lambda$ = 1.0]
The signal acceptance times efficiency for single plus non-resonant produced LQ in the $U_1^{YM}$ model from the combination of the high and low b-jet $p_{T}$ signal regions for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$\lambda$ = 1.7]
The signal acceptance times efficiency for single plus non-resonant produced LQ in the $U_1^{YM}$ model from the combination of the high and low b-jet $p_{T}$ signal regions for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$\lambda$ = 2.5]
Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of singly produced vector LQ signals from the combination of the high and low b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region. [$U_1^{YM}$ model ($\kappa$ = 0) with $\lambda$ = 1.0]
Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of singly produced vector LQ signals from the combination of the high and low b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region. [$U_1^{YM}$ model ($\kappa$ = 0) with $\lambda$ = 1.7]
Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of singly produced vector LQ signals from the combination of the high and low b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region. [$U_1^{YM}$ model ($\kappa$ = 0) with $\lambda$ = 2.5]
Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of singly produced vector LQ signals from the combination of the high and low b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region. [$U_1^{MIN}$ model ($\kappa$ = 1) with $\lambda$ = 1.0]
Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of singly produced vector LQ signals from the combination of the high and low b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region. [$U_1^{MIN}$ model ($\kappa$ = 1) with $\lambda$ = 1.7]
Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of singly produced vector LQ signals from the combination of the high and low b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region. [$U_1^{MIN}$ model ($\kappa$ = 1) with $\lambda$ = 2.5]
Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of the single plus non-resonant plus pair production of vector LQ from the combination of the high and low b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region. [$U_1^{YM}$ model ($\kappa$ = 0) with $\lambda$ = 1.0]
Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of the single plus non-resonant plus pair production of vector LQ from the combination of the high and low b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region. [$U_1^{YM}$ model ($\kappa$ = 0) with $\lambda$ = 1.7]
Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of the single plus non-resonant plus pair production of vector LQ from the combination of the high and low b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region. [$U_1^{YM}$ model ($\kappa$ = 0) with $\lambda$ = 2.5]
Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of the single plus non-resonant plus pair production of vector LQ from the combination of the high and low b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region. [$U_1^{MIN}$ model ($\kappa$ = 1) with $\lambda$ = 1.0]
Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of the single plus non-resonant plus pair production of vector LQ from the combination of the high and low b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region. [$U_1^{MIN}$ model ($\kappa$ = 1) with $\lambda$ = 1.7]
Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of the single plus non-resonant plus pair production of vector LQ from the combination of the high and low b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region. [$U_1^{MIN}$ model ($\kappa$ = 1) with $\lambda$ = 2.5]
The two-dimensional 95% CL exclusion limits in the $\lambda$-$m_{LQ}$ plane for singly plus non-resonant produced vector LQ (green lines) and for the sum, referred as Total, of single plus non-resonant plus pair vector LQ production (blue lines).Regions to the left of the lines are excluded. The dotted area shows the preferred region where the chosen LQ model can explain observed B anomalies. Results are extracted from the combination of the high and low b-jet $p_{T}$ signal region for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region. [$\kappa$ = 0]
The two-dimensional 95% CL exclusion limits in the $\lambda$-$m_{LQ}$ plane for singly plus non-resonant produced vector LQ (green lines) and for the sum, referred as Total, of single plus non-resonant plus pair vector LQ production (blue lines).Regions to the left of the lines are excluded. The dotted area shows the preferred region where the chosen LQ model can explain observed B anomalies. Results are extracted from the combination of the high and low b-jet $p_{T}$ signal region for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region. [$\kappa$ = 1]
Observed (solid line) and expected (dashed line) 95% CL upper limits for $\lambda$ = 1.0 on the cross-section of singly-produced $\widetilde{S_{1}}$ signals from the combination of the high and low b-jet $p_{T}$ categories for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region.
Observed (solid line) and expected (dashed line) 95% CL upper limits for $\lambda$ = 1.7 on the cross-section of singly-produced $\widetilde{S_{1}}$ signals from the combination of the high and low b-jet $p_{T}$ categories for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region.
Observed (solid line) and expected (dashed line) 95% CL upper limits for $\lambda$ = 2.5 on the cross-section of singly-produced $\widetilde{S_{1}}$ signals from the combination of the high and low b-jet $p_{T}$ categories for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region.
Observed (solid line) and expected (dashed line) 95% CL upper limits for $\lambda$ = 1.0 on the cross-section of single plus non-resonant plus pair $\widetilde{S_{1}}$ production signal from the combination of the high and low b-jet $p_{T}$ categories for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region.
Observed (solid line) and expected (dashed line) 95% CL upper limits for $\lambda$ = 1.7 on the cross-section of single plus non-resonant plus pair $\widetilde{S_{1}}$ production signal from the combination of the high and low b-jet $p_{T}$ categories for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region.
Observed (solid line) and expected (dashed line) 95% CL upper limits for $\lambda$ = 2.5 on the cross-section of single plus non-resonant plus pair $\widetilde{S_{1}}$ production signal from the combination of the high and low b-jet $p_{T}$ categories for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region.
The two-dimensional 95% CL exclusion limits in the $\lambda$-$m_{LQ}$ plane for singly plus non-resonant produced $\widetilde{S_{1}}$ (green lines) and for the sum, referred as Total, of single plus non-resonant plus pair $\widetilde{S_{1}}$ production (blue lines). Regions to the left of the lines are excluded. Results are extracted from the combination of the high and low b-jet $p_{T}$ signal region for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region.
A search for supersymmetry involving the pair production of gluinos decaying via off-shell third-generation squarks into the lightest neutralino ($\tilde\chi^0_1$) is reported. It exploits LHC proton$-$proton collision data at a centre-of-mass energy $\sqrt{s} = 13$ TeV with an integrated luminosity of 139 fb$^{-1}$ collected with the ATLAS detector from 2015 to 2018. The search uses events containing large missing transverse momentum, up to one electron or muon, and several energetic jets, at least three of which must be identified as containing $b$-hadrons. Both a simple kinematic event selection and an event selection based upon a deep neural-network are used. No significant excess above the predicted background is found. In simplified models involving the pair production of gluinos that decay via off-shell top (bottom) squarks, gluino masses less than 2.44 TeV (2.35 TeV) are excluded at 95% CL for a massless $\tilde\chi^0_1$. Limits are also set on the gluino mass in models with variable branching ratios for gluino decays to $b\bar{b}\tilde\chi^0_1$, $t\bar{t}\tilde\chi^0_1$ and $t\bar{b}\tilde\chi^-_1$ / $\bar{t}b\tilde\chi^+_1$.
A summary of the uncertainties in the background estimates for SR-Gtt-0L-B. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gtt-0L-B. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gtt-0L-M1. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gtt-0L-M1. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gtt-0L-M2. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gtt-0L-M2. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gtt-0L-C. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gtt-0L-C. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gtt-1L-B. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gtt-1L-B. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gtt-1L-M1. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gtt-1L-M1. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gtt-1L-M2. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gtt-1L-M2. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gtt-1L-C. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gtt-1L-C. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gbb-B. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gbb-B. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gbb-M. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gbb-M. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gbb-C. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gbb-C. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gtb-B. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gtb-B. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gtb-M. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gtb-M. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gtb-C. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gtb-C. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gtt-2100-1. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gtt-2100-1. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gtt-1800-1. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gtt-1800-1. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gtt-2300-1200. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gtt-2300-1200. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gtt-1900-1400. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gtt-1900-1400. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gbb-2800-1400. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gbb-2800-1400. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gbb-2300-1000. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gbb-2300-1000. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gbb-2100-1600. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gbb-2100-1600. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gbb-2000-1800. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
A summary of the uncertainties in the background estimates for SR-Gbb-2000-1800. The individual experimental and theoretical uncertainties are assumed to be uncorrelated and are combined by adding in quadrature.
Results of the background-only fit extrapolated to SR_Gtt_0L_B in the CC analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gtt_0L_B in the CC analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gtt_0L_M1 in the CC analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gtt_0L_M1 in the CC analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gtt_0L_M2 in the CC analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gtt_0L_M2 in the CC analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gtt_0L_C in the CC analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gtt_0L_C in the CC analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gtt_1L_B in the CC analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gtt_1L_B in the CC analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gtt_1L_M1 in the CC analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gtt_1L_M1 in the CC analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gtt_1L_M2 in the CC analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gtt_1L_M2 in the CC analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gtt_1L_C in the CC analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gtt_1L_C in the CC analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gbb_B in the CC analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gbb_B in the CC analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gbb_M in the CC analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gbb_M in the CC analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gbb_C in the CC analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gbb_C in the CC analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gtb_B in the CC analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gtb_B in the CC analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gtb_M in the CC analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gtb_M in the CC analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gtb_C in the CC analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gtb_C in the CC analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gtt_2100_1 in the NN analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gtt_2100_1 in the NN analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gtt_1800_1 in the NN analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gtt_1800_1 in the NN analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gtt_2300_1200 in the NN analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gtt_2300_1200 in the NN analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gtt_1900_1400 in the NN analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gtt_1900_1400 in the NN analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gbb_2800_1400 in the NN analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gbb_2800_1400 in the NN analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gbb_2300_1000 in the NN analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gbb_2300_1000 in the NN analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gbb_2100_1600 in the NN analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gbb_2100_1600 in the NN analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gbb_2000_1800 in the NN analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Results of the background-only fit extrapolated to SR_Gbb_2000_1800 in the NN analysis, for both the total expected background yields and the main contributing background processes. The quoted uncertainties include both experimental and theoretical systematics. The data in the SRs are not included in the fit. The background category $t\bar{t}+X$ includes $t\bar{t} W/Z$, $t\bar{t} H$ and $t\bar{t} t\bar{t}$ events. The row ``Pre-fit background'' provides the total background prediction when the $t\bar{t}$ and $Z+$jets normalisations are obtained from theoretical calculation, taking into account the kinematic weights described in Section 5.
Observed exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gtt models obtained from the NN analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Observed exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gtt models obtained from the NN analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Observed exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gtt models obtained from the NN analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Observed exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gtt models obtained from the NN analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Observed exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gtt models obtained from the NN analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Observed exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gtt models obtained from the NN analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Expected exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gtt models obtained from the NN analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Expected exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gtt models obtained from the NN analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Expected exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gtt models obtained from the NN analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Expected exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gtt models obtained from the NN analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Expected exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gtt models obtained from the NN analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Expected exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gtt models obtained from the NN analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Observed exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gbb models obtained from the NN analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Observed exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gbb models obtained from the NN analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Observed exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gbb models obtained from the NN analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Observed exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gbb models obtained from the NN analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Observed exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gbb models obtained from the NN analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Observed exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gbb models obtained from the NN analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Expected exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gbb models obtained from the NN analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Expected exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gbb models obtained from the NN analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Expected exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gbb models obtained from the NN analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Expected exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gbb models obtained from the NN analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Expected exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gbb models obtained from the NN analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Expected exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gbb models obtained from the NN analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Observed (left) 95\%~CL exclusion limits on the gluino mass as a function of BR$(\tilde{g} \to b\bar{b}\tilde\chi^{0}_{1}$) (vertical) and BR$(\tilde{g} \to t\bar{t}\tilde\chi^{0}_{1}$) (horizontal) for Gtb models with $m(\tilde\chi^{0}_{1}) = 1$~GeV, obtained from the CC analysis.
Observed (left) 95\%~CL exclusion limits on the gluino mass as a function of BR$(\tilde{g} \to b\bar{b}\tilde\chi^{0}_{1}$) (vertical) and BR$(\tilde{g} \to t\bar{t}\tilde\chi^{0}_{1}$) (horizontal) for Gtb models with $m(\tilde\chi^{0}_{1}) = 1$~GeV, obtained from the CC analysis.
Expected (right) 95\%~CL exclusion limits on the gluino mass as a function of BR$(\tilde{g} \to b\bar{b}\tilde\chi^{0}_{1}$) (vertical) and BR$(\tilde{g} \to t\bar{t}\tilde\chi^{0}_{1}$) (horizontal) for Gtb models with $m(\tilde\chi^{0}_{1}) = 1$~GeV, obtained from the CC analysis.
Expected (right) 95\%~CL exclusion limits on the gluino mass as a function of BR$(\tilde{g} \to b\bar{b}\tilde\chi^{0}_{1}$) (vertical) and BR$(\tilde{g} \to t\bar{t}\tilde\chi^{0}_{1}$) (horizontal) for Gtb models with $m(\tilde\chi^{0}_{1}) = 1$~GeV, obtained from the CC analysis.
Observed (left) 95\%~CL exclusion limits on the gluino mass as a function of BR$(\tilde{g} \to b\bar{b}\tilde\chi^{0}_{1}$) (vertical) and BR$(\tilde{g} \to t\bar{t}\tilde\chi^{0}_{1}$) (horizontal) for Gtb models with $m(\tilde\chi^{0}_{1}) = 600$~GeV, obtained from the CC analysis.
Observed (left) 95\%~CL exclusion limits on the gluino mass as a function of BR$(\tilde{g} \to b\bar{b}\tilde\chi^{0}_{1}$) (vertical) and BR$(\tilde{g} \to t\bar{t}\tilde\chi^{0}_{1}$) (horizontal) for Gtb models with $m(\tilde\chi^{0}_{1}) = 600$~GeV, obtained from the CC analysis.
Expected (right) 95\%~CL exclusion limits on the gluino mass as a function of BR$(\tilde{g} \to b\bar{b}\tilde\chi^{0}_{1}$) (vertical) and BR$(\tilde{g} \to t\bar{t}\tilde\chi^{0}_{1}$) (horizontal) for Gtb models with $m(\tilde\chi^{0}_{1}) = 600$~GeV, obtained from the CC analysis.
Expected (right) 95\%~CL exclusion limits on the gluino mass as a function of BR$(\tilde{g} \to b\bar{b}\tilde\chi^{0}_{1}$) (vertical) and BR$(\tilde{g} \to t\bar{t}\tilde\chi^{0}_{1}$) (horizontal) for Gtb models with $m(\tilde\chi^{0}_{1}) = 600$~GeV, obtained from the CC analysis.
Observed (left) 95\%~CL exclusion limits on the gluino mass as a function of BR$(\tilde{g} \to b\bar{b}\tilde\chi^{0}_{1}$) (vertical) and BR$(\tilde{g} \to t\bar{t}\tilde\chi^{0}_{1}$) (horizontal) for Gtb models with $m(\tilde\chi^{0}_{1}) = 1$~TeV, obtained from the CC analysis.
Observed (left) 95\%~CL exclusion limits on the gluino mass as a function of BR$(\tilde{g} \to b\bar{b}\tilde\chi^{0}_{1}$) (vertical) and BR$(\tilde{g} \to t\bar{t}\tilde\chi^{0}_{1}$) (horizontal) for Gtb models with $m(\tilde\chi^{0}_{1}) = 1$~TeV, obtained from the CC analysis.
Expected (right) 95\%~CL exclusion limits on the gluino mass as a function of BR$(\tilde{g} \to b\bar{b}\tilde\chi^{0}_{1}$) (vertical) and BR$(\tilde{g} \to t\bar{t}\tilde\chi^{0}_{1}$) (horizontal) for Gtb models with $m(\tilde\chi^{0}_{1}) = 1$~TeV, obtained from the CC analysis.
Expected (right) 95\%~CL exclusion limits on the gluino mass as a function of BR$(\tilde{g} \to b\bar{b}\tilde\chi^{0}_{1}$) (vertical) and BR$(\tilde{g} \to t\bar{t}\tilde\chi^{0}_{1}$) (horizontal) for Gtb models with $m(\tilde\chi^{0}_{1}) = 1$~TeV, obtained from the CC analysis.
Observed exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gtt models obtained from the CC analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Observed exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gtt models obtained from the CC analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Observed exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gtt models obtained from the CC analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Observed exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gtt models obtained from the CC analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Observed exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gtt models obtained from the CC analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Observed exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gtt models obtained from the CC analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Expected exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gtt models obtained from the CC analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Expected exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gtt models obtained from the CC analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Expected exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gtt models obtained from the CC analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Expected exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gtt models obtained from the CC analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Expected exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gtt models obtained from the CC analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Expected exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gtt models obtained from the CC analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Observed exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gbb models obtained from the CC analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Observed exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gbb models obtained from the CC analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Observed exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gbb models obtained from the CC analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Observed exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gbb models obtained from the CC analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Observed exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gbb models obtained from the CC analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Observed exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gbb models obtained from the CC analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Expected exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gbb models obtained from the CC analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Expected exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gbb models obtained from the CC analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Expected exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gbb models obtained from the CC analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Expected exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gbb models obtained from the CC analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Expected exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gbb models obtained from the CC analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Expected exclusion limit in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gbb models obtained from the CC analysis. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm 1 \sigma$ of its theoretical uncertainty.
Upper limit at 95\% CL on the cross-section times branching ratio (fb) in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gbb (right) models obtained from the CC analysis. The numbers give the observed 95\% CL upper limit on the cross section in fb, with the label colour matching the associated best-expected region. Only a lower limit on the excluded cross section (>0.7 fb) is given at some points due to the very small number events expected and observed in the chosen SR. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background theoretical uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm1\sigma$ of its theoretical uncertainty.
Upper limit at 95\% CL on the cross-section times branching ratio (fb) in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gbb (right) models obtained from the CC analysis. The numbers give the observed 95\% CL upper limit on the cross section in fb, with the label colour matching the associated best-expected region. Only a lower limit on the excluded cross section (>0.7 fb) is given at some points due to the very small number events expected and observed in the chosen SR. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background theoretical uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm1\sigma$ of its theoretical uncertainty.
Upper limit at 95\% CL on the cross-section times branching ratio (fb) in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gbb (right) models obtained from the NN analysis. The numbers give the observed 95\% CL upper limit on the cross section in fb, with the label colour matching the associated best-expected region. Only a lower limit on the excluded cross section (>0.7 fb) is given at some points due to the very small number events expected and observed in the chosen SR. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background theoretical uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm1\sigma$ of its theoretical uncertainty.
Upper limit at 95\% CL on the cross-section times branching ratio (fb) in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gbb (right) models obtained from the NN analysis. The numbers give the observed 95\% CL upper limit on the cross section in fb, with the label colour matching the associated best-expected region. Only a lower limit on the excluded cross section (>0.7 fb) is given at some points due to the very small number events expected and observed in the chosen SR. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background theoretical uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm1\sigma$ of its theoretical uncertainty.
Upper limit at 95\% CL on the cross-section times branching ratio (fb) in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gtt (left) models obtained from the CC analysis. The numbers give the observed 95\% CL upper limit on the cross section in fb, with the label colour matching the associated best-expected region. Only a lower limit on the excluded cross section (>0.7 fb) is given at some points due to the very small number events expected and observed in the chosen SR. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background theoretical uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm1\sigma$ of its theoretical uncertainty.
Upper limit at 95\% CL on the cross-section times branching ratio (fb) in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gtt (left) models obtained from the CC analysis. The numbers give the observed 95\% CL upper limit on the cross section in fb, with the label colour matching the associated best-expected region. Only a lower limit on the excluded cross section (>0.7 fb) is given at some points due to the very small number events expected and observed in the chosen SR. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background theoretical uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm1\sigma$ of its theoretical uncertainty.
Upper limit at 95\% CL on the cross-section times branching ratio (fb) in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gtt (left) models obtained from the NN analysis. The numbers give the observed 95\% CL upper limit on the cross section in fb, with the label colour matching the associated best-expected region. Only a lower limit on the excluded cross section (>0.7 fb) is given at some points due to the very small number events expected and observed in the chosen SR. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background theoretical uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm1\sigma$ of its theoretical uncertainty.
Upper limit at 95\% CL on the cross-section times branching ratio (fb) in the $\tilde{g}$--$\tilde\chi^0_1$ mass plane for the Gtt (left) models obtained from the NN analysis. The numbers give the observed 95\% CL upper limit on the cross section in fb, with the label colour matching the associated best-expected region. Only a lower limit on the excluded cross section (>0.7 fb) is given at some points due to the very small number events expected and observed in the chosen SR. The dashed and solid bold lines show the 95\% CL expected and observed limits, respectively. The shaded bands around the expected limits show the impact of the experimental and background theoretical uncertainties. The dotted lines show the impact on the observed limit of the variation of the nominal signal cross-section by $\pm1\sigma$ of its theoretical uncertainty.
Acceptance for SR-Gtt-0L-B and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gtt-0L-B and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gtt-0L-B and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gtt-0L-B and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gtt-0L-M1 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gtt-0L-M1 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gtt-0L-M1 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gtt-0L-M1 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gtt-0L-M2 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gtt-0L-M2 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gtt-0L-M2 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gtt-0L-M2 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gtt-0L-C and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gtt-0L-C and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gtt-0L-C and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gtt-0L-C and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gtt-1L-B and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gtt-1L-B and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gtt-1L-B and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gtt-1L-B and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gtt-1L-M1 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gtt-1L-M1 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gtt-1L-M1 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gtt-1L-M1 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gtt-1L-M2 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gtt-1L-M2 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gtt-1L-M2 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gtt-1L-M2 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gtt-1L-C and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gtt-1L-C and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gtt-1L-C and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gtt-1L-C and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gbb-B and the $\tilde{g}\rightarrow b\bar{b}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gbb-B and the $\tilde{g}\rightarrow b\bar{b}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gbb-B and the $\tilde{g}\rightarrow b\bar{b}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gbb-B and the $\tilde{g}\rightarrow b\bar{b}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gbb-M and the $\tilde{g}\rightarrow b\bar{b}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gbb-M and the $\tilde{g}\rightarrow b\bar{b}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gbb-M and the $\tilde{g}\rightarrow b\bar{b}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gbb-M and the $\tilde{g}\rightarrow b\bar{b}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gbb-C and the $\tilde{g}\rightarrow b\bar{b}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gbb-C and the $\tilde{g}\rightarrow b\bar{b}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gbb-C and the $\tilde{g}\rightarrow b\bar{b}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gbb-C and the $\tilde{g}\rightarrow b\bar{b}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gtt-2100-1 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gtt-2100-1 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gtt-2100-1 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gtt-2100-1 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gtt-1800-1 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gtt-1800-1 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gtt-1800-1 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gtt-1800-1 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gtt-2300-1200 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gtt-2300-1200 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gtt-2300-1200 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gtt-2300-1200 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gtt-1900-1400 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gtt-1900-1400 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gtt-1900-1400 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gtt-1900-1400 and the $\tilde{g}\rightarrow t\bar{t}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gbb-2800-1400 and the $\tilde{g}\rightarrow b\bar{b}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gbb-2800-1400 and the $\tilde{g}\rightarrow b\bar{b}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gbb-2800-1400 and the $\tilde{g}\rightarrow b\bar{b}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gbb-2800-1400 and the $\tilde{g}\rightarrow b\bar{b}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gbb-2300-1000 and the $\tilde{g}\rightarrow b\bar{b}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gbb-2300-1000 and the $\tilde{g}\rightarrow b\bar{b}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gbb-2300-1000 and the $\tilde{g}\rightarrow b\bar{b}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gbb-2300-1000 and the $\tilde{g}\rightarrow b\bar{b}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gbb-2100-1600 and the $\tilde{g}\rightarrow b\bar{b}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gbb-2100-1600 and the $\tilde{g}\rightarrow b\bar{b}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gbb-2100-1600 and the $\tilde{g}\rightarrow b\bar{b}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gbb-2100-1600 and the $\tilde{g}\rightarrow b\bar{b}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gbb-2000-1800 and the $\tilde{g}\rightarrow b\bar{b}\tilde\chi^0_1$ signal process.
Acceptance for SR-Gbb-2000-1800 and the $\tilde{g}\rightarrow b\bar{b}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gbb-2000-1800 and the $\tilde{g}\rightarrow b\bar{b}\tilde\chi^0_1$ signal process.
Efficiency for SR-Gbb-2000-1800 and the $\tilde{g}\rightarrow b\bar{b}\tilde\chi^0_1$ signal process.
Cutflow for the SR-Gtt-0L-B for a representative Gtt signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gtt-0L-B for a representative Gtt signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gtt-0L-M1 for a representative Gtt signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gtt-0L-M1 for a representative Gtt signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gtt-0L-M2 for a representative Gtt signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gtt-0L-M2 for a representative Gtt signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gtt-0L-C for a representative Gtt signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gtt-0L-C for a representative Gtt signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gtt-1L-B for a representative Gtt signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gtt-1L-B for a representative Gtt signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gtt-1L-M1 for a representative Gtt signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gtt-1L-M1 for a representative Gtt signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gtt-1L-M2 for a representative Gtt signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gtt-1L-M2 for a representative Gtt signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gtt-1L-C for a representative Gtt signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gtt-1L-C for a representative Gtt signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gbb-B for a representative Gbb signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gbb-B for a representative Gbb signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gbb-M for a representative Gbb signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gbb-M for a representative Gbb signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gbb-C for a representative Gbb signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gbb-C for a representative Gbb signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gtb-B for a representative Gtb signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gtb-B for a representative Gtb signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gtb-M for a representative Gtb signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gtb-M for a representative Gtb signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gtb-C for a representative Gtb signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gtb-C for a representative Gtb signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gtt-2100-1 for a representative Gtt signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gtt-2100-1 for a representative Gtt signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gtt-1800-1 for a representative Gtt signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gtt-1800-1 for a representative Gtt signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gtt-2300-1200 for a representative Gtt signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gtt-2300-1200 for a representative Gtt signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gtt-1900-1400 for a representative Gtt signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gtt-1900-1400 for a representative Gtt signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gbb-2800-1400 for a representative Gbb signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gbb-2800-1400 for a representative Gbb signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gbb-2300-1000 for a representative Gbb signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gbb-2300-1000 for a representative Gbb signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gbb-2100-1600 for a representative Gbb signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gbb-2100-1600 for a representative Gbb signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gbb-2000-1800 for a representative Gbb signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
Cutflow for the SR-Gbb-2000-1800 for a representative Gbb signal. Signal was generated with 30000 events. Expected yields are normalised to a luminosity of 139~fb$^{-1}$.
This paper presents studies of Bose-Einstein correlations (BEC) in proton-proton collisions at a centre-of-mass energy of 13 TeV, using data from the ATLAS detector at the CERN Large Hadron Collider. Data were collected in a special low-luminosity configuration with a minimum-bias trigger and a high-multiplicity track trigger, accumulating integrated luminosities of 151 $\mu$b$^{-1}$ and 8.4 nb$^{-1}$ respectively. The BEC are measured for pairs of like-sign charged particles, each with $|\eta|$ < 2.5, for two kinematic ranges: the first with particle $p_T$ > 100 MeV and the second with particle $p_T$ > 500 MeV. The BEC parameters, characterizing the source radius and particle correlation strength, are investigated as functions of charged-particle multiplicity (up to 300) and average transverse momentum of the pair (up to 1.5 GeV). The double-differential dependence on charged-particle multiplicity and average transverse momentum of the pair is also studied. The BEC radius is found to be independent of the charged-particle multiplicity for high charged-particle multiplicity (above 100), confirming a previous observation at lower energy. This saturation occurs independent of the transverse momentum of the pair.
Comparison of single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q) and C<sub>2</sub><sup>MC</sup>(Q), with the two-particle double-ratio correlation function, R<sub>2</sub>(Q), for the high-multiplicity track (HMT) events using the opposite hemisphere (OHP) like-charge particles pairs reference sample for k<sub>T</sub> - interval 1000 < k<sub>T</sub> ≤ 1500 MeV.
Comparison of single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q) and C<sub>2</sub><sup>MC</sup>(Q), with the two-particle double-ratio correlation function, R<sub>2</sub>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k<sub>T</sub> - interval 1000 < k<sub>T</sub> ≤ 1500 MeV.
The Bose-Einstein correlation (BEC) parameter R as a function of n<sub>ch</sub> for MB events using different MC generators in the calculation of R<sub>2</sub>(Q). The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.
The Bose-Einstein correlation (BEC) parameter R as a function of n<sub>ch</sub> for HMT events using different MC generators in the calculation of R<sub>2</sub>(Q). The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.
The Bose-Einstein correlation (BEC) parameter R as a function of k<sub>T</sub> for MB events using different MC generators in the calculation of R<sub>2</sub>(Q). The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.
The Bose-Einstein correlation (BEC) parameter λ as a function of k<sub>T</sub> for MB events using different MC generators in the calculation of R<sub>2</sub>(Q). The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.
The two-particle double-ratio correlation function, R<sub>2</sub>(Q), for pp collisions for track p<sub>T</sub> >100 MeV at √s=13 TeV in the multiplicity interval 71 ≤ n<sub>ch</sub> < 80 for the minimum-bias (MB) events. The blue dashed and red solid lines show the results of the exponential and Gaussian fits, respectively. The region excluded from the fits is shown. The statistical uncertainty and the systematic uncertainty for imperfections in the data reconstruction procedure are added in quadrature.
The two-particle double-ratio correlation function, R<sub>2</sub>(Q), for pp collisions for track p<sub>T</sub> >100 MeV at √s=13 TeV in the multiplicity interval 231 ≤ n<sub>ch</sub> < 300 for the high-multiplicity track (HMT) events. The blue dashed and red solid lines show the results of the exponential and Gaussian fits, respectively. The region excluded from the fits is shown. The statistical uncertainty and the systematic uncertainty for imperfections in the data reconstruction procedure are added in quadrature.
The dependence of the correlation strength, λ(m<sub>ch</sub>), on rescaled multiplicity, m<sub>ch</sub>, obtained from the exponential fit of the R<sub>2</sub>(Q) correlation functions for tracks with p<sub>T</sub> > 100 MeV and p<sub>T</sub> > 500 MeV at √s = 13 TeV for the minimum-bias (MB) and high multiplicity track (HMT) data. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the exponential fit of λ(m<sub>ch</sub>) for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively.
The dependence of the correlation strength, λ(m<sub>ch</sub>), on rescaled multiplicity, m<sub>ch</sub>, obtained from the exponential fit of the R<sub>2</sub>(Q) correlation functions for tracks with p<sub>T</sub> > 100 MeV and p<sub>T</sub> > 500 MeV at √s = 13 TeV for the minimum-bias (MB) and high multiplicity track (HMT) data. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the exponential fit of λ(m<sub>ch</sub>) for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively.
The dependence of the correlation strength, λ(m<sub>ch</sub>), on rescaled multiplicity, m<sub>ch</sub>, obtained from the exponential fit of the R<sub>2</sub>(Q) correlation functions for tracks with p<sub>T</sub> > 100 MeV and p<sub>T</sub> > 500 MeV at √s = 13 TeV for the minimum-bias (MB) and high multiplicity track (HMT) data. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the exponential fit of λ(m<sub>ch</sub>) for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively.
The dependence of the correlation strength, λ(m<sub>ch</sub>), on rescaled multiplicity, m<sub>ch</sub>, obtained from the exponential fit of the R<sub>2</sub>(Q) correlation functions for tracks with p<sub>T</sub> > 100 MeV and p<sub>T</sub> > 500 MeV at √s = 13 TeV for the minimum-bias (MB) and high multiplicity track (HMT) data. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the exponential fit of λ(m<sub>ch</sub>) for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively.
The dependence of the source radius, R(m<sub>ch</sub>), on m<sub>ch</sub>. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> < 1.2 for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m<sub>ch</sub> > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> > 1.45 with p<sub>T</sub> >100 MeV and for ∛m<sub>ch</sub> > 1.6 with p<sub>T</sub> >500 MeV, respectively.
The dependence of the source radius, R(m<sub>ch</sub>), on m<sub>ch</sub>. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> < 1.2 for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m<sub>ch</sub> > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> > 1.45 with p<sub>T</sub> >100 MeV and for ∛m<sub>ch</sub> > 1.6 with p<sub>T</sub> >500 MeV, respectively.
The dependence of the source radius, R(m<sub>ch</sub>), on m<sub>ch</sub>. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> < 1.2 for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m<sub>ch</sub> > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> > 1.45 with p<sub>T</sub> >100 MeV and for ∛m<sub>ch</sub> > 1.6 with p<sub>T</sub> >500 MeV, respectively.
The dependence of the source radius, R(m<sub>ch</sub>), on m<sub>ch</sub>. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> < 1.2 for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m<sub>ch</sub> > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> > 1.45 with p<sub>T</sub> >100 MeV and for ∛m<sub>ch</sub> > 1.6 with p<sub>T</sub> >500 MeV, respectively.
The dependence of the R(m<sub>ch</sub>) on ∛m<sub>ch</sub>. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> < 1.2 for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m<sub>ch</sub> > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> > 1.45 with p<sub>T</sub> >100 MeV and for ∛m<sub>ch</sub> > 1.6 with p<sub>T</sub> >500 MeV, respectively
The dependence of the R(m<sub>ch</sub>) on ∛m<sub>ch</sub>. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> < 1.2 for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m<sub>ch</sub> > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> > 1.45 with p<sub>T</sub> >100 MeV and for ∛m<sub>ch</sub> > 1.6 with p<sub>T</sub> >500 MeV, respectively
The dependence of the R(m<sub>ch</sub>) on ∛m<sub>ch</sub>. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> < 1.2 for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m<sub>ch</sub> > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> > 1.45 with p<sub>T</sub> >100 MeV and for ∛m<sub>ch</sub> > 1.6 with p<sub>T</sub> >500 MeV, respectively
The dependence of the R(m<sub>ch</sub>) on ∛m<sub>ch</sub>. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> < 1.2 for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m<sub>ch</sub> > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> > 1.45 with p<sub>T</sub> >100 MeV and for ∛m<sub>ch</sub> > 1.6 with p<sub>T</sub> >500 MeV, respectively
Comparison of single-ratio two-particle correlation functions, using the unlike-charge particle (UCP) pair reference sample, for minimum-bias (MB) events, showing C<sub>2</sub><sup>data</sup>(Q) (top panel) at 13 TeV (black circles) and 7 TeV (open blue circles), and the ratio of C<sub>2</sub><sup>7 TeV</sup> (Q) to C<sub>2</sub><sup>13 TeV</sup> (Q) (bottom panel). Comparison of C<sub>2</sub><sup>data</sup> (Q) for representative multiplicity region 3.09 < m<sub>ch</sub> ≤ 3.86. The statistical and systematic uncertainties, combined in quadrature, are presented. The systematic uncertainties include track efficiency, Coulomb correction, non-closure and multiplicity-unfolding uncertainties.
Comparison of single-ratio two-particle correlation functions, using the unlike-charge particle (UCP) pair reference sample, for minimum-bias (MB) events, showing C<sub>2</sub><sup>data</sup>(Q) (top panel) at 13 TeV (black circles) and 7 TeV (open blue circles), and the ratio of C<sub>2</sub><sup>7 TeV</sup> (Q) to C<sub>2</sub><sup>13 TeV</sup> (Q) (bottom panel). Comparison of C<sub>2</sub><sup>data</sup> (Q) for representative k<sub>T</sub> region 400 < k<sub>T</sub> ≤500 MeV. The statistical and systematic uncertainties, combined in quadrature, are presented. The systematic uncertainties include track efficiency, Coulomb correction, non-closure and multiplicity-unfolding uncertainties.
The k<sub>T</sub> dependence of the correlation strength, λ(k<sub>T</sub>), obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions for events with multiplicity n<sub>ch</sub> ≥ 2 and transfer momentum of tracks with p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to λ(k<sub>T</sub>).
The k<sub>T</sub> dependence of the correlation strength, λ(k<sub>T</sub>), obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions for events with multiplicity n<sub>ch</sub> ≥ 2 and transfer momentum of tracks with p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to λ(k<sub>T</sub>).
The k<sub>T</sub> dependence of the correlation strength, λ(k<sub>T</sub>), obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions for events with multiplicity n<sub>ch</sub> ≥ 2 and transfer momentum of tracks with p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to λ(k<sub>T</sub>).
The k<sub>T</sub> dependence of the correlation strength, λ(k<sub>T</sub>), obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions for events with multiplicity n<sub>ch</sub> ≥ 2 and transfer momentum of tracks with p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to λ(k<sub>T</sub>).
The k<sub>T</sub> dependence of the source radius, R(k<sub>T</sub>), obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions for events with multiplicity n<sub>ch</sub> ≥ 2 and transfer momentum of tracks with p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to R(k<sub>T</sub>).
The k<sub>T</sub> dependence of the source radius, R(k<sub>T</sub>), obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions for events with multiplicity n<sub>ch</sub> ≥ 2 and transfer momentum of tracks with p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to R(k<sub>T</sub>).
The k<sub>T</sub> dependence of the source radius, R(k<sub>T</sub>), obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions for events with multiplicity n<sub>ch</sub> ≥ 2 and transfer momentum of tracks with p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to R(k<sub>T</sub>).
The k<sub>T</sub> dependence of the source radius, R(k<sub>T</sub>), obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions for events with multiplicity n<sub>ch</sub> ≥ 2 and transfer momentum of tracks with p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to R(k<sub>T</sub>).
The two-dimensional dependence on m<sub>ch</sub> and k<sub>T</sub> for p<sub>T</sub> > 100 MeV for the correlation strength, λ, obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions using the MB sample for m<sub>ch</sub> ≤ 3.08 and the HMT sample for m<sub>ch</sub> > 3.08.
The two-dimensional dependence on m<sub>ch</sub> and k<sub>T</sub> for p<sub>T</sub> > 100 MeV for the source radius, R, obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions using the MB sample for m<sub>ch</sub> ≤ 3.08 and the HMT sample for m<sub>ch</sub> > 3.08.
The parameter λ for p<sub>T</sub> > 100 MeV as a function of k<sub>T</sub> in selected low m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter λ for p<sub>T</sub> > 100 MeV as a function of k<sub>T</sub> in selected low m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter λ for p<sub>T</sub> > 100 MeV as a function of k<sub>T</sub> in selected high m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter λ for p<sub>T</sub> > 100 MeV as a function of k<sub>T</sub> in selected high m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter λ for p<sub>T</sub> > 100 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.1 and 0.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter λ for p<sub>T</sub> > 100 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.1 and 0.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter λ for p<sub>T</sub> > 100 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.5 and 1.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter λ for p<sub>T</sub> > 100 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.5 and 1.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 100 MeV as a function of k<sub>T</sub> in selected low m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 100 MeV as a function of k<sub>T</sub> in selected low m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 100 MeV as a function of k<sub>T</sub> in selected high m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 100 MeV as a function of k<sub>T</sub> in selected high m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 100 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.1 and 0.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 100 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.1 and 0.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 100 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.5 and 1.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 100 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.5 and 1.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
The fit parameter μ describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter μ on m<sub>ch</sub> for tracks with p<sub>T</sub> >100 MeV (p<sub>T</sub> >500 MeV).
The fit parameter μ describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter μ on m<sub>ch</sub> for tracks with p<sub>T</sub> >100 MeV (p<sub>T</sub> >500 MeV).
The fit parameter μ describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter μ on m<sub>ch</sub> for tracks with p<sub>T</sub> >100 MeV (p<sub>T</sub> >500 MeV).
The fit parameter μ describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter μ on m<sub>ch</sub> for tracks with p<sub>T</sub> >100 MeV (p<sub>T</sub> >500 MeV).
The fit parameter ν describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter ν on m<sub>ch</sub> for tracks with p<sub>T</sub> >100 MeV (p<sub>T</sub> >500 MeV).
The fit parameter ν describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter ν on m<sub>ch</sub> for tracks with p<sub>T</sub> >100 MeV (p<sub>T</sub> >500 MeV).
The fit parameter ν describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter ν on m<sub>ch</sub> for tracks with p<sub>T</sub> >100 MeV (p<sub>T</sub> >500 MeV).
The fit parameter ν describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter ν on m<sub>ch</sub> for tracks with p<sub>T</sub> >100 MeV (p<sub>T</sub> >500 MeV).
The parameter ξ describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m<sub>ch</sub>, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the saturated value of the parameter ξ for m<sub>ch</sub> > 3.0 for tracks with p<sub>T</sub> >100 MeV and for m<sub>ch</sub> > 2.8 for tracks with p<sub>T</sub> >500 MeV, respectively.
The parameter ξ describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m<sub>ch</sub>, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the saturated value of the parameter ξ for m<sub>ch</sub> > 3.0 for tracks with p<sub>T</sub> >100 MeV and for m<sub>ch</sub> > 2.8 for tracks with p<sub>T</sub> >500 MeV, respectively.
The parameter ξ describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m<sub>ch</sub>, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the saturated value of the parameter ξ for m<sub>ch</sub> > 3.0 for tracks with p<sub>T</sub> >100 MeV and for m<sub>ch</sub> > 2.8 for tracks with p<sub>T</sub> >500 MeV, respectively.
The parameter ξ describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m<sub>ch</sub>, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the saturated value of the parameter ξ for m<sub>ch</sub> > 3.0 for tracks with p<sub>T</sub> >100 MeV and for m<sub>ch</sub> > 2.8 for tracks with p<sub>T</sub> >500 MeV, respectively.
The parameter κ describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m<sub>ch</sub>, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the exponential fit to the parameter κ for tracks with p<sub>T</sub> >100 MeV and for tracks with p<sub>T</sub> >500 MeV, respectively.
The parameter κ describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m<sub>ch</sub>, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the exponential fit to the parameter κ for tracks with p<sub>T</sub> >100 MeV and for tracks with p<sub>T</sub> >500 MeV, respectively.
The parameter κ describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m<sub>ch</sub>, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the exponential fit to the parameter κ for tracks with p<sub>T</sub> >100 MeV and for tracks with p<sub>T</sub> >500 MeV, respectively.
The parameter κ describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m<sub>ch</sub>, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the exponential fit to the parameter κ for tracks with p<sub>T</sub> >100 MeV and for tracks with p<sub>T</sub> >500 MeV, respectively.
The two-dimensional dependence on m<sub>ch</sub> and k<sub>T</sub> for p<sub>T</sub> > 500 MeV for the correlation strength, λ, obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions using the MB sample for m<sub>ch</sub> ≤ 3.08 and the HMT sample for m<sub>ch</sub> > 3.08.
The two-dimensional dependence on m<sub>ch</sub> and k<sub>T</sub> for p<sub>T</sub> > 500 MeV for the source radius, R, obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions using the MB sample for m<sub>ch</sub> ≤ 3.08 and the HMT sample for m<sub>ch</sub> > 3.08.
The parameter λ for p<sub>T</sub> > 500 MeV as a function of k<sub>T</sub> in selected low m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter λ for p<sub>T</sub> > 500 MeV as a function of k<sub>T</sub> in selected low m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter λ for p<sub>T</sub> > 500 MeV as a function of k<sub>T</sub> in selected high m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter λ for p<sub>T</sub> > 500 MeV as a function of k<sub>T</sub> in selected high m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter λ for p<sub>T</sub> > 500 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.5 and 1.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter λ for p<sub>T</sub> > 500 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.5 and 1.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 500 MeV as a function of k<sub>T</sub> in selected low m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 500 MeV as a function of k<sub>T</sub> in selected low m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 500 MeV as a function of k<sub>T</sub> in selected high m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 500 MeV as a function of k<sub>T</sub> in selected high m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 500 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.5 and 1.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 500 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.5 and 1.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
ATLAS and CMS results for the source radius R as a function of n<sub>ch</sub> in pp interactions at 13 TeV. The CMS results (open circles) have been adjusted (by the CMS collaboration) to the ATLAS kinematic region∶ p<sub>T</sub> > 100 MeV and |η|<2.5. The ATLAS uncertainties are the sum in quadrature of the statistical and asymmetric systematic uncertainties. For CMS, only the systematic uncertainties are shown since the statistical uncertainties are smaller than the marker size. The dashed blue (ATLAS) and black (CMS) lines represent the fit to ∛n<sub>ch</sub> at low multiplicity, continued as dotted lines beyond the fit range. The solid green (ATLAS) and broken black (CMS) lines indicate the plateau level at high multiplicity.
ATLAS and CMS results for the source radius R as a function of n<sub>ch</sub> in pp interactions at 13 TeV. The CMS results (open circles) have been adjusted (by the CMS collaboration) to the ATLAS kinematic region∶ p<sub>T</sub> > 100 MeV and |η|<2.5. The ATLAS uncertainties are the sum in quadrature of the statistical and asymmetric systematic uncertainties. For CMS, only the systematic uncertainties are shown since the statistical uncertainties are smaller than the marker size. The dashed blue (ATLAS) and black (CMS) lines represent the fit to ∛n<sub>ch</sub> at low multiplicity, continued as dotted lines beyond the fit range. The solid green (ATLAS) and broken black (CMS) lines indicate the plateau level at high multiplicity.
ATLAS and CMS results for the source radius R as a function of n<sub>ch</sub> in pp interactions at 13 TeV. The CMS results (open circles) have been adjusted (by the CMS collaboration) to the ATLAS kinematic region∶ p<sub>T</sub> > 100 MeV and |η|<2.5. The ATLAS uncertainties are the sum in quadrature of the statistical and asymmetric systematic uncertainties. For CMS, only the systematic uncertainties are shown since the statistical uncertainties are smaller than the marker size. The dashed blue (ATLAS) and black (CMS) lines represent the fit to ∛n<sub>ch</sub> at low multiplicity, continued as dotted lines beyond the fit range. The solid green (ATLAS) and broken black (CMS) lines indicate the plateau level at high multiplicity.
ATLAS and CMS results for the source radius R as a function of ∛n<sub>ch</sub> in pp interactions at 13 TeV. The CMS results (open circles) have been adjusted (by the CMS collaboration) to the ATLAS kinematic region∶ p<sub>T</sub> > 100 MeV and |η|<2.5. The ATLAS uncertainties are the sum in quadrature of the statistical and asymmetric systematic uncertainties. For CMS, only the systematic uncertainties are shown since the statistical uncertainties are smaller than the marker size. The dashed blue (ATLAS) and black (CMS) lines represent the fit to ∛n<sub>ch</sub> at low multiplicity, continued as dotted lines beyond the fit range. The solid green (ATLAS) and broken black (CMS) lines indicate the plateau level at high multiplicity.
ATLAS and CMS results for the source radius R as a function of ∛n<sub>ch</sub> in pp interactions at 13 TeV. The CMS results (open circles) have been adjusted (by the CMS collaboration) to the ATLAS kinematic region∶ p<sub>T</sub> > 100 MeV and |η|<2.5. The ATLAS uncertainties are the sum in quadrature of the statistical and asymmetric systematic uncertainties. For CMS, only the systematic uncertainties are shown since the statistical uncertainties are smaller than the marker size. The dashed blue (ATLAS) and black (CMS) lines represent the fit to ∛n<sub>ch</sub> at low multiplicity, continued as dotted lines beyond the fit range. The solid green (ATLAS) and broken black (CMS) lines indicate the plateau level at high multiplicity.
ATLAS and CMS results for the source radius R as a function of ∛n<sub>ch</sub> in pp interactions at 13 TeV. The CMS results (open circles) have been adjusted (by the CMS collaboration) to the ATLAS kinematic region∶ p<sub>T</sub> > 100 MeV and |η|<2.5. The ATLAS uncertainties are the sum in quadrature of the statistical and asymmetric systematic uncertainties. For CMS, only the systematic uncertainties are shown since the statistical uncertainties are smaller than the marker size. The dashed blue (ATLAS) and black (CMS) lines represent the fit to ∛n<sub>ch</sub> at low multiplicity, continued as dotted lines beyond the fit range. The solid green (ATLAS) and broken black (CMS) lines indicate the plateau level at high multiplicity.
Systematic uncertainties (in percent) in the correlation strength, λ, and source radius, R, for the exponential fit of the two-particle double-ratio correlation functions, R<sub>2</sub>(Q), for p<sub>T</sub> > 100 MeV at √s= 13 TeV for the MB and HMT events. The choice of MC generator gives rise to asymmetric uncertainties, denoted by uparrow and downarrow. This asymmetry propagates through to the cumulative uncertainty. The columns under ‘Uncertainty range’ show the range of systematic uncertainty from the fits in the various n<sub>ch</sub> intervals.
The results of the fits to the dependencies of the correlation strength, λ, and source radius, R, on the average rescaled charged-particle multiplicity, m<sub>ch</sub>, for |η| < 2.5 and both p<sub>T</sub> > 100 MeV and p<sub>T</sub> > 500 MeV at √s = 13 TeV for the minimum-bias (MB) and the high-multiplicity track (HMT) events. The parameters γ and δ resulting from a joint fit to the MB and HMT data are presented. The total uncertainties are shown.
The results of the fits to the dependencies of the correlation strength, λ, and source radius, R, on the pair average transverse momentum, k<sub>T</sub>, for various functional forms and for minimum-bias (MB) and high-multiplicity track (HMT) events for p<sub>T</sub> > 100 MeV and p<sub>T</sub> > 500 MeV at √s = 13 TeV. The total uncertainties are shown.
The Bose-Einstein correlation (BEC) parameters λ and R as a function of n<sub>ch</sub> and k<sub>T</sub> using different MC generators in the calculation of R<sub>2</sub>(Q). (a) λ versus n<sub>ch</sub> for MB events, (b) λ versus n<sub>ch</sub> for HMT events, (c) λ versus k<sub>T</sub> and (d) R versus k<sub>T</sub> for MB events. The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.
The Bose-Einstein correlation (BEC) parameters λ and R as a function of n<sub>ch</sub> and k<sub>T</sub> using different MC generators in the calculation of R<sub>2</sub>(Q). (a) λ versus n<sub>ch</sub> for MB events, (b) λ versus n<sub>ch</sub> for HMT events, (c) λ versus k<sub>T</sub> and (d) R versus k<sub>T</sub> for MB events. The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.
The Bose-Einstein correlation (BEC) parameters λ and R as a function of n<sub>ch</sub> and k<sub>T</sub> using different MC generators in the calculation of R<sub>2</sub>(Q). (a) λ versus n<sub>ch</sub> for MB events, (b) λ versus n<sub>ch</sub> for HMT events, (c) λ versus k<sub>T</sub> and (d) R versus k<sub>T</sub> for MB events. The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.
The Bose-Einstein correlation (BEC) parameters λ and R as a function of n<sub>ch</sub> and k<sub>T</sub> using different MC generators in the calculation of R<sub>2</sub>(Q). (a) λ versus n<sub>ch</sub> for MB events, (b) λ versus n<sub>ch</sub> for HMT events, (c) λ versus k<sub>T</sub> and (d) R versus k<sub>T</sub> for MB events. The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 10, (b) 11 < n<sub>ch</sub> ≤ 20, (c) 21 < n<sub>ch</sub> ≤ 30, (d) 31 < n<sub>ch</sub> ≤ 40, (e) 41 < n<sub>ch</sub> ≤ 50, (f) 51 < n<sub>ch</sub> ≤ 60, (g) 61 < n<sub>ch</sub> ≤ 70, (h) 71 < n<sub>ch</sub> ≤ 80 and (i) 81 < n<sub>ch</sub> ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 10, (b) 11 < n<sub>ch</sub> ≤ 20, (c) 21 < n<sub>ch</sub> ≤ 30, (d) 31 < n<sub>ch</sub> ≤ 40, (e) 41 < n<sub>ch</sub> ≤ 50, (f) 51 < n<sub>ch</sub> ≤ 60, (g) 61 < n<sub>ch</sub> ≤ 70, (h) 71 < n<sub>ch</sub> ≤ 80 and (i) 81 < n<sub>ch</sub> ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 10, (b) 11 < n<sub>ch</sub> ≤ 20, (c) 21 < n<sub>ch</sub> ≤ 30, (d) 31 < n<sub>ch</sub> ≤ 40, (e) 41 < n<sub>ch</sub> ≤ 50, (f) 51 < n<sub>ch</sub> ≤ 60, (g) 61 < n<sub>ch</sub> ≤ 70, (h) 71 < n<sub>ch</sub> ≤ 80 and (i) 81 < n<sub>ch</sub> ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 10, (b) 11 < n<sub>ch</sub> ≤ 20, (c) 21 < n<sub>ch</sub> ≤ 30, (d) 31 < n<sub>ch</sub> ≤ 40, (e) 41 < n<sub>ch</sub> ≤ 50, (f) 51 < n<sub>ch</sub> ≤ 60, (g) 61 < n<sub>ch</sub> ≤ 70, (h) 71 < n<sub>ch</sub> ≤ 80 and (i) 81 < n<sub>ch</sub> ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 10, (b) 11 < n<sub>ch</sub> ≤ 20, (c) 21 < n<sub>ch</sub> ≤ 30, (d) 31 < n<sub>ch</sub> ≤ 40, (e) 41 < n<sub>ch</sub> ≤ 50, (f) 51 < n<sub>ch</sub> ≤ 60, (g) 61 < n<sub>ch</sub> ≤ 70, (h) 71 < n<sub>ch</sub> ≤ 80 and (i) 81 < n<sub>ch</sub> ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 10, (b) 11 < n<sub>ch</sub> ≤ 20, (c) 21 < n<sub>ch</sub> ≤ 30, (d) 31 < n<sub>ch</sub> ≤ 40, (e) 41 < n<sub>ch</sub> ≤ 50, (f) 51 < n<sub>ch</sub> ≤ 60, (g) 61 < n<sub>ch</sub> ≤ 70, (h) 71 < n<sub>ch</sub> ≤ 80 and (i) 81 < n<sub>ch</sub> ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 10, (b) 11 < n<sub>ch</sub> ≤ 20, (c) 21 < n<sub>ch</sub> ≤ 30, (d) 31 < n<sub>ch</sub> ≤ 40, (e) 41 < n<sub>ch</sub> ≤ 50, (f) 51 < n<sub>ch</sub> ≤ 60, (g) 61 < n<sub>ch</sub> ≤ 70, (h) 71 < n<sub>ch</sub> ≤ 80 and (i) 81 < n<sub>ch</sub> ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 10, (b) 11 < n<sub>ch</sub> ≤ 20, (c) 21 < n<sub>ch</sub> ≤ 30, (d) 31 < n<sub>ch</sub> ≤ 40, (e) 41 < n<sub>ch</sub> ≤ 50, (f) 51 < n<sub>ch</sub> ≤ 60, (g) 61 < n<sub>ch</sub> ≤ 70, (h) 71 < n<sub>ch</sub> ≤ 80 and (i) 81 < n<sub>ch</sub> ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 10, (b) 11 < n<sub>ch</sub> ≤ 20, (c) 21 < n<sub>ch</sub> ≤ 30, (d) 31 < n<sub>ch</sub> ≤ 40, (e) 41 < n<sub>ch</sub> ≤ 50, (f) 51 < n<sub>ch</sub> ≤ 60, (g) 61 < n<sub>ch</sub> ≤ 70, (h) 71 < n<sub>ch</sub> ≤ 80 and (i) 81 < n<sub>ch</sub> ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 91 < n<sub>ch</sub> ≤ 100, (b) 101 < n<sub>ch</sub> ≤ 125, (c) 126 < n<sub>ch</sub> ≤ 150, (d) 151 < n<sub>ch</sub> ≤ 200, (e) 201 < n<sub>ch</sub> ≤ 250. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 91 < n<sub>ch</sub> ≤ 100, (b) 101 < n<sub>ch</sub> ≤ 125, (c) 126 < n<sub>ch</sub> ≤ 150, (d) 151 < n<sub>ch</sub> ≤ 200, (e) 201 < n<sub>ch</sub> ≤ 250. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 91 < n<sub>ch</sub> ≤ 100, (b) 101 < n<sub>ch</sub> ≤ 125, (c) 126 < n<sub>ch</sub> ≤ 150, (d) 151 < n<sub>ch</sub> ≤ 200, (e) 201 < n<sub>ch</sub> ≤ 250. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 91 < n<sub>ch</sub> ≤ 100, (b) 101 < n<sub>ch</sub> ≤ 125, (c) 126 < n<sub>ch</sub> ≤ 150, (d) 151 < n<sub>ch</sub> ≤ 200, (e) 201 < n<sub>ch</sub> ≤ 250. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 91 < n<sub>ch</sub> ≤ 100, (b) 101 < n<sub>ch</sub> ≤ 125, (c) 126 < n<sub>ch</sub> ≤ 150, (d) 151 < n<sub>ch</sub> ≤ 200, (e) 201 < n<sub>ch</sub> ≤ 250. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 101 < n<sub>ch</sub> ≤ 110, (b) 111 < n<sub>ch</sub> ≤ 120, (c) 121 < n<sub>ch</sub> ≤ 130, (d) 131 < n<sub>ch</sub> ≤ 140, (e) 141 < n<sub>ch</sub> ≤ 155, (f) 156 < n<sub>ch</sub> ≤ 175, (g) 176 < n<sub>ch</sub> ≤ 200, (h) 201 < n<sub>ch</sub> ≤ 230 and (i) 231 < n<sub>ch</sub> ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 101 < n<sub>ch</sub> ≤ 110, (b) 111 < n<sub>ch</sub> ≤ 120, (c) 121 < n<sub>ch</sub> ≤ 130, (d) 131 < n<sub>ch</sub> ≤ 140, (e) 141 < n<sub>ch</sub> ≤ 155, (f) 156 < n<sub>ch</sub> ≤ 175, (g) 176 < n<sub>ch</sub> ≤ 200, (h) 201 < n<sub>ch</sub> ≤ 230 and (i) 231 < n<sub>ch</sub> ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 101 < n<sub>ch</sub> ≤ 110, (b) 111 < n<sub>ch</sub> ≤ 120, (c) 121 < n<sub>ch</sub> ≤ 130, (d) 131 < n<sub>ch</sub> ≤ 140, (e) 141 < n<sub>ch</sub> ≤ 155, (f) 156 < n<sub>ch</sub> ≤ 175, (g) 176 < n<sub>ch</sub> ≤ 200, (h) 201 < n<sub>ch</sub> ≤ 230 and (i) 231 < n<sub>ch</sub> ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 101 < n<sub>ch</sub> ≤ 110, (b) 111 < n<sub>ch</sub> ≤ 120, (c) 121 < n<sub>ch</sub> ≤ 130, (d) 131 < n<sub>ch</sub> ≤ 140, (e) 141 < n<sub>ch</sub> ≤ 155, (f) 156 < n<sub>ch</sub> ≤ 175, (g) 176 < n<sub>ch</sub> ≤ 200, (h) 201 < n<sub>ch</sub> ≤ 230 and (i) 231 < n<sub>ch</sub> ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 101 < n<sub>ch</sub> ≤ 110, (b) 111 < n<sub>ch</sub> ≤ 120, (c) 121 < n<sub>ch</sub> ≤ 130, (d) 131 < n<sub>ch</sub> ≤ 140, (e) 141 < n<sub>ch</sub> ≤ 155, (f) 156 < n<sub>ch</sub> ≤ 175, (g) 176 < n<sub>ch</sub> ≤ 200, (h) 201 < n<sub>ch</sub> ≤ 230 and (i) 231 < n<sub>ch</sub> ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 101 < n<sub>ch</sub> ≤ 110, (b) 111 < n<sub>ch</sub> ≤ 120, (c) 121 < n<sub>ch</sub> ≤ 130, (d) 131 < n<sub>ch</sub> ≤ 140, (e) 141 < n<sub>ch</sub> ≤ 155, (f) 156 < n<sub>ch</sub> ≤ 175, (g) 176 < n<sub>ch</sub> ≤ 200, (h) 201 < n<sub>ch</sub> ≤ 230 and (i) 231 < n<sub>ch</sub> ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 101 < n<sub>ch</sub> ≤ 110, (b) 111 < n<sub>ch</sub> ≤ 120, (c) 121 < n<sub>ch</sub> ≤ 130, (d) 131 < n<sub>ch</sub> ≤ 140, (e) 141 < n<sub>ch</sub> ≤ 155, (f) 156 < n<sub>ch</sub> ≤ 175, (g) 176 < n<sub>ch</sub> ≤ 200, (h) 201 < n<sub>ch</sub> ≤ 230 and (i) 231 < n<sub>ch</sub> ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 101 < n<sub>ch</sub> ≤ 110, (b) 111 < n<sub>ch</sub> ≤ 120, (c) 121 < n<sub>ch</sub> ≤ 130, (d) 131 < n<sub>ch</sub> ≤ 140, (e) 141 < n<sub>ch</sub> ≤ 155, (f) 156 < n<sub>ch</sub> ≤ 175, (g) 176 < n<sub>ch</sub> ≤ 200, (h) 201 < n<sub>ch</sub> ≤ 230 and (i) 231 < n<sub>ch</sub> ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 101 < n<sub>ch</sub> ≤ 110, (b) 111 < n<sub>ch</sub> ≤ 120, (c) 121 < n<sub>ch</sub> ≤ 130, (d) 131 < n<sub>ch</sub> ≤ 140, (e) 141 < n<sub>ch</sub> ≤ 155, (f) 156 < n<sub>ch</sub> ≤ 175, (g) 176 < n<sub>ch</sub> ≤ 200, (h) 201 < n<sub>ch</sub> ≤ 230 and (i) 231 < n<sub>ch</sub> ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The correlation strength, λ, and source radius, R, of the exponential fits to the two-particle double-ratio correlation functions, R<sub>2</sub>(Q), in dependence on the multiplicity, m<sub>ch</sub>, intervals for the minimum-bias (MB) and the high-multiplicity track (HMT) events for p<sub>T</sub> > 100 MeV at √s = 13 TeV. Statistical uncertainties for √χ<sup>2</sup>/ndf>1 are corrected by the √χ<sup>2</sup>/ndf. The total uncertainties are shown.
The correlation strength, λ, and source radius, R, of the exponential fits to the two-particle double-ratio correlation functions, R<sub>2</sub>(Q), in dependence on the multiplicity, m<sub>ch</sub>, intervals for the minimum-bias (MB) and the high-multiplicity track (HMT) events for p<sub>T</sub> > 500 MeV at √s = 13 TeV. Statistical uncertainties for √χ<sup>2</sup>/ndf>1 are corrected by the √χ<sup>2</sup>/ndf. The total uncertainties are shown.
The correlation strength, λ, and source radius, R, of the exponential fits to the two-particle double-ratio correlation functions, R<sub>2</sub>(Q), in dependence on the pair transverse momentum, k<sub>T</sub>, intervals for the minimum-bias (MB) and the high-multiplicity track (HMT) events for p<sub>T</sub> > 100 MeV at √s = 13 TeV. Statistical uncertainties for √χ<sup>2</sup>/ndf>1 are corrected by the √χ<sup>2</sup>/ndf. The total uncertainties are shown.
The correlation strength, λ, and source radius, R, of the exponential fits to the two-particle double-ratio correlation functions, R<sub>2</sub>(Q), in dependence on the pair transverse momentum, k<sub>T</sub>, intervals for the minimum-bias (MB) and the high-multiplicity track (HMT) events for p<sub>T</sub> > 500 MeV at √s = 13 TeV. Statistical uncertainties for √χ<sup>2</sup>/ndf>1 are corrected by the √χ<sup>2</sup>/ndf. The total uncertainties are shown.
A search for chargino$-$neutralino pair production in three-lepton final states with missing transverse momentum is presented. The study is based on a dataset of $\sqrt{s} = 13$ TeV $pp$ collisions recorded with the ATLAS detector at the LHC, corresponding to an integrated luminosity of 139 fb$^{-1}$. No significant excess relative to the Standard Model predictions is found in data. The results are interpreted in simplified models of supersymmetry, and statistically combined with results from a previous ATLAS search for compressed spectra in two-lepton final states. Various scenarios for the production and decay of charginos ($\tilde\chi^\pm_1$) and neutralinos ($\tilde\chi^0_2$) are considered. For pure higgsino $\tilde\chi^\pm_1\tilde\chi^0_2$ pair-production scenarios, exclusion limits at 95% confidence level are set on $\tilde\chi^0_2$ masses up to 210 GeV. Limits are also set for pure wino $\tilde\chi^\pm_1\tilde\chi^0_2$ pair production, on $\tilde\chi^0_2$ masses up to 640 GeV for decays via on-shell $W$ and $Z$ bosons, up to 300 GeV for decays via off-shell $W$ and $Z$ bosons, and up to 190 GeV for decays via $W$ and Standard Model Higgs bosons.
Comparison of the observed data and expected SM background yields in the CRs (pre-fit) and VRs (post-fit) of the onshell $W\!Z$ and $W\!h$ selections. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. The bottom panel shows the relative difference between the observed data and expected yields for the CRs and the significance of the difference for the VRs, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Comparison of the observed data and expected SM background yields in the CRs (pre-fit) and VRs (post-fit) of the onshell $W\!Z$ and $W\!h$ selections. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. The bottom panel shows the relative difference between the observed data and expected yields for the CRs and the significance of the difference for the VRs, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Comparison of the observed data and expected SM background yields in the CRs and VRs of the offshell $W\!Z$ selection. The SM prediction is taken from the background-only fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Comparison of the observed data and expected SM background yields in the CRs and VRs of the offshell $W\!Z$ selection. The SM prediction is taken from the background-only fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Observed and expected yields after the background-only fit in the SRs for the onshell $W\!Z$ selection. The normalization factors of the $W\!Z$ sample are extracted separately for the 0j, low-H<sub>T</sub> and high-H<sub>T</sub> regions, and are treated separately in the combined fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. Combined statistical and systematic uncertainties are presented.
Observed and expected yields after the background-only fit in the SRs for the onshell $W\!Z$ selection. The normalization factors of the $W\!Z$ sample are extracted separately for the 0j, low-H<sub>T</sub> and high-H<sub>T</sub> regions, and are treated separately in the combined fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. Combined statistical and systematic uncertainties are presented.
Observed and expected yields after the background-only fit in the SRs for the $W\!h$ selection. The normalization factors of the $W\!Z$ sample are extracted separately for the 0j, low-H<sub>T</sub> and high-H<sub>T</sub> regions, and are treated separately in the combined fit. The "Others" category contains the single-top, WW, tt̄+X and rare top processes. Combined statistical and systematic uncertainties are presented.
Observed and expected yields after the background-only fit in the SRs for the $W\!h$ selection. The normalization factors of the $W\!Z$ sample are extracted separately for the 0j, low-H<sub>T</sub> and high-H<sub>T</sub> regions, and are treated separately in the combined fit. The "Others" category contains the single-top, WW, tt̄+X and rare top processes. Combined statistical and systematic uncertainties are presented.
Comparison of the observed data and expected SM background yields in the SRs of the onshell $W\!Z$ selection. The SM prediction is taken from the background-only fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Comparison of the observed data and expected SM background yields in the SRs of the onshell $W\!Z$ selection. The SM prediction is taken from the background-only fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Comparison of the observed data and expected SM background yields in the SRs of the $W\!h$ selection. The SM prediction is taken from the background-only fit. The "Others" category contains the single-top, WW, tt̄+X and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Comparison of the observed data and expected SM background yields in the SRs of the $W\!h$ selection. The SM prediction is taken from the background-only fit. The "Others" category contains the single-top, WW, tt̄+X and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Observed and expected yields after the background-only fit in SR<sup>offWZ</sup><sub>lowETmiss</sub>. The normalization factors of the $W\!Z$ sample extracted separately for 0j and nj, and are treated separately in the combined fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. Combined statistical and systematic uncertainties are presented.
Observed and expected yields after the background-only fit in SR<sup>offWZ</sup><sub>lowETmiss</sub>. The normalization factors of the $W\!Z$ sample extracted separately for 0j and nj, and are treated separately in the combined fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. Combined statistical and systematic uncertainties are presented.
Observed and expected yields after the background-only fit in SR<sup>offWZ</sup><sub>highETmiss</sub>. The normalization factors of the $W\!Z$ sample extracted separately for 0j and nj, and are treated separately in the combined fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. Combined statistical and systematic uncertainties are presented.
Observed and expected yields after the background-only fit in SR<sup>offWZ</sup><sub>highETmiss</sub>. The normalization factors of the $W\!Z$ sample extracted separately for 0j and nj, and are treated separately in the combined fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. Combined statistical and systematic uncertainties are presented.
Comparison of the observed data and expected SM background yields in the SRs of the offshell $W\!Z$ selection. The SM prediction is taken from the background-only fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W^{*}\!Z^{*}$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Comparison of the observed data and expected SM background yields in the SRs of the offshell $W\!Z$ selection. The SM prediction is taken from the background-only fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W^{*}\!Z^{*}$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the onshell $W\!Z$ and $W\!h$ selections. The figure shows (a) the ΔR<sub>OS,near</sub> distribution in SR<sup>Wh</sup><sub>DF</sub>-1, (b) the 3rd leading lepton p<sub>T</sub> in SR<sup>Wh</sup><sub>DF</sub>-2, and the (c) E<sub>T</sub><sup>miss</sup> and (d) m<sub>T</sub> distributions in SR<sup>WZ</sup><sub>0j</sub> (with all SR-i bins of SR<sup>WZ</sup><sub>0j</sub> summed up). The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes, except in the top panels, where triboson and Higgs production contributions are shown separately, and tt̄+X is merged into Others. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$/$W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the onshell $W\!Z$ and $W\!h$ selections. The figure shows (a) the ΔR<sub>OS,near</sub> distribution in SR<sup>Wh</sup><sub>DF</sub>-1, (b) the 3rd leading lepton p<sub>T</sub> in SR<sup>Wh</sup><sub>DF</sub>-2, and the (c) E<sub>T</sub><sup>miss</sup> and (d) m<sub>T</sub> distributions in SR<sup>WZ</sup><sub>0j</sub> (with all SR-i bins of SR<sup>WZ</sup><sub>0j</sub> summed up). The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes, except in the top panels, where triboson and Higgs production contributions are shown separately, and tt̄+X is merged into Others. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$/$W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the onshell $W\!Z$ and $W\!h$ selections. The figure shows (a) the ΔR<sub>OS,near</sub> distribution in SR<sup>Wh</sup><sub>DF</sub>-1, (b) the 3rd leading lepton p<sub>T</sub> in SR<sup>Wh</sup><sub>DF</sub>-2, and the (c) E<sub>T</sub><sup>miss</sup> and (d) m<sub>T</sub> distributions in SR<sup>WZ</sup><sub>0j</sub> (with all SR-i bins of SR<sup>WZ</sup><sub>0j</sub> summed up). The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes, except in the top panels, where triboson and Higgs production contributions are shown separately, and tt̄+X is merged into Others. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$/$W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the onshell $W\!Z$ and $W\!h$ selections. The figure shows (a) the ΔR<sub>OS,near</sub> distribution in SR<sup>Wh</sup><sub>DF</sub>-1, (b) the 3rd leading lepton p<sub>T</sub> in SR<sup>Wh</sup><sub>DF</sub>-2, and the (c) E<sub>T</sub><sup>miss</sup> and (d) m<sub>T</sub> distributions in SR<sup>WZ</sup><sub>0j</sub> (with all SR-i bins of SR<sup>WZ</sup><sub>0j</sub> summed up). The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes, except in the top panels, where triboson and Higgs production contributions are shown separately, and tt̄+X is merged into Others. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$/$W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the onshell $W\!Z$ and $W\!h$ selections. The figure shows (a) the ΔR<sub>OS,near</sub> distribution in SR<sup>Wh</sup><sub>DF</sub>-1, (b) the 3rd leading lepton p<sub>T</sub> in SR<sup>Wh</sup><sub>DF</sub>-2, and the (c) E<sub>T</sub><sup>miss</sup> and (d) m<sub>T</sub> distributions in SR<sup>WZ</sup><sub>0j</sub> (with all SR-i bins of SR<sup>WZ</sup><sub>0j</sub> summed up). The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes, except in the top panels, where triboson and Higgs production contributions are shown separately, and tt̄+X is merged into Others. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$/$W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the onshell $W\!Z$ and $W\!h$ selections. The figure shows (a) the ΔR<sub>OS,near</sub> distribution in SR<sup>Wh</sup><sub>DF</sub>-1, (b) the 3rd leading lepton p<sub>T</sub> in SR<sup>Wh</sup><sub>DF</sub>-2, and the (c) E<sub>T</sub><sup>miss</sup> and (d) m<sub>T</sub> distributions in SR<sup>WZ</sup><sub>0j</sub> (with all SR-i bins of SR<sup>WZ</sup><sub>0j</sub> summed up). The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes, except in the top panels, where triboson and Higgs production contributions are shown separately, and tt̄+X is merged into Others. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$/$W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the onshell $W\!Z$ and $W\!h$ selections. The figure shows (a) the ΔR<sub>OS,near</sub> distribution in SR<sup>Wh</sup><sub>DF</sub>-1, (b) the 3rd leading lepton p<sub>T</sub> in SR<sup>Wh</sup><sub>DF</sub>-2, and the (c) E<sub>T</sub><sup>miss</sup> and (d) m<sub>T</sub> distributions in SR<sup>WZ</sup><sub>0j</sub> (with all SR-i bins of SR<sup>WZ</sup><sub>0j</sub> summed up). The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes, except in the top panels, where triboson and Higgs production contributions are shown separately, and tt̄+X is merged into Others. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$/$W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the onshell $W\!Z$ and $W\!h$ selections. The figure shows (a) the ΔR<sub>OS,near</sub> distribution in SR<sup>Wh</sup><sub>DF</sub>-1, (b) the 3rd leading lepton p<sub>T</sub> in SR<sup>Wh</sup><sub>DF</sub>-2, and the (c) E<sub>T</sub><sup>miss</sup> and (d) m<sub>T</sub> distributions in SR<sup>WZ</sup><sub>0j</sub> (with all SR-i bins of SR<sup>WZ</sup><sub>0j</sub> summed up). The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes, except in the top panels, where triboson and Higgs production contributions are shown separately, and tt̄+X is merged into Others. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$/$W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the offshell $W\!Z$ selection. The figure shows the m<sub>T</sub><sup>m<sub>ll</sub>min</sup> distribution in (a) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj and (c) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and the |p<sub>T</sub><sup>lep</sup>|/E<sub>T</sub><sup>miss</sup> distribution in (d) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj. The contributing m<sub>ll</sub><sup>min</sup> mass bins within each SR<sup>offWZ</sup> category are summed together. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the offshell $W\!Z$ selection. The figure shows the m<sub>T</sub><sup>m<sub>ll</sub>min</sup> distribution in (a) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj and (c) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and the |p<sub>T</sub><sup>lep</sup>|/E<sub>T</sub><sup>miss</sup> distribution in (d) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj. The contributing m<sub>ll</sub><sup>min</sup> mass bins within each SR<sup>offWZ</sup> category are summed together. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the offshell $W\!Z$ selection. The figure shows the m<sub>T</sub><sup>m<sub>ll</sub>min</sup> distribution in (a) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj and (c) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and the |p<sub>T</sub><sup>lep</sup>|/E<sub>T</sub><sup>miss</sup> distribution in (d) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj. The contributing m<sub>ll</sub><sup>min</sup> mass bins within each SR<sup>offWZ</sup> category are summed together. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the offshell $W\!Z$ selection. The figure shows the m<sub>T</sub><sup>m<sub>ll</sub>min</sup> distribution in (a) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj and (c) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and the |p<sub>T</sub><sup>lep</sup>|/E<sub>T</sub><sup>miss</sup> distribution in (d) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj. The contributing m<sub>ll</sub><sup>min</sup> mass bins within each SR<sup>offWZ</sup> category are summed together. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the offshell $W\!Z$ selection. The figure shows the m<sub>T</sub><sup>m<sub>ll</sub>min</sup> distribution in (a) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj and (c) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and the |p<sub>T</sub><sup>lep</sup>|/E<sub>T</sub><sup>miss</sup> distribution in (d) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj. The contributing m<sub>ll</sub><sup>min</sup> mass bins within each SR<sup>offWZ</sup> category are summed together. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the offshell $W\!Z$ selection. The figure shows the m<sub>T</sub><sup>m<sub>ll</sub>min</sup> distribution in (a) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj and (c) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and the |p<sub>T</sub><sup>lep</sup>|/E<sub>T</sub><sup>miss</sup> distribution in (d) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj. The contributing m<sub>ll</sub><sup>min</sup> mass bins within each SR<sup>offWZ</sup> category are summed together. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the offshell $W\!Z$ selection. The figure shows the m<sub>T</sub><sup>m<sub>ll</sub>min</sup> distribution in (a) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj and (c) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and the |p<sub>T</sub><sup>lep</sup>|/E<sub>T</sub><sup>miss</sup> distribution in (d) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj. The contributing m<sub>ll</sub><sup>min</sup> mass bins within each SR<sup>offWZ</sup> category are summed together. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the offshell $W\!Z$ selection. The figure shows the m<sub>T</sub><sup>m<sub>ll</sub>min</sup> distribution in (a) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj and (c) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and the |p<sub>T</sub><sup>lep</sup>|/E<sub>T</sub><sup>miss</sup> distribution in (d) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj. The contributing m<sub>ll</sub><sup>min</sup> mass bins within each SR<sup>offWZ</sup> category are summed together. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Observed (N<sub>obs</sub>) yields after the discovery-fit and expected (N<sub>exp</sub>) after the background-only fit, for the inclusive SRs of the onshell $W\!Z$ and $W\!h$ selections. The third and fourth column list the 95 CL upper limits on the visible cross-section (σ<sub>vis</sub><sup>95</sup>) and on the number of signal events (S<sub>obs</sub><sup>95</sup>). The fifth column (S<sub>exp</sub><sup>95</sup>) shows the 95 CL upper limit on the number of signal events, given the expected number (and ± 1σ excursions on the expectation) of background events. The last two columns indicate the CLb value, i.e. the confidence level observed for the background-only hypothesis, and the discovery p-value (p(s = 0)). If the observed yield is below the expected yield, the p-value is capped at 0.5.
Observed (N<sub>obs</sub>) yields after the discovery-fit and expected (N<sub>exp</sub>) after the background-only fit, for the inclusive SRs of the onshell $W\!Z$ and $W\!h$ selections. The third and fourth column list the 95 CL upper limits on the visible cross-section (σ<sub>vis</sub><sup>95</sup>) and on the number of signal events (S<sub>obs</sub><sup>95</sup>). The fifth column (S<sub>exp</sub><sup>95</sup>) shows the 95 CL upper limit on the number of signal events, given the expected number (and ± 1σ excursions on the expectation) of background events. The last two columns indicate the CLb value, i.e. the confidence level observed for the background-only hypothesis, and the discovery p-value (p(s = 0)). If the observed yield is below the expected yield, the p-value is capped at 0.5.
Observed (N<sub>obs</sub>) yields after the discovery-fit and expected (N<sub>exp</sub>) after the background-only fit, for the inclusive SRs of the offshell $W\!Z$ selection. The third and fourth column list the 95 CL upper limits on the visible cross section (σ<sub>vis</sub><sup>95</sup>) and on the number of signal events (S<sub>obs</sub><sup>95</sup>). The fifth column (S<sub>exp</sub><sup>95</sup>) shows the 95 CL upper limit on the number of signal events, given the expected number (and ± 1σ excursions on the expectation) of background events. The last two columns indicate the CLb value, i.e. the confidence level observed for the background-only hypothesis, and the discovery p-value (p(s = 0)). If the observed yield is below the expected yield, the p-value is capped at 0.5.
Observed (N<sub>obs</sub>) yields after the discovery-fit and expected (N<sub>exp</sub>) after the background-only fit, for the inclusive SRs of the offshell $W\!Z$ selection. The third and fourth column list the 95 CL upper limits on the visible cross section (σ<sub>vis</sub><sup>95</sup>) and on the number of signal events (S<sub>obs</sub><sup>95</sup>). The fifth column (S<sub>exp</sub><sup>95</sup>) shows the 95 CL upper limit on the number of signal events, given the expected number (and ± 1σ excursions on the expectation) of background events. The last two columns indicate the CLb value, i.e. the confidence level observed for the background-only hypothesis, and the discovery p-value (p(s = 0)). If the observed yield is below the expected yield, the p-value is capped at 0.5.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Comparison of the observed data and expected SM background yields in the CRs and VRs of the RJR selection. The SM prediction is taken from the background-only fit. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Comparison of the observed data and expected SM background yields in the CRs and VRs of the RJR selection. The SM prediction is taken from the background-only fit. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Observed and expected yields after the background-only fit in the SRs for the RJR selection. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Combined statistical and systematic uncertainties are presented.
Observed and expected yields after the background-only fit in the SRs for the RJR selection. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Combined statistical and systematic uncertainties are presented.
Example of kinematic distributions after the background-only fit, showing the data and the post-fit expected background, in regions of the RJR selection. The figure shows the (a) p<sub>T</sub><sup>ℓ<sub>1</sub></sup> and (b) H<sup>PP</sup><sub>3,1</sub> distributions in SR3ℓ-Low, and the (c) p<sup>CM</sup><sub>T ISR</sub> and (d) R<sub>ISR</sub> distributions in SR3ℓ-ISR. The last bin includes overflow. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Example of kinematic distributions after the background-only fit, showing the data and the post-fit expected background, in regions of the RJR selection. The figure shows the (a) p<sub>T</sub><sup>ℓ<sub>1</sub></sup> and (b) H<sup>PP</sup><sub>3,1</sub> distributions in SR3ℓ-Low, and the (c) p<sup>CM</sup><sub>T ISR</sub> and (d) R<sub>ISR</sub> distributions in SR3ℓ-ISR. The last bin includes overflow. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Example of kinematic distributions after the background-only fit, showing the data and the post-fit expected background, in regions of the RJR selection. The figure shows the (a) p<sub>T</sub><sup>ℓ<sub>1</sub></sup> and (b) H<sup>PP</sup><sub>3,1</sub> distributions in SR3ℓ-Low, and the (c) p<sup>CM</sup><sub>T ISR</sub> and (d) R<sub>ISR</sub> distributions in SR3ℓ-ISR. The last bin includes overflow. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Example of kinematic distributions after the background-only fit, showing the data and the post-fit expected background, in regions of the RJR selection. The figure shows the (a) p<sub>T</sub><sup>ℓ<sub>1</sub></sup> and (b) H<sup>PP</sup><sub>3,1</sub> distributions in SR3ℓ-Low, and the (c) p<sup>CM</sup><sub>T ISR</sub> and (d) R<sub>ISR</sub> distributions in SR3ℓ-ISR. The last bin includes overflow. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Example of kinematic distributions after the background-only fit, showing the data and the post-fit expected background, in regions of the RJR selection. The figure shows the (a) p<sub>T</sub><sup>ℓ<sub>1</sub></sup> and (b) H<sup>PP</sup><sub>3,1</sub> distributions in SR3ℓ-Low, and the (c) p<sup>CM</sup><sub>T ISR</sub> and (d) R<sub>ISR</sub> distributions in SR3ℓ-ISR. The last bin includes overflow. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Example of kinematic distributions after the background-only fit, showing the data and the post-fit expected background, in regions of the RJR selection. The figure shows the (a) p<sub>T</sub><sup>ℓ<sub>1</sub></sup> and (b) H<sup>PP</sup><sub>3,1</sub> distributions in SR3ℓ-Low, and the (c) p<sup>CM</sup><sub>T ISR</sub> and (d) R<sub>ISR</sub> distributions in SR3ℓ-ISR. The last bin includes overflow. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Example of kinematic distributions after the background-only fit, showing the data and the post-fit expected background, in regions of the RJR selection. The figure shows the (a) p<sub>T</sub><sup>ℓ<sub>1</sub></sup> and (b) H<sup>PP</sup><sub>3,1</sub> distributions in SR3ℓ-Low, and the (c) p<sup>CM</sup><sub>T ISR</sub> and (d) R<sub>ISR</sub> distributions in SR3ℓ-ISR. The last bin includes overflow. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Example of kinematic distributions after the background-only fit, showing the data and the post-fit expected background, in regions of the RJR selection. The figure shows the (a) p<sub>T</sub><sup>ℓ<sub>1</sub></sup> and (b) H<sup>PP</sup><sub>3,1</sub> distributions in SR3ℓ-Low, and the (c) p<sup>CM</sup><sub>T ISR</sub> and (d) R<sub>ISR</sub> distributions in SR3ℓ-ISR. The last bin includes overflow. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
{Results of the discovery-fit for the SRs of the RJR selection, calculated using pseudo-experiments.} The first and second column list the 95 CL upper limits on the visible cross section (σ<sub>vis</sub><sup>95</sup>) and on the number of signal events (S<sub>obs</sub><sup>95</sup>). The third column (S<sub>exp</sub><sup>95</sup>) shows the 95 CL upper limit on the number of signal events, given the expected number (and ± 1σ excursions on the expectation) of background events. The last two columns indicate the CLb value, i.e. the confidence level observed for the background-only hypothesis, and the discovery p-value (p(s = 0)). If the observed yield is below the expected yield, the p-value is capped at 0.5. vspace{0.5em}
{Results of the discovery-fit for the SRs of the RJR selection, calculated using pseudo-experiments.} The first and second column list the 95 CL upper limits on the visible cross section (σ<sub>vis</sub><sup>95</sup>) and on the number of signal events (S<sub>obs</sub><sup>95</sup>). The third column (S<sub>exp</sub><sup>95</sup>) shows the 95 CL upper limit on the number of signal events, given the expected number (and ± 1σ excursions on the expectation) of background events. The last two columns indicate the CLb value, i.e. the confidence level observed for the background-only hypothesis, and the discovery p-value (p(s = 0)). If the observed yield is below the expected yield, the p-value is capped at 0.5. vspace{0.5em}
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!h$-mediated model, for the wino/bino (+) scenario, as in Figure 17. The black numbers represent the observed (a,c,e,g) and expected (b,d,f,h) upper cross-section limits.
Exclusion limits obtained for the $W\!h$-mediated model, for the wino/bino (+) scenario, as in Figure 17. The black numbers represent the observed (a,c,e,g) and expected (b,d,f,h) upper cross-section limits.
Exclusion limits obtained for the $W\!h$-mediated model, for the wino/bino (+) scenario, as in Figure 17. The black numbers represent the observed (a,c,e,g) and expected (b,d,f,h) upper cross-section limits.
Exclusion limits obtained for the $W\!h$-mediated model, for the wino/bino (+) scenario, as in Figure 17. The black numbers represent the observed (a,c,e,g) and expected (b,d,f,h) upper cross-section limits.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c) truth-level acceptances and (b,d) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>WZ</sup><sub>0j</sub>, (c,d) SR<sup>WZ</sup><sub>nj</sub> regions of the onshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c) truth-level acceptances and (b,d) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>WZ</sup><sub>0j</sub>, (c,d) SR<sup>WZ</sup><sub>nj</sub> regions of the onshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c) truth-level acceptances and (b,d) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>WZ</sup><sub>0j</sub>, (c,d) SR<sup>WZ</sup><sub>nj</sub> regions of the onshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c) truth-level acceptances and (b,d) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>WZ</sup><sub>0j</sub>, (c,d) SR<sup>WZ</sup><sub>nj</sub> regions of the onshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c) truth-level acceptances and (b,d) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>WZ</sup><sub>0j</sub>, (c,d) SR<sup>WZ</sup><sub>nj</sub> regions of the onshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c) truth-level acceptances and (b,d) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>WZ</sup><sub>0j</sub>, (c,d) SR<sup>WZ</sup><sub>nj</sub> regions of the onshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c) truth-level acceptances and (b,d) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>WZ</sup><sub>0j</sub>, (c,d) SR<sup>WZ</sup><sub>nj</sub> regions of the onshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c) truth-level acceptances and (b,d) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>WZ</sup><sub>0j</sub>, (c,d) SR<sup>WZ</sup><sub>nj</sub> regions of the onshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
Summary of onshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (300,200) GeV and m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (600,100) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal points, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks per inclusive regions, and then further for each SR. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5.
Summary of onshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (300,200) GeV and m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (600,100) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal points, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks per inclusive regions, and then further for each SR. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5.
Summary of $W\!h$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (190,60) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks per inclusive regions, and then further for each SR. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5.
Summary of $W\!h$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (190,60) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks per inclusive regions, and then further for each SR. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (250,235) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (250,235) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (125,85) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (125,85) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (250,170) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (250,170) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (250,235) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (-) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (250,235) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (-) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (125,85) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (-) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (125,85) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (-) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (250,170) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (-) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (250,170) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (-) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (120,100) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the higgsino interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (120,100) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the higgsino interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (100,40) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the higgsino interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (100,40) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the higgsino interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (185,125) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the higgsino interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (185,125) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the higgsino interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
A search for a charged Higgs boson, $H^{\pm}$, produced in top-quark decays, $t \rightarrow H^{\pm}b$, is presented. The search targets $H^{\pm}$ decays into a bottom and a charm quark, $H^{\pm} \rightarrow cb$. The analysis focuses on a selection enriched in top-quark pair production, where one top quark decays into a leptonically decaying $W$ boson and a bottom quark, and the other top quark decays into a charged Higgs boson and a bottom quark. This topology leads to a lepton-plus-jets final state, characterised by an isolated electron or muon and at least four jets. The search exploits the high multiplicity of jets containing $b$-hadrons, and deploys a neural network classifier that uses the kinematic differences between the signal and the background. The search uses a dataset of proton-proton collisions collected at a centre-of-mass energy $\sqrt{s}=13$ TeV between 2015 and 2018 with the ATLAS detector at CERN's Large Hadron Collider, amounting to an integrated luminosity of 139 fb$^{-1}$. Observed (expected) 95% confidence-level upper limits between 0.15% (0.09%) and 0.42% (0.25%) are derived for the product of branching fractions $\mathscr{B}(t\rightarrow H^{\pm}b) \times \mathscr{B}(H^{\pm}\rightarrow cb)$ for charged Higgs boson masses between 60 and 160 GeV, assuming the SM production of the top-quark pairs.
The observed 95% CL upper limits on $\mathscr{B}=\mathscr{B}(t\rightarrow H^{\pm}b) \times \mathscr{B}(H^{\pm}\rightarrow cb)$ as a function of $m_{H^{\pm}}$ and the expectation (dashed) under the background-only hypothesis. The inner green and outer yellow shaded bands show the $\pm 1\sigma$ and $\pm 2\sigma$ uncertainties of the expected limits. The exclusion limits are presented for $m_{H^{\pm}}$ between 60 and 160 GeV with 10 GeV $m_{H^{\pm}}$ spacing and linear interpolation between adjacent mass points. Superimposed on the upper limits, the predictions from the 3HDM are shown, corresponding to three benchmark values for the parameters $X$, $Y$, and $Z$
Pre-fit event yields in each of the nine analysis regions. The $H^{\pm}$ signal yields for $m_{H^{\pm}}=130$ GeV and $m_{H^{\pm}}=70$ GeV are normalised to $\mathscr{B}_{\mathrm{ref}}=1\%$. The quoted uncertainties are the sum in quadrature of statistical and systematic uncertainties of the yields, computed taking into account correlations among processes resulting from the data-based $t\bar{t}$ correction procedure.
Post-fit yields in each of the nine analysis regions considered. The total prediction is shown after the fit to data under the signal-plus-background hypothesis assuming $H^{\pm}$ signal with $m_{H^{\pm}}=130$ GeV. The predicted yileds for the $H^{\pm}$ signal with $m_{H^{\pm}}=70$ GeV are also shown for reference. The best fit-values of $\mathscr{B}$ for $H^{\pm}$ signal with $m_{H^{\pm}}=130$ GeV and $m_{H^{\pm}}=70$ GeV are 0.16% and 0.07% respectively. The quoted uncertainties are the sum in quadrature of statistical and systematic uncertainties of the yields, computed taking into account correlations among nuisance parameters and among processes.
Signal selection efficiency ($\epsilon$) times acceptance ($A$) as a function of $H^{\pm}$. The estimated $\epsilon\times A$ arises from the lepton selection and triggering (∼30%) as well as jet selection and flavour tagging (∼10% or lower). The decrease of $\epsilon\times A$ for $m_{H^{\pm}}$ = 120 GeV and higher is expected from the kinematic constraint on the $H^{\pm}$ decay products due to the top-quark mass.
A search for flavour-changing neutral-current decays of a top quark into an up-type quark (either up or charm) and a light scalar particle $X$ decaying into a bottom anti-bottom quark pair is presented. The search focuses on top-quark pair production where one top quark decays to $qX$, with $X \rightarrow b\bar{b}$, and the other top quark decays according to the Standard Model, with the $W$ boson decaying leptonically. The final state is thus characterised by an isolated electron or muon and at least four jets. Events are categorised according to the multiplicity of jets and jets tagged as originating from $b$-quarks, and a neural network is used to discriminate between signal and background processes. The data analysed correspond to 139 fb$^{-1}$ of proton-proton collisions at a centre-of-mass energy of 13 TeV, recorded with the ATLAS detector at the LHC. The 95% confidence-level upper limits between 0.019% and 0.062% are derived for the branching fraction $\mathcal{B}$($t \rightarrow uX$) and between 0.018% and 0.078% for the branching fraction $\mathcal{B}$($t \rightarrow cX$), for masses of the scalar particle $X$ between 20 and 160 GeV.
Expected and observed 95% CL upper limits for $\mathcal{B}$($t \rightarrow uX$) $\times$ $\mathcal{B}$($X \rightarrow b\bar{b}$). The bands surrounding the expected limits show the 68% and 95% confidence intervals, respectively.
Expected and observed 95% CL upper limits for $\mathcal{B}$($t \rightarrow cX$) $\times$ $\mathcal{B}$($X \rightarrow b\bar{b}$). The bands surrounding the expected limits show the 68% and 95% confidence intervals, respectively.
Expected and observed 95% CL upper limits for $\mathcal{B}$($t \rightarrow uH$) $\times$ $\mathcal{B}$($X \rightarrow b\bar{b}$) and $\mathcal{B}$($t \rightarrow cH$) $\times$ $\mathcal{B}$($X \rightarrow b\bar{b}$).
Event yields of the signal and SM background processes in the six analysis regions after the fit to the data under the $t \rightarrow uX$ hypothesis assuming $m_X = 30$ GeV. Total includes signal and background.The quoted uncertainties take into account correlations and constraints of the nuisance parameters and include both the statistical and systematic uncertainties. Negative correlations between the $t\bar{t} +$ light, $t\bar{t} + \geq1b$ and $t\bar{t} + \geq1c$ modelling uncertainties can make the uncertainty in the total yields smaller than in the individual components.
Event yields of the signal and SM background processes in the six analysis regions after the fit to the data under the $t \rightarrow cX$ hypothesis assuming $m_X = 30$ GeV. Total includes signal and background.The quoted uncertainties take into account correlations and constraints of the nuisance parameters and include both the statistical and systematic uncertainties. Negative correlations between the $t\bar{t} +$ light, $t\bar{t} + \geq1b$ and $t\bar{t} + \geq1c$ modelling uncertainties can make the uncertainty in the total yields smaller than in the individual components.
Event acceptance times efficiency in percent for every $t\rightarrow uX$ and $t\rightarrow cX$ mass signal sample.
Cut flow for the scalar signal in the $t\rightarrow uX$ decay combining both quark and anti-quark samples. Shown for each signal are the corresponding mass, the number of generated events, the number of reconstructed ("Reco") events, the events that pass the lepton triggers, the events that have only one electron ("el") or only one muon ("mu") with p$_{\text{T}}$ larger than 27 GeV, the number of events with at least four jets with p$_{\text{T}}$ larger than 25 GeV, the number of events with at least three $b$-tagged jets at the 70% efficiency working point, and the number of events with at least two $b$-tagged jets at the 60% efficiency working point and at least another one at the 70%. The quoted yields do not include reweighting.
Cut flow for the scalar signal in the $t\rightarrow cX$ decay combining both quark and anti-quark samples. Shown for each signal are the corresponding mass, the number of generated events, the number of reconstructed ("Reco") events, the events that pass the lepton triggers, the events that have only one electron ("el") or only one muon ("mu") with p$_{\text{T}}$ larger than 27 GeV, the number of events with at least four jets with p$_{\text{T}}$ larger than 25 GeV, the number of events with at least three $b$-tagged jets at the 70% efficiency working point, and the number of events with at least two $b$-tagged jets at the 60% efficiency working point and at least another one at the 70%. The quoted yields do not include reweighting.
A search for pair production of doubly charged Higgs bosons ($H^{\pm \pm}$), each decaying into a pair of prompt, isolated, highly energetic leptons with the same electric charge, is presented. The search uses a proton-proton collision data sample at a centre-of-mass energy of 13 TeV corresponding to an integrated luminosity of 139 fb$^{-1}$ recorded by the ATLAS detector during Run 2 of the Large Hadron Collider. This analysis focuses on same-charge leptonic decays, $H^{\pm \pm} \rightarrow \ell^{\pm} \ell^{\prime \pm}$ where $\ell, \ell^\prime=e, \mu, \tau$, in two-, three-, and four-lepton channels, but only considers final states which include electrons or muons. No evidence of a signal is observed. Corresponding limits on the production cross-section and consequently a lower limit on $m(H^{\pm \pm})$ are derived at 95% confidence level. Assuming that the branching ratios to each of the possible leptonic final states are equal, $\mathcal{B}(H^{\pm \pm} \rightarrow e^\pm e^\pm) = \mathcal{B}(H^{\pm \pm} \rightarrow e^\pm \mu^\pm) = \mathcal{B}(H^{\pm \pm} \rightarrow \mu^\pm \mu^\pm) = \mathcal{B}(H^{\pm \pm} \rightarrow e^\pm \tau^\pm) = \mathcal{B}(H^{\pm \pm} \rightarrow \mu^\pm \tau^\pm) = \mathcal{B}(H^{\pm \pm} \rightarrow \tau^\pm \tau^\pm) = 1/6$, the observed lower limit on the mass of a doubly charged Higgs boson is 1080 GeV within the left-right symmetric type-II seesaw model, which is an improvement over previous limits. Additionally, a lower limit of $m(H^{\pm \pm})$ = 900 GeV is obtained in the context of the Zee-Babu neutrino mass model.
LO, NLO cross-sections and K-factors for the pair-production of doubly charged Higgs bosons in pp collisions at $\sqrt{s}$ = 13 TeV. The K-factors (K=$\sigma_{NLO}/\sigma_{LO}$) are identical for $H^{\pm\pm}_L$, $H^{\pm\pm}_R$, and $k^{\pm\pm}$. The values are calculated using the NNPDF3.1NLO and NNPDF2.3LO PDF sets.
Observed (solid line) and expected (dashed line) 95% CL upper limits on the $H^{\pm\pm}$ pair production cross-section as a function of $m(H^{\pm\pm})$ resulting from the combination of all analysis channels, assuming $\sum_{\ell \ell^\prime} \mathcal{B}(H^{\pm\pm} \rightarrow \ell^{\pm} \ell^{\prime \pm})=100%$, where $\ell, \ell^\prime = e, \mu, \tau$.
Distribution of $m(e^{\pm},e^{\pm})_{\mathrm{lead}}$ in the electron-electron signal region after the background-only fit.
Distribution of $m(e^{\pm},\mu^{\pm})_{\mathrm{lead}}$ in the electron-muon signal region after the background-only fit.
Distribution of $m(\mu^{\pm},\mu^{\pm})_{\mathrm{lead}}$ in the muon-muon signal region after the background-only fit.
Distribution of $m(\ell^{\pm},\ell^{\prime \pm})_{\mathrm{lead}}$ in the three-lepton signal region after the background-only fit.
Event yield in the four-lepton signal region after the background-only fit.
Two-lepton signal region weighted cutflows for electron-electron channel. Data and a few representative signal samples are presented alongside the main background contributions. Yield stands for the observed yield in data and the expected yields based on $\sigma \cdot \mathcal{L}$ for the signal and background samples. Top quark and multiboson process backgrounds are merged under the 'other' category.
Two-lepton signal region weighted cutflows for electron-muon channel. Data and a few representative signal samples are presented alongside the main background contributions. Yield stands for the observed yield in data and the expected yields based on $\sigma \cdot \mathcal{L}$ for the signal and background samples. Top quark and multiboson process backgrounds are merged under the 'other' category.
Two-lepton signal region weighted cutflows for muon-muon channel. Data and a few representative signal samples are presented alongside the main background contributions. Yield stands for the observed yield in data and the expected yields based on $\sigma \cdot \mathcal{L}$ for the signal and background samples. Top quark and multiboson process backgrounds are merged under the 'other' category.
Three-lepton signal region weighted cutflow for $\ell \ell \ell$ channel. Data and a few representative signal samples are presented alongside the main background contributions. Yield stands for the observed yield in data and the expected yields based on $\sigma \cdot \mathcal{L}$ for the signal and background samples. Top quark and multiboson process backgrounds are merged under the 'other' category.
Four-lepton signal region weighted cutflow for $\ell \ell \ell \ell$ channel. Data and a few representative signal samples are presented alongside the main background contributions. Yield stands for the observed yield in data and the expected yields based on $\sigma \cdot \mathcal{L}$ for the signal and background samples. Top quark, Drell-Yan, and multiboson process backgrounds are merged under the 'other' category.
This paper reports a search for Higgs boson pair ($hh$) production in association with a vector boson ($W$ or $Z$) using 139 $fb^{-1}$ of proton-proton collision data at $\sqrt{s}=$ 13 TeV recorded with the ATLAS detector at the Large Hadron Collider. The search is performed in final states in which the vector boson decays leptonically ($W\to\ell\nu, Z\to\ell\ell,\nu\nu$ with $\ell=e, \mu$) and the Higgs bosons each decay into a pair of $b$-quarks. It targets $Vhh$ signals from both non-resonant $hh$ production, present in the Standard Model (SM), and resonant $hh$ production, as predicted in some SM extensions. A 95% confidence-level upper limit of 183 (87) times the SM cross-section is observed (expected) for non-resonant $Vhh$ production when assuming the kinematics are as expected in the SM. Constraints are also placed on Higgs boson coupling modifiers. For the resonant search, upper limits on the production cross-sections are derived for two specific models: one is the production of a vector boson along with a neutral heavy scalar resonance $H$, in the mass range 260-1000 GeV, that decays into $hh$, and the other is the production of a heavier neutral pseudoscalar resonance $A$ that decays into a $Z$ boson and $H$ boson, where the $A$ boson mass is 360-800 GeV and the $H$ boson mass is 260-400 GeV. Constraints are also derived in the parameter space of two-Higgs-doublet models.
Acceptance times efficiency as a function of resonant mass for each event selection step in the search for a neutral heavy scalar resonance produced in association with a Z boson decaying to neutrinos.
Acceptance times efficiency as a function of resonant mass for each event selection step in the search for a neutral heavy scalar resonance produced in association with a Z boson decaying to neutrinos.
Acceptance times efficiency as a function of resonant mass for each event selection step in the search for a neutral heavy scalar resonance produced in association with a W boson decaying to a charged lepton and a neutrino.
Acceptance times efficiency as a function of resonant mass for each event selection step in the search for a neutral heavy scalar resonance produced in association with a W boson decaying to a charged lepton and a neutrino.
Acceptance times efficiency as a function of resonant mass for each event selection step in the search for a neutral heavy scalar resonance produced in association with a Z boson decaying to charged leptons.
Acceptance times efficiency as a function of resonant mass for each event selection step in the search for a neutral heavy scalar resonance produced in association with a Z boson decaying to charged leptons.
Acceptance times efficiency as a function of pseudoscalar resonant mass for each event selection step in the search for a neutral heavy narrow-width pseudoscalar resonance that decays to a 260 GeV scalar resonance and a Z boson, which decays to neutrinos.
Acceptance times efficiency as a function of pseudoscalar resonant mass for each event selection step in the search for a neutral heavy narrow-width pseudoscalar resonance that decays to a 260 GeV scalar resonance and a Z boson, which decays to neutrinos.
Acceptance times efficiency as a function of pseudoscalar resonant mass for each event selection step in the search for a neutral heavy narrow-width pseudoscalar resonance that decays to a 300 GeV scalar resonance and a Z boson, which decays to neutrinos.
Acceptance times efficiency as a function of pseudoscalar resonant mass for each event selection step in the search for a neutral heavy narrow-width pseudoscalar resonance that decays to a 300 GeV scalar resonance and a Z boson, which decays to neutrinos.
Acceptance times efficiency as a function of pseudoscalar resonant mass for each event selection step in the search for a neutral heavy narrow-width pseudoscalar resonance that decays to a 400 GeV scalar resonance and a Z boson, which decays to neutrinos.
Acceptance times efficiency as a function of pseudoscalar resonant mass for each event selection step in the search for a neutral heavy narrow-width pseudoscalar resonance that decays to a 400 GeV scalar resonance and a Z boson, which decays to neutrinos.
Acceptance times efficiency as a function of pseudoscalar resonant mass for each event selection step in the search for a neutral heavy large-width pseudoscalar resonance that decays to a 260 GeV scalar resonance and a Z boson, which decays to neutrinos.
Acceptance times efficiency as a function of pseudoscalar resonant mass for each event selection step in the search for a neutral heavy large-width pseudoscalar resonance that decays to a 260 GeV scalar resonance and a Z boson, which decays to neutrinos.
Acceptance times efficiency as a function of pseudoscalar resonant mass for each event selection step in the search for a neutral heavy large-width pseudoscalar resonance that decays to a 300 GeV scalar resonance and a Z boson, which decays to neutrinos.
Acceptance times efficiency as a function of pseudoscalar resonant mass for each event selection step in the search for a neutral heavy large-width pseudoscalar resonance that decays to a 300 GeV scalar resonance and a Z boson, which decays to neutrinos.
Acceptance times efficiency as a function of pseudoscalar resonant mass for each event selection step in the search for a neutral heavy large-width pseudoscalar resonance that decays to a 400 GeV scalar resonance and a Z boson, which decays to neutrinos.
Acceptance times efficiency as a function of pseudoscalar resonant mass for each event selection step in the search for a neutral heavy large-width pseudoscalar resonance that decays to a 400 GeV scalar resonance and a Z boson, which decays to neutrinos.
Acceptance times efficiency as a function of pseudoscalar resonant mass for each event selection step in the search for a neutral heavy narrow-width pseudoscalar resonance that decays to a 260 GeV scalar resonance and a Z boson, which decays to charged leptons.
Acceptance times efficiency as a function of pseudoscalar resonant mass for each event selection step in the search for a neutral heavy narrow-width pseudoscalar resonance that decays to a 260 GeV scalar resonance and a Z boson, which decays to charged leptons.
Acceptance times efficiency as a function of pseudoscalar resonant mass for each event selection step in the search for a neutral heavy narrow-width pseudoscalar resonance that decays to a 300 GeV scalar resonance and a Z boson, which decays to charged leptons.
Acceptance times efficiency as a function of pseudoscalar resonant mass for each event selection step in the search for a neutral heavy narrow-width pseudoscalar resonance that decays to a 300 GeV scalar resonance and a Z boson, which decays to charged leptons.
Acceptance times efficiency as a function of pseudoscalar resonant mass for each event selection step in the search for a neutral heavy narrow-width pseudoscalar resonance that decays to a 400 GeV scalar resonance and a Z boson, which decays to charged leptons.
Acceptance times efficiency as a function of pseudoscalar resonant mass for each event selection step in the search for a neutral heavy narrow-width pseudoscalar resonance that decays to a 400 GeV scalar resonance and a Z boson, which decays to charged leptons.
Acceptance times efficiency as a function of pseudoscalar resonant mass for each event selection step in the search for a neutral heavy large-width pseudoscalar resonance that decays to a 260 GeV scalar resonance and a Z boson, which decays to charged leptons.
Acceptance times efficiency as a function of pseudoscalar resonant mass for each event selection step in the search for a neutral heavy large-width pseudoscalar resonance that decays to a 260 GeV scalar resonance and a Z boson, which decays to charged leptons.
Acceptance times efficiency as a function of pseudoscalar resonant mass for each event selection step in the search for a neutral heavy large-width pseudoscalar resonance that decays to a 300 GeV scalar resonance and a Z boson, which decays to charged leptons.
Acceptance times efficiency as a function of pseudoscalar resonant mass for each event selection step in the search for a neutral heavy large-width pseudoscalar resonance that decays to a 300 GeV scalar resonance and a Z boson, which decays to charged leptons.
Acceptance times efficiency as a function of pseudoscalar resonant mass for each event selection step in the search for a neutral heavy large-width pseudoscalar resonance that decays to a 400 GeV scalar resonance and a Z boson, which decays to charged leptons.
Acceptance times efficiency as a function of pseudoscalar resonant mass for each event selection step in the search for a neutral heavy large-width pseudoscalar resonance that decays to a 400 GeV scalar resonance and a Z boson, which decays to charged leptons.
Expected and observed 95% CL upper limits on the cross-section of resonant $H\to 4b$ production in association with a W boson. The $\pm 1 \sigma$ and $\pm 2 \sigma$ uncertainty ranges for the expected limits are shown.
Expected and observed 95% CL upper limits on the cross-section of resonant $H\to 4b$ production in association with a W boson. The $\pm 1 \sigma$ and $\pm 2 \sigma$ uncertainty ranges for the expected limits are shown.
Expected and observed 95% CL upper limits on the cross-section of resonant $H\to 4b$ production in association with a Z boson. The $\pm 1 \sigma$ and $\pm 2 \sigma$ uncertainty ranges for the expected limits are shown.
Expected and observed 95% CL upper limits on the cross-section of resonant $H\to 4b$ production in association with a Z boson. The $\pm 1 \sigma$ and $\pm 2 \sigma$ uncertainty ranges for the expected limits are shown.
Expected 95% CL upper limits on the cross-section of a heavy narrow-width pseudoscalar resonance decaying to a Z boson and a heavy scalar resonance decaying to $H\to 4b$. The $\pm 1 \sigma$ and $\pm 2 \sigma$ uncertainty ranges for the expected limits are shown.
Expected 95% CL upper limits on the cross-section of a heavy narrow-width pseudoscalar resonance decaying to a Z boson and a heavy scalar resonance decaying to $H\to 4b$. The $\pm 1 \sigma$ and $\pm 2 \sigma$ uncertainty ranges for the expected limits are shown.
Observed 95% CL upper limits on the cross-section of a heavy narrow-width pseudoscalar resonance decaying to a Z boson and a heavy scalar resonance decaying to $H\to 4b$. The $\pm 1 \sigma$ and $\pm 2 \sigma$ uncertainty ranges for the expected limits are shown.
Observed 95% CL upper limits on the cross-section of a heavy narrow-width pseudoscalar resonance decaying to a Z boson and a heavy scalar resonance decaying to $H\to 4b$. The $\pm 1 \sigma$ and $\pm 2 \sigma$ uncertainty ranges for the expected limits are shown.
Expected 95% CL upper limits on the cross-section of a heavy large-width pseudoscalar resonance decaying to a Z boson and a heavy scalar resonance decaying to $H\to 4b$. The $\pm 1 \sigma$ and $\pm 2 \sigma$ uncertainty ranges for the expected limits are shown.
Expected 95% CL upper limits on the cross-section of a heavy large-width pseudoscalar resonance decaying to a Z boson and a heavy scalar resonance decaying to $H\to 4b$. The $\pm 1 \sigma$ and $\pm 2 \sigma$ uncertainty ranges for the expected limits are shown.
Expected 95% CL upper limits on the cross-section of a heavy large-width pseudoscalar resonance decaying to a Z boson and a heavy scalar resonance decaying to $H\to 4b$. The $\pm 1 \sigma$ and $\pm 2 \sigma$ uncertainty ranges for the expected limits are shown.
Observed 95% CL upper limits on the cross-section of a heavy large-width pseudoscalar resonance decaying to a Z boson and a heavy scalar resonance decaying to $H\to 4b$. The $\pm 1 \sigma$ and $\pm 2 \sigma$ uncertainty ranges for the expected limits are shown.
Data and post-fit signal and background from S+B fit for 315 GeV resonant $H\to 4b$ production in association with a W boson.
Data and post-fit signal and background from S+B fit for 315 GeV resonant $H\to 4b$ production in association with a W boson.
Data and post-fit signal and background from S+B fit for 400 GeV resonant $H\to 4b$ production in association with a W boson.
Data and post-fit signal and background from S+B fit for 400 GeV resonant $H\to 4b$ production in association with a W boson.
Data and post-fit signal and background from S+B fit for 550 GeV resonant $H\to 4b$ production in association with a Z boson.
Data and post-fit signal and background from S+B fit for 550 GeV resonant $H\to 4b$ production in association with a Z boson.
Data and post-fit signal and background from S+B fit for 400 GeV resonant $H\to 4b$ production in association with a Z boson.
Data and post-fit signal and background from S+B fit for 400 GeV resonant $H\to 4b$ production in association with a Z boson.
Data and post-fit signal and background from S+B fit for a 790 GeV narrow-width pseudoscalar resonance decaying to a Z boson and a 300 GeV scalar resonance decaying to $H\to 4b$.
Data and post-fit signal and background from S+B fit for a 790 GeV narrow-width pseudoscalar resonance decaying to a Z boson and a 300 GeV scalar resonance decaying to $H\to 4b$.
Data and post-fit signal and background from S+B fit for a 420 GeV large-width pseudoscalar resonance decaying to a Z boson and a 320 GeV scalar resonance decaying to $H\to 4b$.
Data and post-fit signal and background from S+B fit for a 420 GeV large-width pseudoscalar resonance decaying to a Z boson and a 320 GeV scalar resonance decaying to $H\to 4b$.
Data and post-fit signal and background from S+B fit for a 700 GeV large-width pseudoscalar resonance decaying to a Z boson and a 380 GeV scalar resonance decaying to $H\to 4b$.
Data and post-fit signal and background from S+B fit for a 700 GeV large-width pseudoscalar resonance decaying to a Z boson and a 380 GeV scalar resonance decaying to $H\to 4b$.
Data and post-fit signal and background from S+B fit for SM VHH production, with each Higgs boson decaying to $2b$.
Data and post-fit signal and background from S+B fit for SM VHH production, with each Higgs boson decaying to $2b$.
A search for flavour-changing neutral current (FCNC) $tqH$ interactions involving a top quark, another up-type quark ($q=u$, $c$), and a Standard Model (SM) Higgs boson decaying into a $\tau$-lepton pair ($H\rightarrow \tau^+\tau^-$) is presented. The search is based on a dataset of $pp$ collisions at $\sqrt{s}=13$ TeV that corresponds to an integrated luminosity of 139 fb$^{-1}$ recorded with the ATLAS detector at the Large Hadron Collider. Two processes are considered: single top quark FCNC production in association with a Higgs boson ($pp\rightarrow tH$), and top quark pair production in which one of the top quarks decays into $Wb$ and the other decays into $qH$ through the FCNC interactions. The search selects events with two hadronically decaying $\tau$-lepton candidates ($\tau_{\text{had}}$) or at least one $\tau_{\text{had}}$ with an additional lepton ($e$, $\mu$), as well as multiple jets. Event kinematics is used to separate signal from the background through a multivariate discriminant. A slight excess of data is observed with a significance of 2.3$\sigma$ above the expected SM background, and 95% CL upper limits on the $t\to qH$ branching ratios are derived. The observed (expected) 95% CL upper limits set on the $t\to cH$ and $t\to uH$ branching ratios are $9.4 \times 10^{-4}$ $(4.8^{+2.2}_{-1.4}\times 10^{-4})$ and $6.9\times 10^{-4}$ $(3.5^{+1.5}_{-1.0}\times 10^{-4})$, respectively. The corresponding combined observed (expected) upper limits on the dimension-6 operator Wilson coefficients in the effective $tqH$ couplings are $C_{c\phi} <1.35$ $(0.97)$ and $C_{u\phi} <1.16$ $(0.82)$.
Leading tau Pt distributions obtained before the fit to data (Pre-Fit) showing the expected background and tuH signals after applying fake factors in the $t_{\ell}\tau_{had}\tau_{had}$ region. Other MC includes single top, V+jets, and other small backgrounds. The tuH signals with nominal branching ratio of 0.1% are scaled using normalization factors of 2 to 50. Statistical and systematic uncertainties are included in the "Total background".
Leading tau Pt distributions obtained before the fit to data (Pre-Fit) showing the expected background and tuH signals after applying fake factors in the $t_{\ell}\tau_{had}$-1j region. Other MC includes single top, V+jets, and other small backgrounds. The tuH signals with nominal branching ratio of 0.1% are scaled using normalization factors of 2 to 50. Statistical and systematic uncertainties are included in the "Total background".
Leading tau Pt distributions obtained before the fit to data (Pre-Fit) showing the expected background and tuH signals after applying fake factors in the $t_{\ell}\tau_{had}$-2j region. Other MC includes single top, V+jets, and other small backgrounds. The tuH signals with nominal branching ratio of 0.1% are scaled using normalization factors of 2 to 50. Statistical and systematic uncertainties are included in the "Total background".
Leading tau Pt distributions obtained before the fit to data (Pre-Fit) showing the expected background and tuH signals after applying fake factors in the $t_{h}\tau_{lep}\tau_{had}$-2j region. Other MC includes single top, V+jets, and other small backgrounds. The tuH signals with nominal branching ratio of 0.1% are scaled using normalization factors of 2 to 50. Statistical and systematic uncertainties are included in the "Total background".
Leading tau Pt distributions obtained before the fit to data (Pre-Fit) showing the expected background and tuH signals after applying fake factors in the $t_{h}\tau_{lep}\tau_{had}$-3j region. Other MC includes single top, V+jets, and other small backgrounds. The tuH signals with nominal branching ratio of 0.1% are scaled using normalization factors of 2 to 50. Statistical and systematic uncertainties are included in the "Total background".
Leading tau Pt distributions obtained before the fit to data (Pre-Fit) showing the expected background and tuH signals after applying fake factors in the $t_{\ell}\tau_{had}\tau_{had}$SS region. Other MC includes single top, V+jets, and other small backgrounds. The tuH signals with nominal branching ratio of 0.1% are scaled using normalization factors of 2 to 50. Statistical and systematic uncertainties are included in the "Total background".
Leading tau Pt distributions obtained before the fit to data (Pre-Fit) showing the expected background and tuH signals after applying fake factors in the $t_{h}\tau_{had}\tau_{had}$-2j region. Rare includes single top, V+jets, and other small backgrounds. $\tau_{sub}$ real includes the contribution of fakes for which the sub-leading tau is real. The tuH signals with nominal branching ratio of 0.1% are scaled using normalization factors of 2 to 50. Statistical and systematic uncertainties are included in the "Total background".
Leading tau Pt distributions obtained before the fit to data (Pre-Fit) showing the expected background and tuH signals after applying fake factors in the $t_{h}\tau_{had}\tau_{had}$-3j region. Rare includes single top, V+jets, and other small backgrounds. $\tau_{sub}$ real includes the contribution of fakes for which the sub-leading tau is real. The tuH signals with nominal branching ratio of 0.1% are scaled using normalization factors of 2 to 50. Statistical and systematic uncertainties are included in the "Total background".
Leading tau Pt distributions obtained before the fit to data (Pre-Fit) showing the expected background and tuH signals after applying fake factors in the $t_{h}\tau_{had}\tau_{had}$-3jSS region. Rare includes single top, V+jets, and other small backgrounds. $\tau_{sub}$ real includes the contribution of fakes for which the sub-leading tau is real. The tuH signals with nominal branching ratio of 0.1% are scaled using normalization factors of 2 to 50. Statistical and systematic uncertainties are included in the "Total background".
Di-tau mass distributions obtained before the fit to data (Pre-Fit) showing the expected background and tuH signals after applying fake factors in the $t_{\ell}\tau_{had}\tau_{had}$ region. Other MC includes single top, V+jets, and other small backgrounds. The tuH signals with nominal branching ratio of 0.1% are scaled using normalization factors of 2 to 50. Statistical and systematic uncertainties are included in the "Total background".
Di-tau mass distributions obtained before the fit to data (Pre-Fit) showing the expected background and tuH signals after applying fake factors in the $t_{\ell}\tau_{had}$-1j region. Other MC includes single top, V+jets, and other small backgrounds. The tuH signals with nominal branching ratio of 0.1% are scaled using normalization factors of 2 to 50. Statistical and systematic uncertainties are included in the "Total background".
Di-tau mass distributions obtained before the fit to data (Pre-Fit) showing the expected background and tuH signals after applying fake factors in the $t_{\ell}\tau_{had}$-2j region. Other MC includes single top, V+jets, and other small backgrounds. The tuH signals with nominal branching ratio of 0.1% are scaled using normalization factors of 2 to 50. Statistical and systematic uncertainties are included in the "Total background".
Di-tau mass distributions obtained before the fit to data (Pre-Fit) showing the expected background and tuH signals after applying fake factors in the $t_{h}\tau_{lep}\tau_{had}$-2j region. Other MC includes single top, V+jets, and other small backgrounds. The tuH signals with nominal branching ratio of 0.1% are scaled using normalization factors of 2 to 50. Statistical and systematic uncertainties are included in the "Total background".
Di-tau mass distributions obtained before the fit to data (Pre-Fit) showing the expected background and tuH signals after applying fake factors in the $t_{h}\tau_{lep}\tau_{had}$-3j region. Other MC includes single top, V+jets, and other small backgrounds. The tuH signals with nominal branching ratio of 0.1% are scaled using normalization factors of 2 to 50. Statistical and systematic uncertainties are included in the "Total background".
Di-tau mass distributions obtained before the fit to data (Pre-Fit) showing the expected background and tuH signals after applying fake factors in the $t_{\ell}\tau_{had}\tau_{had}$SS region. Other MC includes single top, V+jets, and other small backgrounds. The tuH signals with nominal branching ratio of 0.1% are scaled using normalization factors of 2 to 50. Statistical and systematic uncertainties are included in the "Total background".
Di-tau mass distributions obtained before the fit to data (Pre-Fit) showing the expected background and tuH signals after applying fake factors in the $t_{h}\tau_{had}\tau_{had}$-2j region. Rare includes single top, V+jets, and other small backgrounds. $\tau_{sub}$ real includes the contribution of fakes for which the sub-leading tau is real. The tuH signals with nominal branching ratio of 0.1% are scaled using normalization factors of 2 to 50. Statistical and systematic uncertainties are included in the "Total background".
Di-tau mass distributions obtained before the fit to data (Pre-Fit) showing the expected background and tuH signals after applying fake factors in the $t_{h}\tau_{had}\tau_{had}$-3j region. Rare includes single top, V+jets, and other small backgrounds. $\tau_{sub}$ real includes the contribution of fakes for which the sub-leading tau is real. The tuH signals with nominal branching ratio of 0.1% are scaled using normalization factors of 2 to 50. Statistical and systematic uncertainties are included in the "Total background".
Di-tau mass distributions obtained before the fit to data (Pre-Fit) showing the expected background and tuH signals after applying fake factors in the $t_{h}\tau_{had}\tau_{had}$-3jSS region. Rare includes single top, V+jets, and other small backgrounds. $\tau_{sub}$ real includes the contribution of fakes for which the sub-leading tau is real. The tuH signals with nominal branching ratio of 0.1% are scaled using normalization factors of 2 to 50. Statistical and systematic uncertainties are included in the "Total background".
BDT output distributions obtained from a signal+background fit to the data for the tuH search in the $t_{\ell}\tau_{had}\tau_{had}$ region, Other MC includes single top, V+jets, and other small backgrounds. Statistical and systematic uncertainties are included in the "Total background". The signal shapes of tt(uH), tH, and their sum are also shown using a normalisation of 2 x $\mathcal{B}(\mathrm{t}\to\mathrm{uH})$ of 0.1%.
BDT output distributions obtained from a signal+background fit to the data for the tuH search in the $t_{\ell}\tau_{had}$-1j region, Other MC includes single top, V+jets, and other small backgrounds. Statistical and systematic uncertainties are included in the "Total background". The signal shapes of tt(uH), tH, and their sum are also shown using a normalisation of 2 x $\mathcal{B}(\mathrm{t}\to\mathrm{uH})$ of 0.1%.
BDT output distributions obtained from a signal+background fit to the data for the tuH search in the $t_{\ell}\tau_{had}$-2j region, Other MC includes single top, V+jets, and other small backgrounds. Statistical and systematic uncertainties are included in the "Total background". The signal shapes of tt(uH), tH, and their sum are also shown using a normalisation of 2 x $\mathcal{B}(\mathrm{t}\to\mathrm{uH})$ of 0.1%.
BDT output distributions obtained from a signal+background fit to the data for the tuH search in the $t_{h}\tau_{lep}\tau_{had}$-2j region, Other MC includes single top, V+jets, and other small backgrounds. Statistical and systematic uncertainties are included in the "Total background". The signal shapes of tt(uH), tH, and their sum are also shown using a normalisation of 2 x $\mathcal{B}(\mathrm{t}\to\mathrm{uH})$ of 0.1%.
BDT output distributions obtained from a signal+background fit to the data for the tuH search in the $t_{h}\tau_{lep}\tau_{had}$-3j region, Other MC includes single top, V+jets, and other small backgrounds. Statistical and systematic uncertainties are included in the "Total background". The signal shapes of tt(uH), tH, and their sum are also shown using a normalisation of 2 x $\mathcal{B}(\mathrm{t}\to\mathrm{uH})$ of 0.1%.
BDT output distributions obtained from a signal+background fit to the data for the tuH search in the $t_{\ell}\tau_{had}\tau_{had}$SS region, Other MC includes single top, V+jets, and other small backgrounds. Statistical and systematic uncertainties are included in the "Total background". The signal shapes of tt(uH), tH, and their sum are also shown using a normalisation of 2 x $\mathcal{B}(\mathrm{t}\to\mathrm{uH})$ of 0.1%.
BDT output distributions obtained from a signal+background fit to the data for the tuH search in the $t_{h}\tau_{had}\tau_{had}$-2j region, Rare includes single top, V+jets, and other small backgrounds. $\tau_{sub}$ real includes the contribution of fakes for which the sub-leading tau is real. Statistical and systematic uncertainties are included in the "Total background". The signal shapes of tt(uH), tH, and their sum are also shown using a normalisation of 2 x $\mathcal{B}(\mathrm{t}\to\mathrm{uH})$ of 0.1%.
BDT output distributions obtained from a signal+background fit to the data for the tuH search in the $t_{h}\tau_{had}\tau_{had}$-3j region, Rare includes single top, V+jets, and other small backgrounds. $\tau_{sub}$ real includes the contribution of fakes for which the sub-leading tau is real. Statistical and systematic uncertainties are included in the "Total background". The signal shapes of tt(uH), tH, and their sum are also shown using a normalisation of 2 x $\mathcal{B}(\mathrm{t}\to\mathrm{uH})$ of 0.1%.
BDT output distributions obtained from a signal+background fit to the data for the tuH search in the $t_{h}\tau_{had}\tau_{had}$-3jSS region, Rare includes single top, V+jets, and other small backgrounds. $\tau_{sub}$ real includes the contribution of fakes for which the sub-leading tau is real. Statistical and systematic uncertainties are included in the "Total background". The signal shapes of tt(uH), tH, and their sum are also shown using a normalisation of 2 x $\mathcal{B}(\mathrm{t}\to\mathrm{uH})$ of 0.1%.
BDT output distributions obtained from a signal+background fit to the data for the tcH search in the $t_{\ell}\tau_{had}\tau_{had}$ region, Other MC includes single top, V+jets, and other small backgrounds. Statistical and systematic uncertainties are included in the "Total background". The signal shapes of tt(cH), tH, and their sum are also shown using a normalisation of 2 x $\mathcal{B}(\mathrm{t}\to\mathrm{cH})$ of 0.1%.
BDT output distributions obtained from a signal+background fit to the data for the tcH search in the $t_{\ell}\tau_{had}$-1j region, Other MC includes single top, V+jets, and other small backgrounds. Statistical and systematic uncertainties are included in the "Total background". The signal shapes of tt(cH), tH, and their sum are also shown using a normalisation of 2 x $\mathcal{B}(\mathrm{t}\to\mathrm{cH})$ of 0.1%.
BDT output distributions obtained from a signal+background fit to the data for the tcH search in the $t_{\ell}\tau_{had}$-2j region, Other MC includes single top, V+jets, and other small backgrounds. Statistical and systematic uncertainties are included in the "Total background". The signal shapes of tt(cH), tH, and their sum are also shown using a normalisation of 2 x $\mathcal{B}(\mathrm{t}\to\mathrm{cH})$ of 0.1%.
BDT output distributions obtained from a signal+background fit to the data for the tcH search in the $t_{h}\tau_{lep}\tau_{had}$-2j region, Other MC includes single top, V+jets, and other small backgrounds. Statistical and systematic uncertainties are included in the "Total background". The signal shapes of tt(cH), tH, and their sum are also shown using a normalisation of 2 x $\mathcal{B}(\mathrm{t}\to\mathrm{cH})$ of 0.1%.
BDT output distributions obtained from a signal+background fit to the data for the tcH search in the $t_{h}\tau_{lep}\tau_{had}$-3j region,Other MC includes single top, V+jets, and other small backgrounds. Statistical and systematic uncertainties are included in the "Total background". The signal shapes of tt(cH), tH, and their sum are also shown using a normalisation of 2 x $\mathcal{B}(\mathrm{t}\to\mathrm{cH})$ of 0.1%.
BDT output distributions obtained from a signal+background fit to the data for the tcH search in the $t_{\ell}\tau_{had}\tau_{had}$SS region, Other MC includes single top, V+jets, and other small backgrounds. Statistical and systematic uncertainties are included in the "Total background". The signal shapes of tt(cH), tH, and their sum are also shown using a normalisation of 2 x $\mathcal{B}(\mathrm{t}\to\mathrm{cH})$ of 0.1%.
BDT output distributions obtained from a signal+background fit to the data for the tcH search in the $t_{h}\tau_{had}\tau_{had}$-2j region, Rare includes single top, V+jets, and other small backgrounds. $\tau_{sub}$ real includes the contribution of fakes for which the sub-leading tau is real. Statistical and systematic uncertainties are included in the "Total background". The signal shapes of tt(cH), tH, and their sum are also shown using a normalisation of 2 x $\mathcal{B}(\mathrm{t}\to\mathrm{cH})$ of 0.1%.
BDT output distributions obtained from a signal+background fit to the data for the tcH search in the $t_{h}\tau_{had}\tau_{had}$-3j region, Rare includes single top, V+jets, and other small backgrounds. $\tau_{sub}$ real includes the contribution of fakes for which the sub-leading tau is real. Statistical and systematic uncertainties are included in the "Total background". The signal shapes of tt(cH), tH, and their sum are also shown using a normalisation of 2 x $\mathcal{B}(\mathrm{t}\to\mathrm{cH})$ of 0.1%.
BDT output distributions obtained from a signal+background fit to the data for the tcH search in the $t_{h}\tau_{had}\tau_{had}$-3jSS region, Rare includes single top, V+jets, and other small backgrounds. $\tau_{sub}$ real includes the contribution of fakes for which the sub-leading tau is real. Statistical and systematic uncertainties are included in the "Total background". The signal shapes of tt(cH), tH, and their sum are also shown using a normalisation of 2 x $\mathcal{B}(\mathrm{t}\to\mathrm{cH})$ of 0.1%.
95% CL upper limits on $\mathcal{B}(\mathrm{t}\to\mathrm{cH})$ for the individual searches as well as their combination, assuming $\mathcal{B}(\mathrm{t}\to\mathrm{uH}) = 0$. The observed limits are compared with the expected (median) limits under the background-only hypothesis. The surrounding shaded bands correspond to the 68% and 95% CL intervals around the expected limits, denoted by $\pm 1\sigma$ and $\pm 2\sigma$, respectively.
95% CL upper limits on $\mathcal{B}(\mathrm{t}\to\mathrm{uH})$ for the individual searches as well as their combination, assuming $\mathcal{B}(\mathrm{t}\to\mathrm{cH}) = 0$. The observed limits are compared with the expected (median) limits under the background-only hypothesis. The surrounding shaded bands correspond to the 68% and 95% CL intervals around the expected limits, denoted by $\pm 1\sigma$ and $\pm 2\sigma$, respectively.
Observed upper limits at 95% CL on the branching fractions in the plane of $\mathcal{B}(\mathrm{t}\to\mathrm{uH})$ and $\mathcal{B}(\mathrm{t}\to\mathrm{cH})$.
Expected upper limits at 95% CL on the branching fractions in the plane of $\mathcal{B}(\mathrm{t}\to\mathrm{uH})$ and $\mathcal{B}(\mathrm{t}\to\mathrm{cH})$.
Expected $+2\sigma$ upper limits at 95% CL on the branching fractions in the plane of $\mathcal{B}(\mathrm{t}\to\mathrm{uH})$ and $\mathcal{B}(\mathrm{t}\to\mathrm{cH})$.
Expected $+1\sigma$ upper limits at 95% CL on the branching fractions in the plane of $\mathcal{B}(\mathrm{t}\to\mathrm{uH})$ and $\mathcal{B}(\mathrm{t}\to\mathrm{cH})$.
Expected $-1\sigma$ upper limits at 95% CL on the branching fractions in the plane of $\mathcal{B}(\mathrm{t}\to\mathrm{uH})$ and $\mathcal{B}(\mathrm{t}\to\mathrm{cH})$.
Expected $-2\sigma$ upper limits at 95% CL on the branching fractions in the plane of $\mathcal{B}(\mathrm{t}\to\mathrm{uH})$ and $\mathcal{B}(\mathrm{t}\to\mathrm{cH})$.
Observed upper limits at 95% CL on the anomalous couplings in the plane of $C_{\mathrm{c\phi}}$ and $C_{\mathrm{u\phi}}$.
Expected upper limits at 95% CL on the anomalous couplings in the plane of $C_{\mathrm{c\phi}}$ and $C_{\mathrm{u\phi}}$.
Expected $+2\sigma$ upper limits at 95% CL on the anomalous couplings in the plane of $C_{\mathrm{c\phi}}$ and $C_{\mathrm{u\phi}}$.
Expected $+1\sigma$ upper limits at 95% CL on the anomalous couplings in the plane of $C_{\mathrm{c\phi}}$ and $C_{\mathrm{u\phi}}$.
Expected $-1\sigma$ upper limits at 95% CL on the anomalous couplings in the plane of $C_{\mathrm{c\phi}}$ and $C_{\mathrm{u\phi}}$.
Expected $-2\sigma$ upper limits at 95% CL on the anomalous couplings in the plane of $C_{\mathrm{c\phi}}$ and $C_{\mathrm{u\phi}}$.
Predicted and observed yields in each of the analysis regions considered in leptonic channel.
Predicted and observed yields in each of the analysis regions considered in hadronic channel.
Absolute uncertainties on $\mathcal{B}(\mathrm{t}\to\mathrm{qH})$ obtained from the combined fit to the data.
Summary of 95% CL upper limits on $\mathcal{B}(\mathrm{t}\to\mathrm{qH})$, significance and best-fit branching ratio in the signal regions. The values in the tables are in the form of observed(expected).
A search is reported for excited $\tau$-leptons and leptoquarks in events with two hadronically decaying $\tau$-leptons and two or more jets. The search uses proton-proton (pp) collision data at $\sqrt{s} = 13$ TeV recorded by the ATLAS experiment during the Run 2 of the Large Hadron Collider in 2015-2018. The total integrated luminosity is 139 fb$^{-1}$. The excited $\tau$-lepton is assumed to be produced and to decay via a four-fermion contact interaction into an ordinary $\tau$-lepton and a quark-antiquark pair. The leptoquarks are assumed to be produced in pairs via the strong interaction, and each leptoquark is assumed to couple to a charm or lighter quark and a $\tau$-lepton. No excess over the background prediction is observed. Excited $\tau$-leptons with masses below 2.8 TeV are excluded at 95% CL in scenarios with the contact interaction scale $\Lambda$ set to 10 TeV. At the extreme limit of model validity where $\Lambda$ is set equal to the excited $\tau$-lepton mass, excited $\tau$-leptons with masses below 4.6 TeV are excluded. Leptoquarks with masses below 1.3 TeV are excluded at 95% CL if their branching ratio to a charm quark and a $\tau$-lepton equals 1. The analysis does not exploit flavour-tagging in the signal region.
Observed and expected upper 95% CL limit on the $\tau^\ast$ production cross-section as a function of $m_{\tau^\ast}$ for a fixed value of the contact interaction scale, $\Lambda = 10$ TeV.
Observed and expected lower 95% CL limit on the contact interaction scale $\Lambda$ as a function of $m_{\tau^\ast}$.
Observed and expected upper 95% CL limit on the LQ production cross-section as a function of $m_\mathrm{LQ}$. The LQ couples to a tau lepton and a c-quark. The limits are also valid for scenarios in which the LQ couples to lighter quarks.
Cutflow for two representative signal samples used in this analysis. The excited tau mass $m_{\tau^\ast} = 2.75$ TeV and the contact interaction scale $\Lambda=10$ TeV. The LQ mass $m_\mathrm{LQ} = 1.3$ TeV. The event yields include all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.
Acceptance x efficiency of the $\tau^\ast$ signal SR selection
Acceptance x efficiency of the LQ signal SR selection
A study of $B_c^+\to J/\psi D_s^+$ and $B_c^+\to J/\psi D_s^{*+}$ decays using 139 fb$^{-1}$ of integrated luminosity collected with the ATLAS detector from $\sqrt{s} = 13$ TeV $pp$ collisions at the LHC is presented. The ratios of the branching fractions of the two decays to the branching fraction of the $B_c^+\to J/\psi \pi^+$ decay are measured: $\mathcal B(B_c^+\to J/\psi D_s^+)/\mathcal B(B_c^+\to J/\psi \pi^+) = 2.76\pm 0.47$ and $\mathcal B(B_c^+\to J/\psi D_s^{*+})/\mathcal B(B_c^+\to J/\psi \pi^+) = 5.33\pm 0.96$. The ratio of the branching fractions of the two decays is found to be $\mathcal B(B_c^+\to J/\psi D_s^{*+})/\mathcal B(B_c^+\to J/\psi D_s^+) = 1.93\pm0.26$. For the $B_c^+\to J/\psi D_s^{*+}$ decay, the transverse polarization fraction, $\Gamma_{\pm\pm}/\Gamma$, is measured to be $0.70\pm0.11$. The reported uncertainties include both the statistical and systematic components added in quadrature. The precision of the measurements exceeds that in all previous studies of these decays. These results supersede those obtained in the earlier ATLAS study of the same decays with $\sqrt{s} = 7$ and 8 TeV $pp$ collision data. A comparison with available theoretical predictions for the measured quantities is presented.
Measured values of $R_{D_s^+/\pi^+}$, $R_{D_s^{*+}/\pi^+}$, $R_{D_s^{*+}/D_s^+}$ ratios of branching fractions, fraction of transverse polarization $\Gamma_{\pm\pm}/\Gamma$ with their statistical uncertainties and full breakdown of systematic uncertainties. Predictions of various theory calculations are also shown with their uncertainties where available, as well as the estimates based on similar decays of light $B$ mesons.
Parameters of the $B_c^+\to J/\psi D_s^+$ and $B_c^+\to J/\psi D_s^{*+}$ signals obtained with the unbinned extended maximum-likelihood fit to the data. Only the statistical uncertainties are included. No acceptance or efficiency corrections are applied to the signal yields.
Parameters of the $B_c^+\to J/\psi \pi^+$ signal obtained with the unbinned extended maximum-likelihood fit. Only the statistical uncertainties are included. No efficiency correction is applied to the signal yield.
Summary of the total efficiencies. Quoted uncertainties correspond to statistical uncertainties of the simulated samples used. For the $B_c^+\to J/\psi \pi^+$ channel, the efficiency $\epsilon_{B_c^+\to J/\psi \pi^+}$ entering the equations for $R_{D_s^{(*)+}/\pi^+}$ is shown, while the efficiency for the full dataset is not defined.
A search for new phenomena has been performed in final states with at least one isolated high-momentum photon, jets and missing transverse momentum in proton--proton collisions at a centre-of-mass energy of $\sqrt{s} = 13$ TeV. The data, collected by the ATLAS experiment at the CERN LHC, correspond to an integrated luminosity of 139 $fb^{-1}$. The experimental results are interpreted in a supersymmetric model in which pair-produced gluinos decay into neutralinos, which in turn decay into a gravitino, at least one photon, and jets. No significant deviations from the predictions of the Standard Model are observed. Upper limits are set on the visible cross section due to physics beyond the Standard Model, and lower limits are set on the masses of the gluinos and neutralinos, all at 95% confidence level. Visible cross sections greater than 0.022 fb are excluded and pair-produced gluinos with masses up to 2200 GeV are excluded for most of the NLSP masses investigated.
The observed and expected (post-fit) yields in the control and validation regions. The lower panel shows the difference in standard deviations between the observed and expected yields, considering both the systematic and statistical uncertainties on the background expectation.
Observed (points with error bars) and expected background (solid histograms) distributions for $E_{T}^{miss}$ in the signal region (a) SRL, (b) SRM and (c) SRH after the background-only fit applied to the CRs. The predicted signal distributions for the two models with a gluino mass of 2000 GeV and neutralino mass of 250 GeV (SRL), 1050 GeV (SRM) or 1950 GeV (SRH) are also shown for comparison. The uncertainties in the SM background are only statistical.
Observed (points with error bars) and expected background (solid histograms) distributions for $E_{T}^{miss}$ in the signal region (a) SRL, (b) SRM and (c) SRH after the background-only fit applied to the CRs. The predicted signal distributions for the two models with a gluino mass of 2000 GeV and neutralino mass of 250 GeV (SRL), 1050 GeV (SRM) or 1950 GeV (SRH) are also shown for comparison. The uncertainties in the SM background are only statistical.
Observed (points with error bars) and expected background (solid histograms) distributions for $E_{T}^{miss}$ in the signal region (a) SRL, (b) SRM and (c) SRH after the background-only fit applied to the CRs. The predicted signal distributions for the two models with a gluino mass of 2000 GeV and neutralino mass of 250 GeV (SRL), 1050 GeV (SRM) or 1950 GeV (SRH) are also shown for comparison. The uncertainties in the SM background are only statistical.
Observed and expected exclusion limit in the gluino-neutralino mass plane at 95% CL combined using the signal region with the best expected sensitivity at each point, for the full Run-2 dataset corresponding to an integrated luminosity of $139~\mathrm{fb}^{-1}$, for $\gamma/Z$ (a) and $\gamma/h$ (b) signal models. The black solid line corresponds to the expected limits at 95% CL, with the light (yellow) bands indicating the 1$\sigma$ exclusions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves, the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties. For each point in the higgsino-bino parameter space, the labels indicate the best-expected signal region, where L, M and H mean SRL, SRM and SRH, respectively.
Observed and expected exclusion limit in the gluino-neutralino mass plane at 95% CL combined using the signal region with the best expected sensitivity at each point, for the full Run-2 dataset corresponding to an integrated luminosity of $139~\mathrm{fb}^{-1}$, for $\gamma/Z$ (a) and $\gamma/h$ (b) signal models. The black solid line corresponds to the expected limits at 95% CL, with the light (yellow) bands indicating the 1$\sigma$ exclusions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves, the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties. For each point in the higgsino-bino parameter space, the labels indicate the best-expected signal region, where L, M and H mean SRL, SRM and SRH, respectively.
Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Cutflow for the SRL selection, for two relevant signal points for both $\gamma/Z$ and $\gamma/h$ models, where the gluinos have mass of 2000 GeV and the neutralinos have a mass of 250 GeV (10000 generated events). The numbers are normalized to a luminosity of 139 $fb^{-1}$.
Cutflow for the SRM selection, for two relevant signal points for both $\gamma/Z$ and $\gamma/h$ models, where the gluinos have mass of 2000 GeV and the neutralinos have a mass of 1050 GeV (10000 generated events). The numbers are normalized to a luminosity of 139 $fb^{-1}$.
Cutflow for the SRH selection, for two relevant signal points for both $\gamma/Z$ and $\gamma/h$ models, where the gluinos have mass of 2000 GeV and the neutralinos have a mass of 1950 GeV (10000 generated events). The numbers are normalized to a luminosity of 139 $fb^{-1}$.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Searches for new phenomena inspired by supersymmetry in final states containing an $e^+e^-$ or $\mu^+\mu^-$ pair, jets, and missing transverse momentum are presented. These searches make use of proton-proton collision data with an integrated luminosity of 139 $\text{fb}^{-1}$, collected during 2015-2018 at a centre-of-mass energy $\sqrt{s}=13 $TeV by the ATLAS detector at the Large Hadron Collider. Two searches target the pair production of charginos and neutralinos. One uses the recursive-jigsaw reconstruction technique to follow up on excesses observed in 36.1 $\text{fb}^{-1}$ of data, and the other uses conventional event variables. The third search targets pair production of coloured supersymmetric particles (squarks or gluinos) decaying through the next-to-lightest neutralino $(\tilde\chi_2^0)$ via a slepton $(\tilde\ell)$ or $Z$ boson into $\ell^+\ell^-\tilde\chi_1^0$, resulting in a kinematic endpoint or peak in the dilepton invariant mass spectrum. The data are found to be consistent with the Standard Model expectations. Results are interpreted using simplified models and exclude masses up to 900 GeV for electroweakinos, 1550 GeV for squarks, and 2250 GeV for gluinos.
Breakdown of expected and observed yields in the two recursive-jigsaw reconstruction signal regions after a simultaneous fit of the the CRs. The two sets of regions are fit separately. The uncertainties include both statistical and systematic sources.
Breakdown of expected and observed yields in the electroweak search High and $\ell\ell bb$ signal regions after a simultaneous fit to the signal regions and control regions. All statistical and systematic uncertainties are included.
Breakdown of expected and observed yields in the electroweak search Int, Low, and OffShell signal regions after a simultaneous fit to the signal regions and control regions. All statistical and systematic uncertainties are included.
Breakdown of expected and observed yields in the four edge signal regions, integrated over the $m_{\ell\ell}$ distribution after a separate simultaneous fit to each signal region and control region pair. The uncertainties include both the statistical and systematic sources.
Breakdown of expected and observed yields in the three on-$Z$ signal regions after a separate simultaneous fit to each signal region and control region pair. The uncertainties include both the statistical and systematic sources.
Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-High-Sideband-EWK (top-left), VR-High-R-EWK (top-right), VR-1J-High-EWK (bottom-left), and VR-$\ell\ell bb$-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.
Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-High-Sideband-EWK (top-left), VR-High-R-EWK (top-right), VR-1J-High-EWK (bottom-left), and VR-$\ell\ell bb$-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.
Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-High-Sideband-EWK (top-left), VR-High-R-EWK (top-right), VR-1J-High-EWK (bottom-left), and VR-$\ell\ell bb$-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.
Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-High-Sideband-EWK (top-left), VR-High-R-EWK (top-right), VR-1J-High-EWK (bottom-left), and VR-$\ell\ell bb$-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.
Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-Int-EWK (top-left), VR-Low-EWK (top-right), VR-Low-2-EWK (bottom-left), and VR-OffShell-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.
Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-Int-EWK (top-left), VR-Low-EWK (top-right), VR-Low-2-EWK (bottom-left), and VR-OffShell-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.
Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-Int-EWK (top-left), VR-Low-EWK (top-right), VR-Low-2-EWK (bottom-left), and VR-OffShell-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.
Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-Int-EWK (top-left), VR-Low-EWK (top-right), VR-Low-2-EWK (bottom-left), and VR-OffShell-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.
Observed and expected dilepton mass distributions in VRC-STR (top-left), VRLow-STR (top-right), VRMed-STR (bottom-left), and VRHigh-STR (bottom-right). Each validation region is fit separately with the corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The entries are normalized to the bin width, and the last bin is the overflow.
Observed and expected dilepton mass distributions in VRC-STR (top-left), VRLow-STR (top-right), VRMed-STR (bottom-left), and VRHigh-STR (bottom-right). Each validation region is fit separately with the corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The entries are normalized to the bin width, and the last bin is the overflow.
Observed and expected dilepton mass distributions in VRC-STR (top-left), VRLow-STR (top-right), VRMed-STR (bottom-left), and VRHigh-STR (bottom-right). Each validation region is fit separately with the corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The entries are normalized to the bin width, and the last bin is the overflow.
Observed and expected dilepton mass distributions in VRC-STR (top-left), VRLow-STR (top-right), VRMed-STR (bottom-left), and VRHigh-STR (bottom-right). Each validation region is fit separately with the corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The entries are normalized to the bin width, and the last bin is the overflow.
Observed and expected jet multiplicity in VRLow-STR (top-left), VRMed-STR (top-right), and VRHigh-STR (bottom) after a fit performed on the $m_{\ell\ell}$ distribution and corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The last bin contains the overflow.
Observed and expected jet multiplicity in VRLow-STR (top-left), VRMed-STR (top-right), and VRHigh-STR (bottom) after a fit performed on the $m_{\ell\ell}$ distribution and corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The last bin contains the overflow.
Observed and expected jet multiplicity in VRLow-STR (top-left), VRMed-STR (top-right), and VRHigh-STR (bottom) after a fit performed on the $m_{\ell\ell}$ distribution and corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The last bin contains the overflow.
Observed and expected dilepton mass distributions in VR3L-STR without a fit to the data. The 'Other' category includes the negligible contributions from $t\bar{t}$ and $Z/\gamma^*$+jets processes. The hatched band contains the statistical uncertainty and the theoretical systematic uncertainties of the $WZ$/$ZZ$ prediction, which are the dominant sources of uncertainty. No fit is performed. The last bin contains the overflow.
Observed and expected distributions in five EWK search regions after a simultaneous fit to the SR and CR. In the top row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-High_8-EWK and $m_{bb}$ in SR-$\ell\ell bb$-EWK. In the middle row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Int-EWK and $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Low-EWK. In the bottom row is $m_{\ell\ell}$ in SR-OffShell-EWK. Overlaid are example C1N2 and GMSB signal models, where the numbers in the brackets indicate the masses, in $\mathrm{GeV}$, of the $\tilde{\chi}_1^\pm$ and $\tilde{\chi}_2^0$ or the mass of the $\tilde{\chi}_1^0$ and branching ratio to the Higgs boson respectively. All statistical and systematic uncertainties are included in the hatched bands. The last bin includes the overflow.
Observed and expected distributions in five EWK search regions after a simultaneous fit to the SR and CR. In the top row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-High_8-EWK and $m_{bb}$ in SR-$\ell\ell bb$-EWK. In the middle row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Int-EWK and $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Low-EWK. In the bottom row is $m_{\ell\ell}$ in SR-OffShell-EWK. Overlaid are example C1N2 and GMSB signal models, where the numbers in the brackets indicate the masses, in $\mathrm{GeV}$, of the $\tilde{\chi}_1^\pm$ and $\tilde{\chi}_2^0$ or the mass of the $\tilde{\chi}_1^0$ and branching ratio to the Higgs boson respectively. All statistical and systematic uncertainties are included in the hatched bands. The last bin includes the overflow.
Observed and expected distributions in five EWK search regions after a simultaneous fit to the SR and CR. In the top row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-High_8-EWK and $m_{bb}$ in SR-$\ell\ell bb$-EWK. In the middle row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Int-EWK and $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Low-EWK. In the bottom row is $m_{\ell\ell}$ in SR-OffShell-EWK. Overlaid are example C1N2 and GMSB signal models, where the numbers in the brackets indicate the masses, in $\mathrm{GeV}$, of the $\tilde{\chi}_1^\pm$ and $\tilde{\chi}_2^0$ or the mass of the $\tilde{\chi}_1^0$ and branching ratio to the Higgs boson respectively. All statistical and systematic uncertainties are included in the hatched bands. The last bin includes the overflow.
Observed and expected distributions in five EWK search regions after a simultaneous fit to the SR and CR. In the top row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-High_8-EWK and $m_{bb}$ in SR-$\ell\ell bb$-EWK. In the middle row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Int-EWK and $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Low-EWK. In the bottom row is $m_{\ell\ell}$ in SR-OffShell-EWK. Overlaid are example C1N2 and GMSB signal models, where the numbers in the brackets indicate the masses, in $\mathrm{GeV}$, of the $\tilde{\chi}_1^\pm$ and $\tilde{\chi}_2^0$ or the mass of the $\tilde{\chi}_1^0$ and branching ratio to the Higgs boson respectively. All statistical and systematic uncertainties are included in the hatched bands. The last bin includes the overflow.
Observed and expected distributions in five EWK search regions after a simultaneous fit to the SR and CR. In the top row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-High_8-EWK and $m_{bb}$ in SR-$\ell\ell bb$-EWK. In the middle row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Int-EWK and $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Low-EWK. In the bottom row is $m_{\ell\ell}$ in SR-OffShell-EWK. Overlaid are example C1N2 and GMSB signal models, where the numbers in the brackets indicate the masses, in $\mathrm{GeV}$, of the $\tilde{\chi}_1^\pm$ and $\tilde{\chi}_2^0$ or the mass of the $\tilde{\chi}_1^0$ and branching ratio to the Higgs boson respectively. All statistical and systematic uncertainties are included in the hatched bands. The last bin includes the overflow.
Observed and expected dilepton mass distributions in SRC-STR (top-left), SRLow-STR (top-right), SRMed-STR (bottom-left), and SRHigh-STR (bottom-right), with the binning used for interpretations after a separate simultaneous fit to each signal region and control region pair. The red dashed lines are example signal models overlaid on the figure. All statistical and systematic uncertainties are included in the hatched bands. The last bins are the overflow.
Observed and expected dilepton mass distributions in SRC-STR (top-left), SRLow-STR (top-right), SRMed-STR (bottom-left), and SRHigh-STR (bottom-right), with the binning used for interpretations after a separate simultaneous fit to each signal region and control region pair. The red dashed lines are example signal models overlaid on the figure. All statistical and systematic uncertainties are included in the hatched bands. The last bins are the overflow.
Observed and expected dilepton mass distributions in SRC-STR (top-left), SRLow-STR (top-right), SRMed-STR (bottom-left), and SRHigh-STR (bottom-right), with the binning used for interpretations after a separate simultaneous fit to each signal region and control region pair. The red dashed lines are example signal models overlaid on the figure. All statistical and systematic uncertainties are included in the hatched bands. The last bins are the overflow.
Observed and expected dilepton mass distributions in SRC-STR (top-left), SRLow-STR (top-right), SRMed-STR (bottom-left), and SRHigh-STR (bottom-right), with the binning used for interpretations after a separate simultaneous fit to each signal region and control region pair. The red dashed lines are example signal models overlaid on the figure. All statistical and systematic uncertainties are included in the hatched bands. The last bins are the overflow.
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294]. The grey numbers indicate the observed 95\% CLs upper limit on the cross section.
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294]. The grey numbers indicate the observed 95$\%$ CLs upper limit on the cross section.
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$ ilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$ ilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$ ilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$ ilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].The grey numbers indicated the observed 95\% CL upper limit on the cross section.
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].The grey numbers indicated the observed 95\% CL upper limit on the cross section.
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].The grey numbers indicated the observed 95\% CL upper limit on the cross section.
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
The combined $E_{\mathrm{T}}^{\mathrm{miss}}$ distribution of VRLow-STR and SRLow-STR (left), and the same region with the $\Delta\phi(\boldsymbol{j}_{1,2},\boldsymbol{\mathit{p}}_{ ext{T}}^{ ext{miss}})<0.4$ requirement, used as a control region to normalize the $Z/\gamma^*+\mathrm{jets}$ process (right). Separate fits for the SR and VR are performed, as for the results in the paper, and the resulting distributions are merged. All statistical and systematic uncertainties are included in the hatched bands. The last bins contain the overflow.
Cutflow of expected events in the four Strong search edge signal regions. `Leptons' refers to electrons and muons only. The gluino-$Z^{(*)}$ model with $m_{ ilde{g}}=800~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRC-STR with 60000 Monte Carlo (MC) events generated. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRMed-STR with 30000 (MC) events generated. The gluino-slepton model with $m_{ ilde{g}}=2~TeV$ and $m_{ ilde{\ell}}=1.3~TeV$ is used for SRLow-STR and SRHigh-STR with 30000 MC events generated. The Generator Filter requires two 5~GeV leptons and 100~GeV of \met. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~GeV$ or at least one lepton with $p_{\mathrm{T}}>25~GeV$ and a photon with $p_{\mathrm{T}}>40~GeV$, with all objects within $|\eta|=2.6$.
Cutflow of expected events in the four Strong search edge signal regions. `Leptons' refers to electrons and muons only. The gluino-$Z^{(*)}$ model with $m_{ ilde{g}}=800~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRC-STR with 60000 Monte Carlo (MC) events generated. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRMed-STR with 30000 (MC) events generated. The gluino-slepton model with $m_{ ilde{g}}=2~TeV$ and $m_{ ilde{\ell}}=1.3~TeV$ is used for SRLow-STR and SRHigh-STR with 30000 MC events generated. The Generator Filter requires two 5~GeV leptons and 100~GeV of \met. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~GeV$ or at least one lepton with $p_{\mathrm{T}}>25~GeV$ and a photon with $p_{\mathrm{T}}>40~GeV$, with all objects within $|\eta|=2.6$.
Cutflow of expected events in the four Strong search edge signal regions. `Leptons' refers to electrons and muons only. The gluino-$Z^{(*)}$ model with $m_{ ilde{g}}=800~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRC-STR with 60000 Monte Carlo (MC) events generated. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRMed-STR with 30000 (MC) events generated. The gluino-slepton model with $m_{ ilde{g}}=2~TeV$ and $m_{ ilde{\ell}}=1.3~TeV$ is used for SRLow-STR and SRHigh-STR with 30000 MC events generated. The Generator Filter requires two 5~GeV leptons and 100~GeV of \met. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~GeV$ or at least one lepton with $p_{\mathrm{T}}>25~GeV$ and a photon with $p_{\mathrm{T}}>40~GeV$, with all objects within $|\eta|=2.6$.
Cutflow of expected events in the four Strong search edge signal regions. `Leptons' refers to electrons and muons only. The gluino-$Z^{(*)}$ model with $m_{ ilde{g}}=800~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRC-STR with 60000 Monte Carlo (MC) events generated. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRMed-STR with 30000 (MC) events generated. The gluino-slepton model with $m_{ ilde{g}}=2~TeV$ and $m_{ ilde{\ell}}=1.3~TeV$ is used for SRLow-STR and SRHigh-STR with 30000 MC events generated. The Generator Filter requires two 5~GeV leptons and 100~GeV of \met. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~GeV$ or at least one lepton with $p_{\mathrm{T}}>25~GeV$ and a photon with $p_{\mathrm{T}}>40~GeV$, with all objects within $|\eta|=2.6$.
Cutflow of expected events in the three Strong search on-$Z$ signal regions. The cutflow up to the signal region specific requirements is the same as in the Strong search edge cutflow. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for all of the on-$Z$ signal regions with 30000 (MC) events generated.
Cutflow of expected events in the three Strong search on-$Z$ signal regions. The cutflow up to the signal region specific requirements is the same as in the Strong search edge cutflow. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for all of the on-$Z$ signal regions with 30000 (MC) events generated.
Cutflow of expected events in the three Strong search on-$Z$ signal regions. The cutflow up to the signal region specific requirements is the same as in the Strong search edge cutflow. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for all of the on-$Z$ signal regions with 30000 (MC) events generated.
Table 36: Cutflow of expected events in the region SR-OffShell_a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 36: Cutflow of expected events in the region SR-OffShell_a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 37: Cutflow of expected events in the region SR-OffShell_b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 37: Cutflow of expected events in the region SR-OffShell_b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 38: Cutflow of expected events in the region SR-Low_a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 38: Cutflow of expected events in the region SR-Low_a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 39: Cutflow of expected events in the region SR-Low_b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 39: Cutflow of expected events in the region SR-Low_b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 40: Cutflow of expected events in the region SR-Low-2-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 40: Cutflow of expected events in the region SR-Low-2-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 41: Cutflow of expected events in the region SR-Int_a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 41: Cutflow of expected events in the region SR-Int_a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 42: Cutflow of expected events in the region SR-Int_b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 42: Cutflow of expected events in the region SR-Int_b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 43: Cutflow of expected events in the region SR-High_16a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 43: Cutflow of expected events in the region SR-High_16a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 44: Cutflow of expected events in the region SR-High_16b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 44: Cutflow of expected events in the region SR-High_16b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 45: Cutflow of expected events in the region SR-High_8a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 45: Cutflow of expected events in the region SR-High_8a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 46: Cutflow of expected events in the region SR-High_8b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 46: Cutflow of expected events in the region SR-High_8b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 47: Cutflow of expected events in the region SR-1J-High-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 47: Cutflow of expected events in the region SR-1J-High-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 48: Cutflow of expected events in the region SR-llbb-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 48: Cutflow of expected events in the region SR-llbb-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
The combined $m_{jj}$ distribution of CR-Z-EWK and SR-Low-EWK (left), and the $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ distribution in CR-Z-met-EWK (right), which removes the upper limit of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}}) < 9$ from the definition of CR-Z-EWK. This $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ tail overlaps other control and validation regions, but not signal regions. The arrows indicate the signal region SR-Low-EWK (left), and the $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ phase space which is not included in CR-Z-EWK (right). All EWK search control and signal regions are included in the fit. All statistical and systematic uncertainties are included in the hatched bands. The theoretical uncertainties from CR-Z-EWK are applied to CR-Z-met-EWK. The last bins contain the overflow.
The combined $m_{jj}$ distribution of CR-Z-EWK and SR-Low-EWK (left), and the $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ distribution in CR-Z-met-EWK (right), which removes the upper limit of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}}) < 9$ from the definition of CR-Z-EWK. This $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ tail overlaps other control and validation regions, but not signal regions. The arrows indicate the signal region SR-Low-EWK (left), and the $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ phase space which is not included in CR-Z-EWK (right). All EWK search control and signal regions are included in the fit. All statistical and systematic uncertainties are included in the hatched bands. The theoretical uncertainties from CR-Z-EWK are applied to CR-Z-met-EWK. The last bins contain the overflow.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
A direct search for Higgs bosons produced via vector-boson fusion and subsequently decaying into invisible particles is reported. The analysis uses 139 $\text{fb}^{-1}$ of $pp$ collision data at a centre-of-mass energy of $\sqrt{s}$=13 $\text{TeV}$ recorded by the ATLAS detector at the LHC. The observed numbers of events are found to be in agreement with the background expectation from Standard Model processes. For a scalar Higgs boson with a mass of 125 $\text{GeV}$ and a Standard Model production cross section, an observed upper limit of $0.145$ is placed on the branching fraction of its decay into invisible particles at 95% confidence level, with an expected limit of $0.103$. These results are interpreted in the context of models where the Higgs boson acts as a portal to dark matter, and limits are set on the scattering cross section of weakly interacting massive particles and nucleons. Invisible decays of additional scalar bosons with masses from 50 $\text{GeV}$ to 2 $\text{TeV}$ are also studied, and the derived upper limits on the cross section times branching fraction decrease with increasing mass from 1.0 $\text{pb}$ for a scalar boson mass of 50 $\text{GeV}$ to 0.1 $\text{pb}$ at a mass of 2 $\text{TeV}$.
Yields after each selection criterion for a signal sample of an invisibly decaying Higgs boson produced in VBF and ggF for 139 $fb^{-1}$ of data. The lines 'Timing of j1/j2' are referring to requirements that are part of the jet cleaning, and which ensure that the timing of the two leading jets is compatible with the bunch crossing. The last sixteen rows show the yield in each SR bin and the efficiency with respect to the inclusive signal region.
The electroweak production of $Z(\nu\bar{\nu})\gamma$ in association with two jets is studied in a regime with a photon of high transverse momentum above 150 GeV using proton-proton collisions at a centre-of-mass energy of 13 TeV at the Large Hadron Collider. The analysis uses a data sample with an integrated luminosity of 139 fb$^{-1}$ collected by the ATLAS detector during the 2015-2018 LHC data-taking period. This process is an important probe of the electroweak symmetry breaking mechanism in the Standard Model and is sensitive to quartic gauge boson couplings via vector-boson scattering. The fiducial $Z(\nu\bar{\nu})\gamma jj$ cross section for electroweak production is measured to be 0.77$^{+0.34}_{-0.30}$ fb and is consistent with the Standard Model prediction. Evidence of electroweak $Z(\nu\bar{\nu})\gamma jj$ production is found with an observed significance of 3.2$\sigma$ for the background-only hypothesis, compared with an expected significance of 3.7$\sigma$. The combination of this result with the previously published ATLAS observation of electroweak $Z(\nu\bar{\nu})\gamma jj$ production yields an observed (expected) signal significance of 6.3$\sigma$ (6.6$\sigma$). Limits on anomalous quartic gauge boson couplings are obtained in the framework of effective field theory with dimension-8 operators.
These graphs indicate the effect of the main theory uncertainties, which are associated with the renormalisation and factorisation scales (dashed cyan), underlying event and parton showering (UE+PS) or generator choice (dash-dotted red), alternative PDF sets (dotted orange), combined NNPDF set variation and $\alpha_s$ uncertainty (loosely dash-dotted green). These are shown in the signal region for the $Z(\nu\bar{\nu})\gamma jj$ EWK process. The BDT classifier response was remapped into equal width bins for better representation. The uncertainty band corresponds to the uncertainty due to the limited number of MC events.
These graphs indicate the effect of the main theory uncertainties, which are associated with the renormalisation and factorisation scales (dashed cyan), underlying event and parton showering (UE+PS) or generator choice (dash-dotted red), alternative PDF sets (dotted orange), combined NNPDF set variation and $\alpha_{s}$ uncertainty (loosely dash-dotted green). These are shown in the signal region for the $Z(\nu\bar{\nu})\gamma jj$ QCD process. The BDT classifier response was remapped into equal width bins for better representation. The uncertainty band corresponds to the uncertainty due to the limited number of MC events.
The $m_{jj}$ distributions for the CRs and the BDT classifier response distribution for the SR after the fit in all regions. The dashed line shows the total background distribution before the fit. The vertical error bars on the data points correspond to the data's statistical uncertainty. Overflows are included in the last bin. The uncertainty band corresponds to the combination of the MC statistical uncertainty and systematic uncertainties obtained in the fit.
The $m_{jj}$ distributions for the CRs and the BDT classifier response distribution for the SR after the fit in all regions. The dashed line shows the total background distribution before the fit. The vertical error bars on the data points correspond to the data's statistical uncertainty. Overflows are included in the last bin. The uncertainty band corresponds to the combination of the MC statistical uncertainty and systematic uncertainties obtained in the fit.
The $m_{jj}$ distributions for the CRs and the BDT classifier response distribution for the SR after the fit in all regions. The dashed line shows the total background distribution before the fit. The vertical error bars on the data points correspond to the data's statistical uncertainty. Overflows are included in the last bin. The uncertainty band corresponds to the combination of the MC statistical uncertainty and systematic uncertainties obtained in the fit.
The $m_{jj}$ distributions for the CRs and the BDT classifier response distribution for the SR after the fit in all regions. The dashed line shows the total background distribution before the fit. The vertical error bars on the data points correspond to the data's statistical uncertainty. Overflows are included in the last bin. The uncertainty band corresponds to the combination of the MC statistical uncertainty and systematic uncertainties obtained in the fit.
Observed and expected event yields for the signal and all of the background processes considered in this analysis after the fit to the data in all of the regions. The uncertainty on the expected yield is the combination of statistical and systematic uncertainties obtained in the fit. The individual uncertainties can be correlated and do not necessarily add in quadrature to equal the total background uncertainty.
Summary of the event yield for processes in all regions, after the fit over all regions. The dashed line shows the total background distribution before the fit. The vertical error bars on the data points correspond to the data's statistical uncertainty. The uncertainty band corresponds to the combination of the MC statistical uncertainty and systematic uncertainties obtained in the fit.
Impact of different components of systematic uncertainty on the measured cross section, without taking into account the correlations. The impact is calculated by fixing the value of the corresponding nuisance parameters to the values obtained in the fit used to measure the cross section, performing the fit, estimating the signal strength uncertainty and subtracting it from the nominal uncertainty in quadrature.
Fitted POI values for this analysis, the previous ATLAS analysis, and their combination. The first and second columns present the values obtained in the individual analyses. The third column presents the values obtained in the combination.
Observed and expected one-dimensional limits on dimension 8 aQGC parameters. Limits are obtained by setting all aQGCs parameters except one to zero. Unitarity is not preserved.
Observed and expected one-dimensional limits on dimension 8 aQGC parameters in the region, where unitarity is preserved. Cutoff scales in MC, $E_{c}$, are given for each parameter. Limits are obtained by setting all aQGCs parameters except one to zero.
The $E_{T}^{\gamma}$ distribution in the SR after the fit in the control regions. The red (green) line shows the expected number of events in the case of non-zero EFT coefficient $f_{T0}/\Lambda^4$ ($f_{M0}/\Lambda^4$) with the value shown in the legend. The vertical error bars on the data points correspond to the data statistical uncertainty. Overflows are included in the last bin. The uncertainty band corresponds to the combination of the MC statistical uncertainty and systematic uncertainties obtained in the fit.
Evolution of the expected (red line) and observed (blue line) limits versus $E_{c}$ values for $f_{T0}/\Lambda^4$. The unitarity bound is shown by the black line. The $E_{c}<4$ TeV regime was obtained with $E_{T}^{\gamma} > 600$ GeV. The $E_{c} \geq 4$ TeV regime was obtained with $E_{T}^{\gamma} > 900$ GeV.
Evolution of the expected (red line) and observed (blue line) limits versus $E_{c}$ values for $f_{T5}/\Lambda^4$. The unitarity bound is shown by the black line. The $E_{c}<4$ TeV regime was obtained with $E_{T}^{\gamma} > 600$ GeV. The $E_{c} \geq 4$ TeV regime was obtained with $E_{T}^{\gamma} > 900$ GeV.
Evolution of the expected (red line) and observed (blue line) limits versus $E_{c}$ values for $f_{T8}/\Lambda^4$. The unitarity bound is shown by the black line. The $E_{c}<4$ TeV regime was obtained with $E_{T}^{\gamma} > 600$ GeV. The $E_{c} \geq 4$ TeV regime was obtained with $E_{T}^{\gamma} > 900$ GeV.
Evolution of the expected (red line) and observed (blue line) limits versus $E_{c}$ values for $f_{T9}/\Lambda^4$. The unitarity bound is shown by the black line. The $E_{c}<4$ TeV regime was obtained with $E_{T}^{\gamma} > 600$ GeV. The $E_{c} \geq 4$ TeV regime was obtained with $E_{T}^{\gamma} > 900$ GeV.
Evolution of the expected (red line) and observed (blue line) limits versus $E_{c}$ values for $f_{M0}/\Lambda^4$. The unitarity bound is shown by the black line. The $E_{c}<4$ TeV regime was obtained with $E_{T}^{\gamma} > 400$ GeV. The $E_{c} \geq 4$ TeV regime was obtained with $E_{T}^{\gamma} > 900$ GeV.
Evolution of the expected (red line) and observed (blue line) limits versus $E_{c}$ values for $f_{M1}/\Lambda^4$. The unitarity bound is shown by the black line. The $E_{c}<4$ TeV regime was obtained with $E_{T}^{\gamma} > 400$ GeV. The $E_{c} \geq 4$ TeV regime was obtained with $E_{T}^{\gamma} > 900$ GeV.
Evolution of the expected (red line) and observed (blue line) limits versus $E_{c}$ values for $f_{M2}/\Lambda^4$. The unitarity bound is shown by the black line. The $E_{c}<4$ TeV regime was obtained with $E_{T}^{\gamma} > 400$ GeV. The $E_{c} \geq 4$ TeV regime was obtained with $E_{T}^{\gamma} > 900$ GeV.
Correlation matrix of the parameters for the fit in all regions. Only parameters with absolute value of the correlation coefficient larger than 10 are shown.
A measurement of the energy asymmetry in jet-associated top-quark pair production is presented using 139 $\mathrm{fb}^{-1}$ of data collected by the ATLAS detector at the Large Hadron Collider during $pp$ collisions at $\sqrt{s}=13$ TeV. The observable measures the different probability of top and antitop quarks to have the higher energy as a function of the jet scattering angle with respect to the beam axis. The energy asymmetry is measured in the semileptonic $t\bar{t}$ decay channel, and the hadronically decaying top quark must have transverse momentum above $350$ GeV. The results are corrected for detector effects to particle level in three bins of the scattering angle of the associated jet. The measurement agrees with the SM prediction at next-to-leading-order accuracy in quantum chromodynamics in all three bins. In the bin with the largest expected asymmetry, where the jet is emitted perpendicular to the beam, the energy asymmetry is measured to be $-0.043\pm0.020$, in agreement with the SM prediction of $-0.037\pm0.003$. Interpreting this result in the framework of the Standard Model effective field theory (SMEFT), it is shown that the energy asymmetry is sensitive to the top-quark chirality in four-quark operators and is therefore a valuable new observable in global SMEFT fits.
Data Measurements and predictions of the energy asymmetry in three bins of the jet angle $\theta_j$. The SM prediction was obtained from simulations of $t\bar{t}j$ events with MadGraph5_aMC@NLO + Pythia 8 at NLO in QCD for $t\bar{t}j$ + PS, including MC statistical and scale uncertainties.
Data measurements and predictions of the energy asymmetry in three bins of the jet angle $\theta_j$. The SM prediction was obtained from simulations of $t\bar{t}j$ events with MadGraph5_aMC@NLO + Pythia 8 at NLO in QCD for $t\bar{t}j$ + PS, including MC statistical and scale uncertainties.
Correlation coefficients $\rho_{i,j}$ for the statistical and systematic uncertainties between the $i$-th and $j$-th bin of the differential $A_E$ measurement as a function of the jet scattering angle $\theta_j$
Correlation coefficients $\rho_{i,j}$ for the statistical and systematic uncertainties between the $i$-th and $j$-th bin of the differential $A_E$ measurement as a function of the jet scattering angle $\theta_j$
The effects on the energy asymmetry of $1\sigma$ variations in its influencing nuisance parameters for the three $\theta_j$ bins. These are extracted from the samples of the posterior distribution with $\sigma_i^{(j)} = c_{ij}/\sqrt{c_{jj}}$ being the estimated shift of bin $i$ in conjunction with a shift $\Delta\theta_j$ of nuisance parameter $j$. The data statistical (Data stat.) uncertainty is obtained from running the unfolding with all nuisance parameters being fixed to their post-marginalised values, the MC statistical uncertainty on the response matrix ($t\bar{t}$ response MC stat.) is evaluated using a bootstrapping method from the covariance matrix of the ensemble of repeated unfolding results with varied response matrices. The $\gamma$ variations denote the statistical uncertainties of the background predictions in the corresponding bin of the $\Delta E$ vs $\theta_{j}$ distribution. The numbers appended to the $W$+jets PDF variations denote the corresponding NNPDF3.0 PDF sets.
The effects on the energy asymmetry of $1\sigma$ variations in its influencing nuisance parameters for the three $\theta_j$ bins. These are extracted from the samples of the posterior distribution with $\sigma_i^{(j)} = c_{ij}/\sqrt{c_{jj}}$ being the estimated shift of bin $i$ in conjunction with a shift $\Delta\theta_j$ of nuisance parameter $j$. The data statistical (Data stat.) uncertainty is obtained from running the unfolding with all nuisance parameters being fixed to their post-marginalised values, the MC statistical uncertainty on the response matrix ($t\bar{t}$ response MC stat.) is evaluated using a bootstrapping method from the covariance matrix of the ensemble of repeated unfolding results with varied response matrices. The $\gamma$ variations denote the statistical uncertainties of the background predictions in the corresponding bin of the $\Delta E$ vs $\theta_{j}$ distribution. The numbers appended to the $W$+jets PDF variations denote the corresponding NNPDF3.0 PDF sets.
Covariances $c_{ij}$ for the highest ranked systematic uncertainties in the energy asymmetry measurement differential in $\theta_j$.
Covariances $c_{ij}$ for the highest ranked systematic uncertainties in the energy asymmetry measurement differential in $\theta_j$.
Definition of the fiducial phase space with lepton candidate ($\ell$), hadronic top candidate ($j_h$), leptonic top candidate ($j_l$) and associated jet candidate ($j_a$).
Definition of the fiducial phase space with lepton candidate ($\ell$), hadronic top candidate ($j_h$), leptonic top candidate ($j_l$) and associated jet candidate ($j_a$).
Bounds on individual Wilson coefficients $C($TeV$/\Lambda)^2$ from the energy asymmetry, obtained from a combined fit to its values in all three $\theta_j$ bins.
Bounds on individual Wilson coefficients $C($TeV$/\Lambda)^2$ from the energy asymmetry, obtained from a combined fit to its values in all three $\theta_j$ bins.
This paper presents a search for hypothetical massive, charged, long-lived particles with the ATLAS detector at the LHC using an integrated luminosity of 139 fb$^{-1}$ of proton-proton collisions at $\sqrt{s}=13$ TeV. These particles are expected to move significantly slower than the speed of light and should be identifiable by their high transverse momenta and anomalously large specific ionisation losses, ${\mathrm{d}}E/\mathrm{d}x$. Trajectories reconstructed solely by the inner tracking system and a ${\mathrm{d}}E/\mathrm{d}x$ measurement in the pixel detector layers provide sensitivity to particles with lifetimes down to ${\cal O}(1)$$\text{ns}$ with a mass, measured using the Bethe--Bloch relation, ranging from 100 GeV to 3 TeV. Interpretations for pair-production of $R$-hadrons, charginos and staus in scenarios of supersymmetry compatible with these particles being long-lived are presented, with mass limits extending considerably beyond those from previous searches in broad ranges of lifetime.
Comparison of the observed and expected VAR distributionsin VR-LowPt-Inclusive_High. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.
Comparison of the observed and expected VAR distributionsin VR-HiEta-Inclusive. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.
The observed mass distribution in the SR-Inclusive_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed mass distribution in the SR-Inclusive_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
List of expected and observed events, $p_{0}$-value and the corresponding $Z$ local significance, as well as the 95% CLs upper limit of the expected and observed signal events ($S^{95}_ ext{exp} and $S^{95}_ ext{obs}$ ) in each mass window for SR-Inclusive bins of the short lifetime regime.
List of expected and observed events, $p_{0}$-value and the corresponding $Z$ local significance, as well as the 95% CLs upper limit of the expected and observed signal events ($S^{95}_ ext{exp} and $S^{95}_ ext{obs}$ ) in each mass window for SR-Inclusive bins of the long lifetime regime.
The observed $p_{\rm T$ distribution in the SR-Inclusive_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed $p_{\rm T$ distribution in the SR-Inclusive_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed $|\eta|$ distribution in the SR-Inclusive_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed $|\eta|$ distribution in the SR-Inclusive_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed dE/dx distribution in the SR-Inclusive_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed dE/dx distribution in the SR-Inclusive_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed mass distribution in the SR-Trk-IBL0_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed mass distribution in the SR-Mu-IBL0_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed mass distribution in the SR-Trk-IBL0_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed mass distribution in the SR-Mu-IBL0_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed mass distribution in the SR-Trk-IBL1 signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed mass distribution in the SR-Mu-IBL1 signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
Lower limits on the gluino mass, from gluino $R$-hadron pair production, as a function of gluino lifetime for two neutralino mass assumptions of (a) $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$ and (b) $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$. The upper $1 \sigma_\text{exp}$ expected bound is very close to the expected limit for some lifetime values due to the expected background getting very close to 0 events.
Lower limits on the gluino mass, from gluino $R$-hadron pair production, as a function of gluino lifetime for two neutralino mass assumptions of (a) $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$ and (b) $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$. The upper $1 \sigma_\text{exp}$ expected bound is very close to the expected limit for some lifetime values due to the expected background getting very close to 0 events.
Lower limits on the gluino mass, from gluino $R$-hadron pair production, as a function of gluino lifetime for two neutralino mass assumptions of (a) $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$ and (b) $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$. The upper $1 \sigma_\text{exp}$ expected bound is very close to the expected limit for some lifetime values due to the expected background getting very close to 0 events.
Lower limits on the gluino mass, from gluino $R$-hadron pair production, as a function of gluino lifetime for two neutralino mass assumptions of (a) $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$ and (b) $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$. The upper $1 \sigma_\text{exp}$ expected bound is very close to the expected limit for some lifetime values due to the expected background getting very close to 0 events.
(a) Lower limits on the chargino mass as a function of lifetime, and (b) the contours around the excluded mass-lifetime region for stau pair production.
(a) Lower limits on the chargino mass as a function of lifetime, and (b) the contours around the excluded mass-lifetime region for stau pair production.
(a) Lower limits on the chargino mass as a function of lifetime, and (b) the contours around the excluded mass-lifetime region for stau pair production.
(a) Lower limits on the chargino mass as a function of lifetime, and (b) the contours around the excluded mass-lifetime region for stau pair production.
Comparison of the observed and expected VAR distributionsin VR-LowPt-Trk-IBL0_Low. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.
Comparison of the observed and expected VAR distributionsin VR-LowPt-Mu-IBL0_Low. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.
Comparison of the observed and expected VAR distributionsin VR-LowPt-Trk-IBL0_High. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.
Comparison of the observed and expected VAR distributionsin VR-LowPt-Mu-IBL0_High. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.
Comparison of the observed and expected VAR distributionsin VR-LowPt-Trk-IBL1. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.
Comparison of the observed and expected VAR distributionsin VR-LowPt-Mu-IBL1. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.
Comparison of the observed and expected VAR distributionsin VR-HiEta-Trk-IBL0_Low. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.
Comparison of the observed and expected VAR distributionsin VR-HiEta-Mu-IBL0_Low. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.
Comparison of the observed and expected VAR distributionsin VR-HiEta-Trk-IBL0_High. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.
Comparison of the observed and expected VAR distributionsin VR-HiEta-Mu-IBL0_High. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.
Comparison of the observed and expected VAR distributionsin VR-HiEta-Trk-IBL1. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.
Comparison of the observed and expected VAR distributionsin VR-HiEta-Mu-IBL1. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.
The observed $p_{\rm T$ distribution in the SR-Trk-IBL0_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed $p_{\rm T$ distribution in the SR-Mu-IBL0_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed $p_{\rm T$ distribution in the SR-Trk-IBL0_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed $p_{\rm T$ distribution in the SR-Mu-IBL0_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed $p_{\rm T$ distribution in the SR-Trk-IBL1 signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed $p_{\rm T$ distribution in the SR-Mu-IBL1 signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed dE/dx distribution in the SR-Trk-IBL0_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed dE/dx distribution in the SR-Mu-IBL0_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed dE/dx distribution in the SR-Trk-IBL0_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed dE/dx distribution in the SR-Mu-IBL0_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed dE/dx distribution in the SR-Trk-IBL1 signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed dE/dx distribution in the SR-Mu-IBL1 signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
Expected and observed distributions in SR-Inclusive_Low of missing transverse momentum. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
Expected and observed distributions in SR-Inclusive_High of missing transverse momentum. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
Expected and observed distributions in SR-Inclusive_Low of relative phi-angle between pTmiss and the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
Expected and observed distributions in SR-Inclusive_High of relative phi-angle between pTmiss and the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
Expected and observed distributions in SR-Inclusive_Low of the transverse mass of pTmiss and the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
Expected and observed distributions in SR-Inclusive_High of the transverse mass of pTmiss and the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
Expected and observed distributions in SR-Inclusive_Low of the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
Expected and observed distributions in SR-Inclusive_High of the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
Expected and observed distributions in SR-Inclusive_Low of the relative phi-angle between the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track, and the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
Expected and observed distributions in SR-Inclusive_High of the relative phi-angle between the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track, and the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
Expected and observed distributions in SR-Inclusive_Low of the relative phi-angle between pTmiss and the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
Expected and observed distributions in SR-Inclusive_High of the relative phi-angle between pTmiss and the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
Expected and observed distributions in SR-Inclusive_Low of the transverse mass of pTmiss and the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
Expected and observed distributions in SR-Inclusive_High of the transverse mass of pTmiss and the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
Expected and observed distributions in SR-Inclusive_Low of the effective mass, defined as the scalar sum pT of the signal candidate track, jets satisfying pT > 30 GeV, excluding ones within deltaR < 0.4 with respect to the signal candidate track, and pTmiss. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
Expected and observed distributions in SR-Inclusive_High of the effective mass, defined as the scalar sum pT of the signal candidate track, jets satisfying pT > 30 GeV, excluding ones within deltaR < 0.4 with respect to the signal candidate track, and pTmiss. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
The expected upper limits on cross-section for gluinos with $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$, with lifetime with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.
The expected upper limits on cross-section for gluinos with $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$, with lifetime with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.
The expected upper limits on cross-section for gluinos with $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$, with lifetime with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.
The expected upper limits on cross-section for gluinos with $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$, with lifetime with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.
The expected upper limits on cross-section for gluinos with $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$, with lifetime with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.
The expected upper limits on cross-section for gluinos with $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$, with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, and (d) 30 ns.
The expected upper limits on cross-section for gluinos with $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$, with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, and (d) 30 ns.
The expected upper limits on cross-section for gluinos with $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$, with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, and (d) 30 ns.
The expected upper limits on cross-section for gluinos with $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$, with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, and (d) 30 ns.
The expected upper limits on cross-section for charginos with lifetime (c) 10 ns, (d) 30 ns, and (e) stable.
The expected upper limits on cross-section for charginos with lifetime (c) 10 ns, (d) 30 ns, and (e) stable.
The expected upper limits on cross-section for charginos with lifetime (c) 10 ns, (d) 30 ns, and (e) stable.
The expected upper limits on cross-section for charginos with lifetime (c) 10 ns, (d) 30 ns, and (e) stable.
The expected upper limits on cross-section for charginos with lifetime (c) 10 ns, (d) 30 ns, and (e) stable.
The expected upper limits on cross-section for sleptons with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.
The expected upper limits on cross-section for sleptons with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.
The expected upper limits on cross-section for sleptons with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.
The expected upper limits on cross-section for sleptons with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.
The expected upper limits on cross-section for sleptons with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.
Muon reconstruction efficiency as a function of β and |η| for (a) stable charginos and (b) stable charged R-hadrons. For weakly interacting LLPs with calorimeter materials the efficiency for the chargino is recommended to refer to. The muon reconstruction efficiency for R-hadrons is significantly lower due to having QCD interactions with materials.
Muon reconstruction efficiency as a function of β and |η| for (a) stable charginos and (b) stable charged R-hadrons. For weakly interacting LLPs with calorimeter materials the efficiency for the chargino is recommended to refer to. The muon reconstruction efficiency for R-hadrons is significantly lower due to having QCD interactions with materials.
Trigger and event selection efficiencies. The band on the marker indicates a typical size of fluctuation by the LLP mass and lifetime observed by the samples used in efficiency derivation, but it does not indicate the full envelope of model dependence.
Trigger and event selection efficiencies. The band on the marker indicates a typical size of fluctuation by the LLP mass and lifetime observed by the samples used in efficiency derivation, but it does not indicate the full envelope of model dependence.
Signal track selection efficiency as a function of CLLP $\beta\gamma$ for SR-Inclusive_Low and SR-Inclusive_High bins. The band on the marker indicates a typical size of fluctuation by the LLP mass and lifetime observed by the samples used in efficiency derivation, but it does not indicate the full envelope of model dependence.
Signal selection efficiency by the mass window for SR-Inclusive_Low and SR-Inclusive_High bins.
Acceptance for the R-hadron pair-production model with m(N1) = 100 GeV for various masses and lifetimes. The acceptance is defined as the fraction of events having at least one charged LLP satisfying pT > 120 GeV, |\eta| < 1.8 and r_decay > 500 mm.
Acceptance for the R-hadron pair-production model with DeltaM(gluino, N1) = 30 GeV for various masses and lifetimes. The acceptance is defined as the fraction of events having at least one charged LLP satisfying pT > 120 GeV, |eta| < 1.8 and r_decay > 500 mm.
Acceptance for the chargino pair-production model for various masses and lifetimes. The acceptance is defined as the fraction of events having at least one charged LLP satisfying pT > 120 GeV, |\eta| < 1.8 and r_decay > 500 mm.
Acceptance for the stau pair-production model for various masses and lifetimes. The acceptance is defined as the fraction of events having at least one charged LLP satisfying pT > 120 GeV, |\eta| < 1.8 and r_decay > 500 mm.
Event-level efficiency for the R-hadron pair-production model with m(N1) = 100 GeV for various masses and lifetimes. The efficiency is defined as the fraction of events satisfying the selection of trigger, event and jet cleaning, ETmiss and primary vertex requirements per events satisfying the acceptance criteria.
Event-level efficiency for the R-hadron pair-production model with DeltaM(gluino, N1) = 30 GeV for various masses and lifetimes. The efficiency is defined as the fraction of events satisfying the selection of trigger, event and jet cleaning, ETmiss and primary vertex requirements per events satisfying the acceptance criteria.
Event-level efficiency for the chargino pair-production model for various masses and lifetimes. The efficiency is defined as the fraction of events satisfying the selection of trigger, event and jet cleaning, ETmiss and primary vertex requirements per events satisfying the acceptance criteria.
Event-level efficiency for the stau pair-production model for various masses and lifetimes. The efficiency is defined as the fraction of events satisfying the selection of trigger, event and jet cleaning, ETmiss and primary vertex requirements per events satisfying the acceptance criteria.
Efficiency of SR-Inclusive_Highfor the R-hadron pair-production model with m(N1) = 100 GeV for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.
Efficiency of SR-Inclusive_Highfor the R-hadron pair-production model with DeltaM(gluino, N1) = 30 GeV for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.
Efficiency of SR-Inclusive_Highfor the chargino pair-production model for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.
Efficiency of SR-Inclusive_Highfor the stau pair-production model for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.
Efficiency of SR-Inclusive_Low for the R-hadron pair-production model with m(N1) = 100 GeV for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.
Efficiency of SR-Inclusive_Low for the R-hadron pair-production model with DeltaM(gluino, N1) = 30 GeV for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.
Efficiency of SR-Inclusive_Low for the chargino pair-production model for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.
Efficiency of SR-Inclusive_Low for the stau pair-production model for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.
Passing events in event selection steps for the R-hadron pair-production model with m(N1) = 100 GeV for various masses and lifetimes.
Passing events in event selection steps for the R-hadron pair-production model with DeltaM(gluino, N1) = 30 GeV for various masses and lifetimes.
Passing events in event selection steps for the chargino pair-production model for various masses and lifetimes.
Passing events in event selection steps for the stau pair-production model for various masses and lifetimes.
Measurements of single-, double-, and triple-differential cross-sections are presented for boosted top-quark pair-production in 13 $\text{TeV}$ proton-proton collisions recorded by the ATLAS detector at the LHC. The top quarks are observed through their hadronic decay and reconstructed as large-radius jets with the leading jet having transverse momentum ($p_{\text{T}}$) greater than 500 GeV. The observed data are unfolded to remove detector effects. The particle-level cross-section, multiplied by the $t\bar{t} \rightarrow W W b \bar{b}$ branching fraction and measured in a fiducial phase space defined by requiring the leading and second-leading jets to have $p_{\text{T}} > 500$ GeV and $p_{\text{T}} > 350$ GeV, respectively, is $331 \pm 3 \text{(stat.)} \pm 39 \text{(syst.)}$ fb. This is approximately 20$\%$ lower than the prediction of $398^{+48}_{-49}$ fb by Powheg+Pythia 8 with next-to-leading-order (NLO) accuracy but consistent within the theoretical uncertainties. Results are also presented at the parton level, where the effects of top-quark decay, parton showering, and hadronization are removed such that they can be compared with fixed-order next-to-next-to-leading-order (NNLO) calculations. The parton-level cross-section, measured in a fiducial phase space similar to that at particle level, is $1.94 \pm 0.02 \text{(stat.)} \pm 0.25 \text{(syst.)}$ pb. This agrees with the NNLO prediction of $1.96^{+0.02}_{-0.17}$ pb. Reasonable agreement with the differential cross-sections is found for most NLO models, while the NNLO calculations are generally in better agreement with the data. The differential cross-sections are interpreted using a Standard Model effective field-theory formalism and limits are set on Wilson coefficients of several four-fermion operators.
Fiducial phase-space cross-section at particle level.
$p_{T}^{t}$ absolute differential cross-section at particle level.
$|y^{t}|$ absolute differential cross-section at particle level.
$p_{T}^{t,1}$ absolute differential cross-section at particle level.
$|{y}^{t,1}|$ absolute differential cross-section at particle level.
$p_{T}^{t,2}$ absolute differential cross-section at particle level.
$|{y}^{t,2}|$ absolute differential cross-section at particle level.
$m^{t\bar{t}}$ absolute differential cross-section at particle level.
$p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level.
$|y^{t\bar{t}}|$ absolute differential cross-section at particle level.
$\chi^{t\bar{t}}$ absolute differential cross-section at particle level.
$|y_{B}^{t\bar{t}}|$ absolute differential cross-section at particle level.
$|p_{out}^{t\bar{t}}|$ absolute differential cross-section at particle level.
$|\Delta \phi(t_{1}, t_{2})|$ absolute differential cross-section at particle level.
$H_{T}^{t\bar{t}}$ absolute differential cross-section at particle level.
$|\cos\theta^{*}|$ absolute differential cross-section at particle level.
$p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level, for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV.
$p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level, for 0.55 TeV < $p_{T}^{t,1}$ < 0.6 TeV.
$p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level, for 0.6 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
$p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level, for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
$|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at particle level, for 0 < $|{y}^{t,1}|$ < 0.2.
$|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at particle level, for 0.2 < $|{y}^{t,1}|$ < 0.5.
$|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at particle level, for 0.5 < $|{y}^{t,1}|$ < 1.
$|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at particle level, for 1 < $|{y}^{t,1}|$ < 2.
$|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level, for 0 < $|{y}^{t,1}|$ < 0.2.
$|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level, for 0.2 < $|{y}^{t,1}|$ < 0.5.
$|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level, for 0.5 < $|{y}^{t,1}|$ < 1.
$|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level, for 1 < $|{y}^{t,1}|$ < 2.
$|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level, for 0 < $|{y}^{t,2}|$ < 0.2.
$|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level, for 0.2 < $|{y}^{t,2}|$ < 0.5.
$|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level, for 0.5 < $|{y}^{t,2}|$ < 1.
$|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level, for 1 < $|{y}^{t,2}|$ < 2.
$p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level, for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV.
$p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level, for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV.
$p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level, for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
$p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level, for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
$p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level, for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV.
$p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level, for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV.
$p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level, for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
$p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level, for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level, for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level, for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level, for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level, for 1 < $|{y}^{t\bar{t}}|$ < 2.
$|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at particle level, for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
$|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at particle level, for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
$|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at particle level, for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
$|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at particle level, for 1 < $|{y}^{t\bar{t}}|$ < 2.
$|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level, for 0 < $|{y}^{t,1}|$ < 0.2.
$|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level, for 0.2 < $|{y}^{t,1}|$ < 0.5.
$|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level, for 0.5 < $|{y}^{t,1}|$ < 1.
$|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level, for 1 < $|{y}^{t,1}|$ < 2.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level, for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level, for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level, for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level, for 1 < $|{y}^{t\bar{t}}|$ < 2.
$p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level, for 0 TeV < $p_{T}^{t\bar{t}}$ < 0.1 TeV.
$p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level, for 0.1 TeV < $p_{T}^{t\bar{t}}$ < 0.2 TeV.
$p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level, for 0.2 TeV < $p_{T}^{t\bar{t}}$ < 0.35 TeV.
$p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level, for 0.35 TeV < $p_{T}^{t\bar{t}}$ < 1 TeV.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level, for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level, for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level, for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level, for 1 < $|{y}^{t\bar{t}}|$ < 2.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level, for 0 < $|{y}^{t\bar{t}}|$ < 0.3 and 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level, for 0 < $|{y}^{t\bar{t}}|$ < 0.3 and 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level, for 0 < $|{y}^{t\bar{t}}|$ < 0.3 and 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level, for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9 and 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level, for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9 and 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level, for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9 and 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level, for 0.9 < $|{y}^{t\bar{t}}|$ < 2 and 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level, for 0.9 < $|{y}^{t\bar{t}}|$ < 2 and 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level, for 0.9 < $|{y}^{t\bar{t}}|$ < 2 and 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
$p_{T}^{t}$ normalized differential cross-section at particle level.
$|y^{t}|$ normalized differential cross-section at particle level.
$p_{T}^{t,1}$ normalized differential cross-section at particle level.
$|{y}^{t,1}|$ normalized differential cross-section at particle level.
$p_{T}^{t,2}$ normalized differential cross-section at particle level.
$|{y}^{t,2}|$ normalized differential cross-section at particle level.
$m^{t\bar{t}}$ normalized differential cross-section at particle level.
$p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level.
$|y^{t\bar{t}}|$ normalized differential cross-section at particle level.
$\chi^{t\bar{t}}$ normalized differential cross-section at particle level.
$|y_{B}^{t\bar{t}}|$ normalized differential cross-section at particle level.
$|p_{out}^{t\bar{t}}|$ normalized differential cross-section at particle level.
$|\Delta \phi(t_{1}, t_{2})|$ normalized differential cross-section at particle level.
$H_{T}^{t\bar{t}}$ normalized differential cross-section at particle level.
$|\cos\theta^{*}|$ normalized differential cross-section at particle level.
$p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level, for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV.
$p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level, for 0.55 TeV < $p_{T}^{t,1}$ < 0.6 TeV.
$p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level, for 0.6 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
$p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level, for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
$|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at particle level, for 0 < $|{y}^{t,1}|$ < 0.2.
$|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at particle level, for 0.2 < $|{y}^{t,1}|$ < 0.5.
$|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at particle level, for 0.5 < $|{y}^{t,1}|$ < 1.
$|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at particle level, for 1 < $|{y}^{t,1}|$ < 2.
$|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level, for 0 < $|{y}^{t,1}|$ < 0.2.
$|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level, for 0.2 < $|{y}^{t,1}|$ < 0.5.
$|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level, for 0.5 < $|{y}^{t,1}|$ < 1.
$|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level, for 1 < $|{y}^{t,1}|$ < 2.
$|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level, for 0 < $|{y}^{t,2}|$ < 0.2.
$|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level, for 0.2 < $|{y}^{t,2}|$ < 0.5.
$|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level, for 0.5 < $|{y}^{t,2}|$ < 1.
$|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level, for 1 < $|{y}^{t,2}|$ < 2.
$p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level, for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV.
$p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level, for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV.
$p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level, for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
$p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level, for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
$p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level, for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV.
$p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level, for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV.
$p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level, for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
$p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level, for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level, for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level, for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level, for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level, for 1 < $|{y}^{t\bar{t}}|$ < 2.
$|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at particle level, for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
$|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at particle level, for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
$|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at particle level, for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
$|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at particle level, for 1 < $|{y}^{t\bar{t}}|$ < 2.
$|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level, for 0 < $|{y}^{t,1}|$ < 0.2.
$|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level, for 0.2 < $|{y}^{t,1}|$ < 0.5.
$|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level, for 0.5 < $|{y}^{t,1}|$ < 1.
$|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level, for 1 < $|{y}^{t,1}|$ < 2.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level, for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level, for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level, for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level, for 1 < $|{y}^{t\bar{t}}|$ < 2.
$p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level, for 0 TeV < $p_{T}^{t\bar{t}}$ < 0.1 TeV.
$p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level, for 0.1 TeV < $p_{T}^{t\bar{t}}$ < 0.2 TeV.
$p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level, for 0.2 TeV < $p_{T}^{t\bar{t}}$ < 0.35 TeV.
$p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level, for 0.35 TeV < $p_{T}^{t\bar{t}}$ < 1 TeV.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level, for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level, for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level, for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level, for 1 < $|{y}^{t\bar{t}}|$ < 2.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level, for 0 < $|{y}^{t\bar{t}}|$ < 0.3 and 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level, for 0 < $|{y}^{t\bar{t}}|$ < 0.3 and 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level, for 0 < $|{y}^{t\bar{t}}|$ < 0.3 and 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level, for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9 and 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level, for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9 and 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level, for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9 and 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level, for 0.9 < $|{y}^{t\bar{t}}|$ < 2 and 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level, for 0.9 < $|{y}^{t\bar{t}}|$ < 2 and 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level, for 0.9 < $|{y}^{t\bar{t}}|$ < 2 and 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Fiducial phase-space cross-section at parton level.
$p_{T}^{t}$ absolute differential cross-section at parton level.
$|y^{t}|$ absolute differential cross-section at parton level.
$p_{T}^{t,1}$ absolute differential cross-section at parton level.
$|y^{t,1}|$ absolute differential cross-section at parton level.
$p_{T}^{t,2}$ absolute differential cross-section at parton level.
$|{y}^{t,2}|$ absolute differential cross-section at parton level.
$m^{t\bar{t}}$ absolute differential cross-section at parton level.
$p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level.
$|{y}^{t\bar{t}}|$ absolute differential cross-section at parton level.
${\chi}^{t\bar{t}}$ absolute differential cross-section at parton level.
$|y_{B}^{t\bar{t}}|$ absolute differential cross-section at parton level.
$|p_{out}^{t\bar{t}}|$ absolute differential cross-section at parton level.
$|\Delta \phi(t_{1}, t_{2})|$ absolute differential cross-section at parton level.
$H_{T}^{t\bar{t}}$ absolute differential cross-section at parton level.
$|\cos\theta^{*}|$ absolute differential cross-section at parton level.
$p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level, for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV.
$p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level, for 0.55 TeV < $p_{T}^{t,1}$ < 0.6 TeV.
$p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level, for 0.6 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
$p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level, for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
$|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at parton level, for 0 < $|{y}^{t,1}|$ < 0.2.
$|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at parton level, for 0.2 < $|{y}^{t,1}|$ < 0.5.
$|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at parton level, for 0.5 < $|{y}^{t,1}|$ < 1.
$|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at parton level, for 1 < $|{y}^{t,1}|$ < 2.
$|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level, for 0 < $|{y}^{t,1}|$ < 0.2.
$|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level, for 0.2 < $|{y}^{t,1}|$ < 0.5.
$|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level, for 0.5 < $|{y}^{t,1}|$ < 1.
$|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level, for 1 < $|{y}^{t,1}|$ < 2.
$|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level, for 0 < $|{y}^{t,2}|$ < 0.2.
$|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level, for 0.2 < $|{y}^{t,2}|$ < 0.5.
$|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level, for 0.5 < $|{y}^{t,2}|$ < 1.
$|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level, for 1 < $|{y}^{t,2}|$ < 2.
$p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level, for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV.
$p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level, for 0.5 TeV < $p_{T}^{t,1}$ < 0.625 TeV.
$p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level, for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
$p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level, for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
$p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level, for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV.
$p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level, for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV.
$p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level, for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
$p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level, for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level, for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level, for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level, for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level, for 1 < $|{y}^{t\bar{t}}|$ < 2.
$|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at parton level, for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
$|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at parton level, for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
$|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at parton level, for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
$|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at parton level, for 1 < $|{y}^{t\bar{t}}|$ < 2.
$|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level, for 0 < $|{y}^{t,1}|$ < 0.2.
$|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level, for 0.2 < $|{y}^{t,1}|$ < 0.5.
$|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level, for 0.5 < $|{y}^{t,1}|$ < 1.
$|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level, for 1 < $|{y}^{t,1}|$ < 2.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level, for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level, for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level, for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level, for 1 < $|{y}^{t\bar{t}}|$ < 2.
$p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level, for 0 TeV < $p_{T}^{t\bar{t}}$ < 0.1 TeV.
$p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level, for 0.1 TeV < $p_{T}^{t\bar{t}}$ < 0.2 TeV.
$p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level, for 0.2 TeV < $p_{T}^{t\bar{t}}$ < 0.35 TeV.
$p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level, for 0.35 TeV < $p_{T}^{t\bar{t}}$ < 1 TeV.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level, for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level, for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level, for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level, for 1 < $|{y}^{t\bar{t}}|$ < 2.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level, for 0 < $|{y}^{t\bar{t}}|$ < 0.3 and 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level, for 0 < $|{y}^{t\bar{t}}|$ < 0.3 and 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level, for 0 < $|{y}^{t\bar{t}}|$ < 0.3 and 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level, for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9 and 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level, for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9 and 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level, for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9 and 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level, for 0.9 < $|{y}^{t\bar{t}}|$ < 2 and 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level, for 0.9 < $|{y}^{t\bar{t}}|$ < 2 and 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level, for 0.9 < $|{y}^{t\bar{t}}|$ < 2 and 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
$p_{T}^{t}$ normalized differential cross-section at parton level.
$|y^{t}|$ normalized differential cross-section at parton level.
$p_{T}^{t,1}$ normalized differential cross-section at parton level.
$|y^{t,1}|$ normalized differential cross-section at parton level.
$p_{T}^{t,2}$ normalized differential cross-section at parton level.
$|{y}^{t,2}|$ normalized differential cross-section at parton level.
$m^{t\bar{t}}$ normalized differential cross-section at parton level.
$p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level.
$|{y}^{t\bar{t}}|$ normalized differential cross-section at parton level.
${\chi}^{t\bar{t}}$ normalized differential cross-section at parton level.
$|y_{B}^{t\bar{t}}|$ normalized differential cross-section at parton level.
$|p_{out}^{t\bar{t}}|$ normalized differential cross-section at parton level.
$|\Delta \phi(t_{1}, t_{2})|$ normalized differential cross-section at parton level.
$H_{T}^{t\bar{t}}$ normalized differential cross-section at parton level.
$|\cos\theta^{*}|$ normalized differential cross-section at parton level.
$p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level, for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV.
$p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level, for 0.55 TeV < $p_{T}^{t,1}$ < 0.6 TeV.
$p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level, for 0.6 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
$p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level, for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
$|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at parton level, for 0 < $|{y}^{t,1}|$ < 0.2.
$|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at parton level, for 0.2 < $|{y}^{t,1}|$ < 0.5.
$|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at parton level, for 0.5 < $|{y}^{t,1}|$ < 1.
$|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at parton level, for 1 < $|{y}^{t,1}|$ < 2.
$|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level, for 0 < $|{y}^{t,1}|$ < 0.2.
$|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level, for 0.2 < $|{y}^{t,1}|$ < 0.5.
$|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level, for 0.5 < $|{y}^{t,1}|$ < 1.
$|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level, for 1 < $|{y}^{t,1}|$ < 2.
$|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level, for 0 < $|{y}^{t,2}|$ < 0.2.
$|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level, for 0.2 < $|{y}^{t,2}|$ < 0.5.
$|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level, for 0.5 < $|{y}^{t,2}|$ < 1.
$|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level, for 1 < $|{y}^{t,2}|$ < 2.
$p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level, for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV.
$p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level, for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV.
$p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level, for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
$p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level, for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
$p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level, for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV.
$p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level, for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV.
$p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level, for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
$p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level, for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level, for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level, for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level, for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level, for 1 < $|{y}^{t\bar{t}}|$ < 2.
$|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at parton level, for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
$|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at parton level, for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
$|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at parton level, for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
$|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at parton level, for 1 < $|{y}^{t\bar{t}}|$ < 2.
$|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level, for 0 < $|{y}^{t,1}|$ < 0.2.
$|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level, for 0.2 < $|{y}^{t,1}|$ < 0.5.
$|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level, for 0.5 < $|{y}^{t,1}|$ < 1.
$|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level, for 1 < $|{y}^{t,1}|$ < 2.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level, for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level, for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level, for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level, for 1 < $|{y}^{t\bar{t}}|$ < 2.
$p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level, for 0 TeV < $p_{T}^{t\bar{t}}$ < 0.1 TeV.
$p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level, for 0.1 TeV < $p_{T}^{t\bar{t}}$ < 0.2 TeV.
$p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level, for 0.2 TeV < $p_{T}^{t\bar{t}}$ < 0.35 TeV.
$p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level, for 0.35 TeV < $p_{T}^{t\bar{t}}$ < 1 TeV.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level, for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level, for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level, for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
$|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level, for 1 < $|{y}^{t\bar{t}}|$ < 2.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level, for 0 < $|{y}^{t\bar{t}}|$ < 0.3 and 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level, for 0 < $|{y}^{t\bar{t}}|$ < 0.3 and 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level, for 0 < $|{y}^{t\bar{t}}|$ < 0.3 and 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level, for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9 and 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level, for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9 and 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level, for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9 and 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level, for 0.9 < $|{y}^{t\bar{t}}|$ < 2 and 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level, for 0.9 < $|{y}^{t\bar{t}}|$ < 2 and 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
$|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level, for 0.9 < $|{y}^{t\bar{t}}|$ < 2 and 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
$p_{T}^{t}$ covariance matrix for the absolute differential cross-section at particle level.
$|{y}^{t}|$ covariance matrix for the absolute differential cross-section at particle level.
$p_{T}^{t,1}$ covariance matrix for the absolute differential cross-section at particle level.
$|{y}^{t,1}|$ covariance matrix for the absolute differential cross-section at particle level.
$p_{T}^{t,2}$ covariance matrix for the absolute differential cross-section at particle level.
$|{y}^{t,2}|$ covariance matrix for the absolute differential cross-section at particle level.
$m^{t\bar{t}}$ covariance matrix for the absolute differential cross-section at particle level.
$p_{T}^{t\bar{t}}$ covariance matrix for the absolute differential cross-section at particle level.
$|y^{t\bar{t}}|$ covariance matrix for the absolute differential cross-section at particle level.
$\chi^{t\bar{t}}$ covariance matrix for the absolute differential cross-section at particle level.
$|y_{B}^{t\bar{t}}|$ covariance matrix for the absolute differential cross-section at particle level.
$|p_{out}^{t\bar{t}}|$ covariance matrix for the absolute differential cross-section at particle level.
$|\Delta \phi(t_{1}, t_{2})|$ covariance matrix for the absolute differential cross-section at particle level.
$H_{T}^{t\bar{t}}$ covariance matrix for the absolute differential cross-section at particle level.
$|\cos\theta^{*}|$ covariance matrix for the absolute differential cross-section at particle level.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0.55 TeV < $p_{T}^{t,1}$ < 0.6 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0.6 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0.55 TeV < $p_{T}^{t,1}$ < 0.6 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0.55 TeV < $p_{T}^{t,1}$ < 0.6 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0.55 TeV < $p_{T}^{t,1}$ < 0.6 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0.6 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0.55 TeV < $p_{T}^{t,1}$ < 0.6 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0.6 TeV < $p_{T}^{t,1}$ < 0.75 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0.6 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0.6 TeV < $p_{T}^{t,1}$ < 0.75 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at particle level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at particle level for 0 < $|{y}^{t,1}|$ < 0.2.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at particle level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t,1}|$ < 0.5.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at particle level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at particle level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at particle level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t,1}|$ < 0.5.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at particle level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t,1}|$ < 1 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t,1}|$ < 1 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at particle level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at particle level for 1 < $|{y}^{t,1}|$ < 2 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at particle level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t,1}|$ < 0.2.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t,1}|$ < 0.5.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t,1}|$ < 0.5.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t,1}|$ < 1 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t,1}|$ < 1 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 1 < $|{y}^{t,1}|$ < 2 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0 < $|{y}^{t,2}|$ < 0.2 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0 < $|{y}^{t,2}|$ < 0.2.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0 < $|{y}^{t,2}|$ < 0.2 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t,2}|$ < 0.5.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0 < $|{y}^{t,2}|$ < 0.2 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t,2}|$ < 1.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0 < $|{y}^{t,2}|$ < 0.2 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 1 < $|{y}^{t,2}|$ < 2.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t,2}|$ < 0.5 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t,2}|$ < 0.5.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t,2}|$ < 0.5 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t,2}|$ < 1.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t,2}|$ < 0.5 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 1 < $|{y}^{t,2}|$ < 2.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t,2}|$ < 1 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t,2}|$ < 1.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t,2}|$ < 1 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 1 < $|{y}^{t,2}|$ < 2.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 1 < $|{y}^{t,2}|$ < 2 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at particle level for 1 < $|{y}^{t,2}|$ < 2.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0 < $|{y}^{t,1}|$ < 0.2.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t,1}|$ < 0.5.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t,1}|$ < 0.5.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t,1}|$ < 1 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t,1}|$ < 1 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 1 < $|{y}^{t,1}|$ < 2 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0 TeV < $p_{T}^{t\bar{t}}$ < 0.1 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0 TeV < $p_{T}^{t\bar{t}}$ < 0.1 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0 TeV < $p_{T}^{t\bar{t}}$ < 0.1 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.1 TeV < $p_{T}^{t\bar{t}}$ < 0.2 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0 TeV < $p_{T}^{t\bar{t}}$ < 0.1 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.2 TeV < $p_{T}^{t\bar{t}}$ < 0.35 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0 TeV < $p_{T}^{t\bar{t}}$ < 0.1 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.35 TeV < $p_{T}^{t\bar{t}}$ < 1 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.1 TeV < $p_{T}^{t\bar{t}}$ < 0.2 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.1 TeV < $p_{T}^{t\bar{t}}$ < 0.2 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.1 TeV < $p_{T}^{t\bar{t}}$ < 0.2 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.2 TeV < $p_{T}^{t\bar{t}}$ < 0.35 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.1 TeV < $p_{T}^{t\bar{t}}$ < 0.2 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.35 TeV < $p_{T}^{t\bar{t}}$ < 1 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.2 TeV < $p_{T}^{t\bar{t}}$ < 0.35 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.2 TeV < $p_{T}^{t\bar{t}}$ < 0.35 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.2 TeV < $p_{T}^{t\bar{t}}$ < 0.35 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.35 TeV < $p_{T}^{t\bar{t}}$ < 1 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.35 TeV < $p_{T}^{t\bar{t}}$ < 1 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at particle level for 0.35 TeV < $p_{T}^{t\bar{t}}$ < 1 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
$p_{T}^{t}$ covariance matrix for the normalized differential cross-section at particle level.
$|y^{t}|$ covariance matrix for the normalized differential cross-section at particle level.
$p_{T}^{t,1}$ covariance matrix for the normalized differential cross-section at particle level.
$|{y}^{t,1}|$ covariance matrix for the normalized differential cross-section at particle level.
$p_{T}^{t,2}$ covariance matrix for the normalized differential cross-section at particle level.
$|{y}^{t,2}|$ covariance matrix for the normalized differential cross-section at particle level.
$m^{t\bar{t}}$ covariance matrix for the normalized differential cross-section at particle level.
$p_{T}^{t\bar{t}}$ covariance matrix for the normalized differential cross-section at particle level.
$|y^{t\bar{t}}|$ covariance matrix for the normalized differential cross-section at particle level.
$\chi^{t\bar{t}}$ covariance matrix for the normalized differential cross-section at particle level.
$|y_{B}^{t\bar{t}}|$ covariance matrix for the normalized differential cross-section at particle level.
$|p_{out}^{t\bar{t}}|$ covariance matrix for the normalized differential cross-section at particle level.
$|\Delta \phi(t_{1}, t_{2})|$ covariance matrix for the normalized differential cross-section at particle level.
$H_{T}^{t\bar{t}}$ covariance matrix for the normalized differential cross-section at particle level.
$|\cos\theta^{*}|$ covariance matrix for the normalized differential cross-section at particle level.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0.55 TeV < $p_{T}^{t,1}$ < 0.6 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0.6 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0.55 TeV < $p_{T}^{t,1}$ < 0.6 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0.55 TeV < $p_{T}^{t,1}$ < 0.6 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0.55 TeV < $p_{T}^{t,1}$ < 0.6 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0.6 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0.55 TeV < $p_{T}^{t,1}$ < 0.6 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0.6 TeV < $p_{T}^{t,1}$ < 0.75 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0.6 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0.6 TeV < $p_{T}^{t,1}$ < 0.75 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at particle level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at particle level for 0 < $|{y}^{t,1}|$ < 0.2.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at particle level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute normalized cross-section at particle level for 0.2 < $|{y}^{t,1}|$ < 0.5.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at particle level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at particle level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at particle level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t,1}|$ < 0.5.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at particle level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t,1}|$ < 1 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t,1}|$ < 1 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at particle level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at particle level for 1 < $|{y}^{t,1}|$ < 2 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at particle level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t,1}|$ < 0.2.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t,1}|$ < 0.5.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t,1}|$ < 0.5.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t,1}|$ < 1 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t,1}|$ < 1 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 1 < $|{y}^{t,1}|$ < 2 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0 < $|{y}^{t,2}|$ < 0.2 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0 < $|{y}^{t,2}|$ < 0.2.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0 < $|{y}^{t,2}|$ < 0.2 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t,2}|$ < 0.5.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0 < $|{y}^{t,2}|$ < 0.2 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t,2}|$ < 1.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0 < $|{y}^{t,2}|$ < 0.2 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 1 < $|{y}^{t,2}|$ < 2.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t,2}|$ < 0.5 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t,2}|$ < 0.5.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t,2}|$ < 0.5 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t,2}|$ < 1.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t,2}|$ < 0.5 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 1 < $|{y}^{t,2}|$ < 2.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t,2}|$ < 1 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t,2}|$ < 1.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t,2}|$ < 1 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 1 < $|{y}^{t,2}|$ < 2.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 1 < $|{y}^{t,2}|$ < 2 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at particle level for 1 < $|{y}^{t,2}|$ < 2.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0 < $|{y}^{t,1}|$ < 0.2.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t,1}|$ < 0.5.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t,1}|$ < 0.5.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t,1}|$ < 1 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t,1}|$ < 1 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 1 < $|{y}^{t,1}|$ < 2 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0 TeV < $p_{T}^{t\bar{t}}$ < 0.1 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0 TeV < $p_{T}^{t\bar{t}}$ < 0.1 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0 TeV < $p_{T}^{t\bar{t}}$ < 0.1 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.1 TeV < $p_{T}^{t\bar{t}}$ < 0.2 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0 TeV < $p_{T}^{t\bar{t}}$ < 0.1 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.2 TeV < $p_{T}^{t\bar{t}}$ < 0.35 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0 TeV < $p_{T}^{t\bar{t}}$ < 0.1 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.35 TeV < $p_{T}^{t\bar{t}}$ < 1 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.1 TeV < $p_{T}^{t\bar{t}}$ < 0.2 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.1 TeV < $p_{T}^{t\bar{t}}$ < 0.2 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.1 TeV < $p_{T}^{t\bar{t}}$ < 0.2 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.2 TeV < $p_{T}^{t\bar{t}}$ < 0.35 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.1 TeV < $p_{T}^{t\bar{t}}$ < 0.2 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.35 TeV < $p_{T}^{t\bar{t}}$ < 1 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.2 TeV < $p_{T}^{t\bar{t}}$ < 0.35 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.2 TeV < $p_{T}^{t\bar{t}}$ < 0.35 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.2 TeV < $p_{T}^{t\bar{t}}$ < 0.35 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.35 TeV < $p_{T}^{t\bar{t}}$ < 1 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.35 TeV < $p_{T}^{t\bar{t}}$ < 1 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at particle level for 0.35 TeV < $p_{T}^{t\bar{t}}$ < 1 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at particle level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at particle level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
$p_{T}^{t}$ covariance matrix for the absolute differential cross-section at parton level.
$|y^{t}|$ covariance matrix for the absolute differential cross-section at parton level.
$p_{T}^{t,1}$ covariance matrix for the absolute differential cross-section at parton level.
$|y^{t,1}|$ covariance matrix for the absolute differential cross-section at parton level.
$p_{T}^{t,2}$ covariance matrix for the absolute differential cross-section at parton level.
$|{y}^{t,2}|$ covariance matrix for the absolute differential cross-section at parton level.
$m^{t\bar{t}}$ covariance matrix for the absolute differential cross-section at parton level.
$p_{T}^{t\bar{t}}$ covariance matrix for the absolute differential cross-section at parton level.
$|{y}^{t\bar{t}}|$ covariance matrix for the absolute differential cross-section at parton level.
${\chi}^{t\bar{t}}$ covariance matrix for the absolute differential cross-section at parton level.
$|y_{B}^{t\bar{t}}|$ covariance matrix for the absolute differential cross-section at parton level.
$|p_{out}^{t\bar{t}}|$ covariance matrix for the absolute differential cross-section at parton level.
$|\Delta \phi(t_{1}, t_{2})|$ covariance matrix for the absolute differential cross-section at parton level.
$H_{T}^{t\bar{t}}$ covariance matrix for the absolute differential cross-section at parton level.
$|\cos\theta^{*}|$ covariance matrix for the absolute differential cross-section at parton level.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0.55 TeV < $p_{T}^{t,1}$ < 0.6 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0.6 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0.55 TeV < $p_{T}^{t,1}$ < 0.6 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0.55 TeV < $p_{T}^{t,1}$ < 0.6 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0.55 TeV < $p_{T}^{t,1}$ < 0.6 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0.6 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0.55 TeV < $p_{T}^{t,1}$ < 0.6 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0.6 TeV < $p_{T}^{t,1}$ < 0.75 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0.6 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0.6 TeV < $p_{T}^{t,1}$ < 0.75 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at parton level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at parton level for 0 < $|{y}^{t,1}|$ < 0.2.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at parton level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t,1}|$ < 0.5.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at parton level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at parton level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at parton level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t,1}|$ < 0.5.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at parton level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t,1}|$ < 1 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t,1}|$ < 1 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at parton level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at parton level for 1 < $|{y}^{t,1}|$ < 2 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ absolute differential cross-section at parton level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t,1}|$ < 0.2.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t,1}|$ < 0.5.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t,1}|$ < 0.5.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t,1}|$ < 1 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t,1}|$ < 1 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 1 < $|{y}^{t,1}|$ < 2 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0 < $|{y}^{t,2}|$ < 0.2 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0 < $|{y}^{t,2}|$ < 0.2.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0 < $|{y}^{t,2}|$ < 0.2 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t,2}|$ < 0.5.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0 < $|{y}^{t,2}|$ < 0.2 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t,2}|$ < 1.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0 < $|{y}^{t,2}|$ < 0.2 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 1 < $|{y}^{t,2}|$ < 2.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t,2}|$ < 0.5 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t,2}|$ < 0.5.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t,2}|$ < 0.5 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t,2}|$ < 1.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t,2}|$ < 0.5 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 1 < $|{y}^{t,2}|$ < 2.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t,2}|$ < 1 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t,2}|$ < 1.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t,2}|$ < 1 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 1 < $|{y}^{t,2}|$ < 2.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 1 < $|{y}^{t,2}|$ < 2 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ absolute differential cross-section at parton level for 1 < $|{y}^{t,2}|$ < 2.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ absolute differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0 < $|{y}^{t,1}|$ < 0.2.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t,1}|$ < 0.5.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t,1}|$ < 0.5.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t,1}|$ < 1 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t,1}|$ < 1 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 1 < $|{y}^{t,1}|$ < 2 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0 TeV < $p_{T}^{t\bar{t}}$ < 0.1 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0 TeV < $p_{T}^{t\bar{t}}$ < 0.1 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0 TeV < $p_{T}^{t\bar{t}}$ < 0.1 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.1 TeV < $p_{T}^{t\bar{t}}$ < 0.2 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0 TeV < $p_{T}^{t\bar{t}}$ < 0.1 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.2 TeV < $p_{T}^{t\bar{t}}$ < 0.35 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0 TeV < $p_{T}^{t\bar{t}}$ < 0.1 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.35 TeV < $p_{T}^{t\bar{t}}$ < 1 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.1 TeV < $p_{T}^{t\bar{t}}$ < 0.2 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.1 TeV < $p_{T}^{t\bar{t}}$ < 0.2 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.1 TeV < $p_{T}^{t\bar{t}}$ < 0.2 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.2 TeV < $p_{T}^{t\bar{t}}$ < 0.35 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.1 TeV < $p_{T}^{t\bar{t}}$ < 0.2 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.35 TeV < $p_{T}^{t\bar{t}}$ < 1 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.2 TeV < $p_{T}^{t\bar{t}}$ < 0.35 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.2 TeV < $p_{T}^{t\bar{t}}$ < 0.35 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.2 TeV < $p_{T}^{t\bar{t}}$ < 0.35 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.35 TeV < $p_{T}^{t\bar{t}}$ < 1 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.35 TeV < $p_{T}^{t\bar{t}}$ < 1 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ absolute differential cross-section at parton level for 0.35 TeV < $p_{T}^{t\bar{t}}$ < 1 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ absolute differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ absolute differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
$p_{T}^{t}$ covariance matrix for the normalized differential cross-section at parton level.
$|y^{t}|$ covariance matrix for the normalized differential cross-section at parton level.
$p_{T}^{t,1}$ covariance matrix for the normalized differential cross-section at parton level.
$|y^{t,1}|$ covariance matrix for the normalized differential cross-section at parton level.
$p_{T}^{t,2}$ covariance matrix for the normalized differential cross-section at parton level.
$|{y}^{t,2}|$ covariance matrix for the normalized differential cross-section at parton level.
$m^{t\bar{t}}$ covariance matrix for the normalized differential cross-section at parton level.
$p_{T}^{t\bar{t}}$ covariance matrix for the normalized differential cross-section at parton level.
$|{y}^{t\bar{t}}|$ covariance matrix for the normalized differential cross-section at parton level.
${\chi}^{t\bar{t}}$ covariance matrix for the normalized differential cross-section at parton level.
$|y_{B}^{t\bar{t}}|$ covariance matrix for the normalized differential cross-section at parton level.
$|p_{out}^{t\bar{t}}|$ covariance matrix for the normalized differential cross-section at parton level.
$|\Delta \phi(t_{1}, t_{2})|$ covariance matrix for the normalized differential cross-section at parton level.
$H_{T}^{t\bar{t}}$ covariance matrix for the normalized differential cross-section at parton level.
$|\cos\theta^{*}|$ covariance matrix for the normalized differential cross-section at parton level.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0.55 TeV < $p_{T}^{t,1}$ < 0.6 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0.6 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0.55 TeV < $p_{T}^{t,1}$ < 0.6 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0.55 TeV < $p_{T}^{t,1}$ < 0.6 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0.55 TeV < $p_{T}^{t,1}$ < 0.6 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0.6 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0.55 TeV < $p_{T}^{t,1}$ < 0.6 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0.6 TeV < $p_{T}^{t,1}$ < 0.75 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0.6 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0.6 TeV < $p_{T}^{t,1}$ < 0.75 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at parton level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at parton level for 0 < $|{y}^{t,1}|$ < 0.2.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at parton level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t,1}|$ < 0.5.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at parton level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at parton level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at parton level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t,1}|$ < 0.5.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at parton level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t,1}|$ < 1 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t,1}|$ < 1 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at parton level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at parton level for 1 < $|{y}^{t,1}|$ < 2 and the $|{y}^{t,1}|\otimes |{y}^{t,2}|$ normalized differential cross-section at parton level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t,1}|$ < 0.2.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t,1}|$ < 0.5.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t,1}|$ < 0.5.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t,1}|$ < 1 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t,1}|$ < 1 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 1 < $|{y}^{t,1}|$ < 2 and the $|{y}^{t,1}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0 < $|{y}^{t,2}|$ < 0.2 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0 < $|{y}^{t,2}|$ < 0.2.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0 < $|{y}^{t,2}|$ < 0.2 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t,2}|$ < 0.5.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0 < $|{y}^{t,2}|$ < 0.2 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t,2}|$ < 1.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0 < $|{y}^{t,2}|$ < 0.2 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 1 < $|{y}^{t,2}|$ < 2.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t,2}|$ < 0.5 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t,2}|$ < 0.5.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t,2}|$ < 0.5 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t,2}|$ < 1.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t,2}|$ < 0.5 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 1 < $|{y}^{t,2}|$ < 2.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t,2}|$ < 1 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t,2}|$ < 1.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t,2}|$ < 1 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 1 < $|{y}^{t,2}|$ < 2.
Covariance matrix between the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 1 < $|{y}^{t,2}|$ < 2 and the $|{y}^{t,2}|\otimes p_{T}^{t,2}$ normalized differential cross-section at parton level for 1 < $|{y}^{t,2}|$ < 2.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV and the $p_{T}^{t,1}\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.5 TeV < $p_{T}^{t,1}$ < 0.55 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.55 TeV < $p_{T}^{t,1}$ < 0.625 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.625 TeV < $p_{T}^{t,1}$ < 0.75 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV and the $p_{T}^{t,1}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.75 TeV < $p_{T}^{t,1}$ < 2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}| $normalized differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2 and the $|{y}^{t\bar{t}}|\otimes |{y}^{t,1}|$ normalized differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0 < $|{y}^{t,1}|$ < 0.2.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t,1}|$ < 0.5.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0 < $|{y}^{t,1}|$ < 0.2 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t,1}|$ < 0.5.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t,1}|$ < 0.5 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t,1}|$ < 1 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t,1}|$ < 1.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t,1}|$ < 1 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 1 < $|{y}^{t,1}|$ < 2 and the $|{y}^{t,1}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 1 < $|{y}^{t,1}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2 and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0 TeV < $p_{T}^{t\bar{t}}$ < 0.1 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0 TeV < $p_{T}^{t\bar{t}}$ < 0.1 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0 TeV < $p_{T}^{t\bar{t}}$ < 0.1 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.1 TeV < $p_{T}^{t\bar{t}}$ < 0.2 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0 TeV < $p_{T}^{t\bar{t}}$ < 0.1 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.2 TeV < $p_{T}^{t\bar{t}}$ < 0.35 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0 TeV < $p_{T}^{t\bar{t}}$ < 0.1 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.35 TeV < $p_{T}^{t\bar{t}}$ < 1 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.1 TeV < $p_{T}^{t\bar{t}}$ < 0.2 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.1 TeV < $p_{T}^{t\bar{t}}$ < 0.2 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.1 TeV < $p_{T}^{t\bar{t}}$ < 0.2 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.2 TeV < $p_{T}^{t\bar{t}}$ < 0.35 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.1 TeV < $p_{T}^{t\bar{t}}$ < 0.2 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.35 TeV < $p_{T}^{t\bar{t}}$ < 1 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.2 TeV < $p_{T}^{t\bar{t}}$ < 0.35 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.2 TeV < $p_{T}^{t\bar{t}}$ < 0.35 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.2 TeV < $p_{T}^{t\bar{t}}$ < 0.35 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.35 TeV < $p_{T}^{t\bar{t}}$ < 1 TeV.
Covariance matrix between the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.35 TeV < $p_{T}^{t\bar{t}}$ < 1 TeV and the $p_{T}^{t\bar{t}}\otimes m^{t\bar{t}}$ normalized differential cross-section at parton level for 0.35 TeV < $p_{T}^{t\bar{t}}$ < 1 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0.2 < $|{y}^{t\bar{t}}|$ < 0.5 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 0.5 < $|{y}^{t\bar{t}}|$ < 1 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2 and the $|{y}^{t\bar{t}}|\otimes p_{T}^{t\bar{t}}$ normalized differential cross-section at parton level for 1 < $|{y}^{t\bar{t}}|$ < 2.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0 < $|{y}^{t\bar{t}}|$ < 0.3, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.3 < $|{y}^{t\bar{t}}|$ < 0.9, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 0.9 TeV < $m^{t\bar{t}}$ < 1.2 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.2 TeV < $m^{t\bar{t}}$ < 1.5 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
Covariance matrix between the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV and the $|{y}^{t\bar{t}}|\otimes m^{t\bar{t}}\otimes p_{T}^{t,1}$ normalized differential cross-section at parton level for 0.9 < $|{y}^{t\bar{t}}|$ < 2, 1.5 TeV < $m^{t\bar{t}}$ < 4 TeV.
A search for pair-produced scalar and vector leptoquarks decaying into quarks and leptons of different generations is presented. It uses the full LHC Run 2 (2015-2018) data set of 139 fb$^{-1}$ collected with the ATLAS detector in proton-proton collisions at a centre-of-mass energy of $\sqrt{s} = 13$ TeV. Scalar leptoquarks with charge -(1/3)e as well as scalar and vector leptoquarks with charge +(2/3)e are considered. All possible decays of the pair-produced leptoquarks into quarks of the third generation (t, b) and charged or neutral leptons of the first or second generation ($e, \mu, \nu$) with exactly one electron or muon in the final state are investigated. No significant deviations from the Standard Model expectation are observed. Upper limits on the production cross-section are provided for eight models as a function of the leptoquark mass and the branching ratio of the leptoquark into the charged or neutral lepton. In addition, lower limits on the leptoquark masses are derived for all models across a range of branching ratios. Two of these models have the goal of providing an explanation for the recent B-anomalies. In both models, a vector leptoquark decays into charged and neutral leptons of the second generation with a similar branching fraction. Lower limits of 1980 GeV and 1710 GeV are set on the leptoquark mass for these two models.
- - - - - - - - Overview of HEPData Record - - - - - - - - <br/><br/> <b>95% CL limits on the production cross-section for:</b> <ul> <li><a href="135703?version=1&table=%24LQ_u%20%5Crightarrow%20t%5Cnu%2Fb%5Cmu%24%20observed%20limits">scalar up-type LQs decaying into a top quark and a neutrino or a bottom quark and a muon (observed)</a> <li><a href="135703?version=1&table=%24LQ_u%20%5Crightarrow%20t%5Cnu%2Fb%5Cmu%24%20expected%20limits">scalar up-type LQs decaying into a top quark and a neutrino or a bottom quark and a muon (expected)</a> <li><a href="135703?version=1&table=%24LQ_u%20%5Crightarrow%20t%5Cnu%2Fbe%24%20observed%20limits">scalar up-type LQs decaying into a top quark and a neutrino or a bottom quark and an electron (observed)</a> <li><a href="135703?version=1&table=%24LQ_u%20%5Crightarrow%20t%5Cnu%2Fbe%24%20expected%20limits">scalar up-type LQs decaying into a top quark and a neutrino or a bottom quark and an electron (expected)</a> <li><a href="135703?version=1&table=%24LQ_d%20%5Crightarrow%20t%5Cmu%2Fb%5Cnu%24%20observed%20limits">scalar down-type LQs decaying into a bottom quark and a neutrino or a top quark and a muon (observed)</a> <li><a href="135703?version=1&table=%24LQ_d%20%5Crightarrow%20t%5Cmu%2Fb%5Cnu%24%20expected%20limits">scalar down-type LQs decaying into a bottom quark and a neutrino or a top quark and a muon (expected)</a> <li><a href="135703?version=1&table=%24LQ_d%20%5Crightarrow%20te%2Fb%5Cnu%24%20observed%20limits">scalar down-type LQs decaying into a bottom quark and a neutrino or a top quark and an electron (observed)</a> <li><a href="135703?version=1&table=%24LQ_d%20%5Crightarrow%20te%2Fb%5Cnu%24%20expected%20limits">scalar down-type LQs decaying into a bottom quark and a neutrino or a top quark and an electron (expected)</a> <li><a href="135703?version=1&table=%24vLQ_%7BYM%7D%20%5Crightarrow%20t%5Cnu%2Fb%5Cmu%24%20observed%20limits">vector up-type LQs in the Yang-Mills coupling scenario decaying into a top quark and a neutrino or a bottom quark and a muon (observed)</a> <li><a href="135703?version=1&table=%24vLQ_%7BYM%7D%20%5Crightarrow%20t%5Cnu%2Fb%5Cmu%24%20expected%20limits">vector up-type LQs in the Yang-Mills coupling scenario decaying into a top quark and a neutrino or a bottom quark and a muon (expected)</a> <li><a href="135703?version=1&table=%24vLQ_%7BYM%7D%20%5Crightarrow%20t%5Cnu%2Fbe%24%20observed%20limits">vector up-type LQs in the Yang-Mills coupling scenario decaying into a top quark and a neutrino or a bottom quark and an electron (observed)</a> <li><a href="135703?version=1&table=%24vLQ_%7BYM%7D%20%5Crightarrow%20t%5Cnu%2Fbe%24%20expected%20limits">vector up-type LQs in the Yang-Mills coupling scenario decaying into a top quark and a neutrino or a bottom quark and an electron (expected)</a> <li><a href="135703?version=1&table=%24vLQ_%7Bmin%7D%20%5Crightarrow%20t%5Cnu%2Fb%5Cmu%24%20observed%20limits">vector up-type LQs in the minimal coupling scenario decaying into a top quark and a neutrino or a bottom quark and a muon (observed)</a> <li><a href="135703?version=1&table=%24vLQ_%7Bmin%7D%20%5Crightarrow%20t%5Cnu%2Fb%5Cmu%24%20expected%20limits">vector up-type LQs in the minimal coupling scenario decaying into a top quark and a neutrino or a bottom quark and a muon (expected)</a> <li><a href="135703?version=1&table=%24vLQ_%7Bmin%7D%20%5Crightarrow%20t%5Cnu%2Fbe%24%20observed%20limits">vector up-type LQs in the minimal coupling scenario decaying into a top quark and a neutrino or a bottom quark and an electron (observed)</a> <li><a href="135703?version=1&table=%24vLQ_%7Bmin%7D%20%5Crightarrow%20t%5Cnu%2Fbe%24%20expected%20limits">vector up-type LQs in the minimal coupling scenario decaying into a top quark and a neutrino or a bottom quark and an electron (expected)</a> </ul> <b>Product of signal acceptance and efficiency in the training region for:</b> <ul> <li><a href="135703?version=1&table=%24LQ_u%20%5Crightarrow%20t%5Cnu%2Fb%5Cmu%24%20Acceptance%20times%20Efficiency">scalar up-type LQs decaying into top quarks and neutrinos or bottom quarks and muons</a> <li><a href="135703?version=1&table=%24LQ_u%20%5Crightarrow%20t%5Cnu%2Fbe%24%20Acceptance%20times%20Efficiency">scalar up-type LQs decaying into top quarks and neutrinos or bottom quarks and electrons</a> <li><a href="135703?version=1&table=%24LQ_d%20%5Crightarrow%20t%5Cmu%2Fb%5Cnu%24%20Acceptance%20times%20Efficiency">scalar down-type LQs decaying into bottom quarks and neutrinos or top quarks and muons</a> <li><a href="135703?version=1&table=%24LQ_d%20%5Crightarrow%20te%2Fb%5Cnu%24%20Acceptance%20times%20Efficiency">scalar down-type LQs decaying into bottom quarks and neutrinos or top quarks and electrons</a> <li><a href="135703?version=1&table=%24vLQ_%7BYM%7D%20%5Crightarrow%20t%5Cnu%2Fb%5Cmu%24%20Acceptance%20times%20Efficiency">vector up-type LQs in the Yang-Mills coupling scenario decaying into top quarks and neutrinos or bottom quarks and muons</a> <li><a href="135703?version=1&table=%24vLQ_%7BYM%7D%20%5Crightarrow%20t%5Cnu%2Fbe%24%20Acceptance%20times%20Efficiency">vector up-type LQs in the Yang-Mills coupling scenario decaying into top quarks and neutrinos or bottom quarks and electrons</a> <li><a href="135703?version=1&table=%24vLQ_%7Bmin%7D%20%5Crightarrow%20t%5Cnu%2Fb%5Cmu%24%20Acceptance%20times%20Efficiency">vector up-type LQs in the minimal coupling scenario decaying into top quarks and neutrinos or bottom quarks and muons</a> <li><a href="135703?version=1&table=%24vLQ_%7Bmin%7D%20%5Crightarrow%20t%5Cnu%2Fbe%24%20Acceptance%20times%20Efficiency">vector up-type LQs in the minimal coupling scenario decaying into top quarks and neutrinos or bottom quarks and electrons</a> </ul> <b>Cut-flow for:</b> <ul> <li><a href="135703?version=1&table=Scalar%20LQs%20cut-flow">scalar LQs</a> <li><a href="135703?version=1&table=Vector%20LQs%20cut-flow">vector LQs</a> </ul>
Observed 95% CL limits on the production cross-section for scalar up-type LQs decaying into a top quark and a neutrino or a bottom quark and a muon.
Expected 95% CL limits on the production cross-section for scalar up-type LQs decaying into a top quark and a neutrino or a bottom quark and a muon.
Observed 95% CL limits on the production cross-section for scalar up-type LQs decaying into a top quark and a neutrino or a bottom quark and an electron.
Expected 95% CL limits on the production cross-section for scalar up-type LQs decaying into a top quark and a neutrino or a bottom quark and an electron.
Observed 95% CL limits on the production cross-section for scalar down-type LQs decaying into a bottom quark and a neutrino or a top quark and a muon.
Expected 95% CL limits on the production cross-section for scalar down-type LQs decaying into a bottom quark and a neutrino or a top quark and a muon.
Observed 95% CL limits on the production cross-section for scalar down-type LQs decaying into a bottom quark and a neutrino or a top quark and an electron.
Expected 95% CL limits on the production cross-section for scalar down-type LQs decaying into a bottom quark and a neutrino or a top quark and an electron.
Observed 95% CL limits on the production cross-section for vector up-type LQs in the Yang-Mills coupling scenario decaying into a top quark and a neutrino or a bottom quark and a muon.
Expected 95% CL limits on the production cross-section for vector up-type LQs in the Yang-Mills coupling scenario decaying into a top quark and a neutrino or a bottom quark and a muon.
Observed 95% CL limits on the production cross-section for vector up-type LQs in the Yang-Mills coupling scenario decaying into a top quark and a neutrino or a bottom quark and an electron.
Expected 95% CL limits on the production cross-section for vector up-type LQs in the Yang-Mills coupling scenario decaying into a top quark and a neutrino or a bottom quark and an electron.
Observed 95% CL limits on the production cross-section for vector up-type LQs in the minimal coupling scenario decaying into a top quark and a neutrino or a bottom quark and a muon.
Expected 95% CL limits on the production cross-section for vector up-type LQs in the minimal coupling scenario decaying into a top quark and a neutrino or a bottom quark and a muon.
Observed 95% CL limits on the production cross-section for vector up-type LQs in the minimal coupling scenario decaying into a top quark and a neutrino or a bottom quark and an electron.
Expected 95% CL limits on the production cross-section for vector up-type LQs in the minimal coupling scenario decaying into a top quark and a neutrino or a bottom quark and an electron.
Product of signal acceptance and efficiency in the training region for scalar up-type LQs decaying into top quarks and neutrinos or bottom quarks and muons depending on the signal mass, $m_{LQ}$, and $\mathcal{B}(LQ_{mix}^u\rightarrow b\mu)$.
Product of signal acceptance and efficiency in the training region for scalar up-type LQs decaying into top quarks and neutrinos or bottom quarks and electrons depending on the signal mass, $m_{LQ}$, and $\mathcal{B}(LQ_{mix}^u\rightarrow be)$.
Product of signal acceptance and efficiency in the training region for scalar down-type LQs decaying into top quarks and muons or bottom quarks and neutrinos depending on the signal mass, $m_{LQ}$, and $\mathcal{B}(LQ_{mix}^d\rightarrow t\mu)$.
Product of signal acceptance and efficiency in the training region for scalar down-type LQs decaying into top quarks and electrons or bottom quarks and neutrinos depending on the signal mass, $m_{LQ}$, and $\mathcal{B}(LQ_{mix}^d\rightarrow te)$.
Product of signal acceptance and efficiency in the training region for vector LQs in the Yang-Mills coupling scenario decaying into top quarks and neutrinos or bottom quarks and muons depending on the signal mass, $m_{LQ}$, and $\mathcal{B}(vLQ_{mix}^{YM}\rightarrow b\mu)$.
Product of signal acceptance and efficiency in the training region for vector LQs in the Yang-Mills coupling scenario decaying into top quarks and neutrinos or bottom quarks and electrons depending on the signal mass, $m_{LQ}$, and $\mathcal{B}(vLQ_{mix}^{YM}\rightarrow be)$.
Product of signal acceptance and efficiency in the training region for vector LQs in the minimal coupling scenario decaying into top quarks and neutrinos or bottom quarks and muons depending on the signal mass, $m_{LQ}$, and $\mathcal{B}(vLQ_{mix}^{min}\rightarrow b\mu)$.
Product of signal acceptance and efficiency in the training region for vector LQs in the minimal coupling scenario decaying into top quarks and neutrinos or bottom quarks and electrons depending on the signal mass, $m_{LQ}$, and $\mathcal{B}(vLQ_{mix}^{min}\rightarrow be)$.
Cut-flow for the four models containing scalar LQs at a mass of $m_{LQ}=1300$ GeV and $\mathcal{B}(LQ_{mix}\rightarrow q_3\ell)=0.5$.
Cut-flow for the four models containing vector LQs at a mass of $m_{LQ}=1300$ GeV and $\mathcal{B}(LQ_{mix}\rightarrow q_3\ell)=0.5$.
This paper presents direct searches for lepton flavour violation in Higgs boson decays, $H\rightarrow e\tau$ and $H\rightarrow\mu\tau$, performed using data collected with the ATLAS detector at the LHC. The searches are based on a data sample of proton-proton collisions at a centre-of-mass energy $\sqrt{s} = 13$ TeV, corresponding to an integrated luminosity of 138 fb$^{-1}$. Leptonic ($\tau \rightarrow \ell \nu_\ell \nu_\tau$) and hadronic ($\tau \rightarrow $ hadrons $ \nu_\tau$) decays of the $\tau$-lepton are considered. Two background estimation techniques are employed: the MC-template method, based on data-corrected simulation samples, and the Symmetry method, based on exploiting the symmetry between electrons and muons in the Standard Model backgrounds. No significant excess of events is observed and the results are interpreted as upper limits on lepton-flavour-violating branching ratios of the Higgs boson. The observed (expected) upper limits set on the branching ratios at 95% confidence level, $\mathcal{B}(H\rightarrow e\tau)<0.20\%$ (0.12%) and $\mathcal{B}(H\rightarrow \mu\tau)<0.18\%$ (0.09%), are obtained with the MC-template method from a simultaneous measurement of potential $H \rightarrow e\tau$ and $H \rightarrow\mu\tau$ signals. The best-fit branching ratio difference, $\mathcal{B}(H\rightarrow \mu\tau)- \mathcal{B}(H\rightarrow e\tau)$, measured with the Symmetry method in the channel where the $\tau$-lepton decays to leptons, is (0.25 $\pm$ 0.10)%, compatible with a value of zero within 2.5$\sigma$.
Fit results of the simultaneous measurements of the $H\to e\tau$ and $H\to \mu\tau$ signals (2POI) showing upper limits at 95% C.L. on the LFV branching ratios of the Higgs boson $H\to e\tau$. The results from standalone channel/categories fits are compared with the results of the combined fit.
Fit results of the simultaneous measurements of the $H\to e\tau$ and $H\to \mu\tau$ signals (2POI) showing upper limits at 95% C.L. on the LFV branching ratios of the Higgs boson $H\to e\tau$. The results from standalone channel/categories fits are compared with the results of the combined fit.
Fit results of the simultaneous measurements of the $H\to e\tau$ and $H\to \mu\tau$ signals (2POI) showing best-fit values of the LFV branching ratios of the Higgs boson $\hat{B}$($H\to e\tau$). The results from standalone channel/categories fits are compared with the results of the combined fit.
Fit results of the simultaneous measurements of the $H\to e\tau$ and $H\to \mu\tau$ signals (2POI) showing best-fit values of the LFV branching ratios of the Higgs boson $\hat{B}$($H\to e\tau$). The results from standalone channel/categories fits are compared with the results of the combined fit.
Fit results of the simultaneous measurements of the $H\to e\tau$ and $H\to \mu\tau$ signals (2POI) showing upper limits at 95% C.L. on the LFV branching ratios of the Higgs boson $H\to \mu\tau$. The results from standalone channel/categories fits are compared with the results of the combined fit.
Fit results of the simultaneous measurements of the $H\to e\tau$ and $H\to \mu\tau$ signals (2POI) showing upper limits at 95% C.L. on the LFV branching ratios of the Higgs boson $H\to \mu\tau$. The results from standalone channel/categories fits are compared with the results of the combined fit.
Fit results of the simultaneous measurements of the $H\to e\tau$ and $H\to \mu\tau$ signals (2POI) showing best-fit values of the LFV branching ratios of the Higgs boson $\hat{B}$($H\to \mu\tau$). The results from standalone channel/categories fits are compared with the results of the combined fit.
Fit results of the simultaneous measurements of the $H\to e\tau$ and $H\to \mu\tau$ signals (2POI) showing best-fit values of the LFV branching ratios of the Higgs boson $\hat{B}$($H\to \mu\tau$). The results from standalone channel/categories fits are compared with the results of the combined fit.
Fit results of the independent searches (1 POI) showing upper limits at 95% C.L. on the LFV branching ratios of the Higgs boson $H\to e\tau$. The results from standalone channel/categories fits are compared with the results of the combined fit.
Fit results of the independent searches (1 POI) showing upper limits at 95% C.L. on the LFV branching ratios of the Higgs boson $H\to e\tau$. The results from standalone channel/categories fits are compared with the results of the combined fit.
Fit results of the independent searches (1 POI) showing best-fit values of the LFV branching ratios of the Higgs boson $\hat{B}$($H\to e\tau$). The results from standalone channel/categories fits are compared with the results of the combined fit.
Fit results of the independent searches (1 POI) showing best-fit values of the LFV branching ratios of the Higgs boson $\hat{B}$($H\to e\tau$). The results from standalone channel/categories fits are compared with the results of the combined fit.
Fit results of the independent searches (1 POI) showing upper limits at 95% C.L. on the LFV branching ratios of the Higgs boson $H\to \mu\tau$. The results from standalone channel/categories fits are compared with the results of the combined fit.
Fit results of the independent searches (1 POI) showing upper limits at 95% C.L. on the LFV branching ratios of the Higgs boson $H\to \mu\tau$. The results from standalone channel/categories fits are compared with the results of the combined fit.
Fit results of the independent searches (1 POI) showing best-fit values of the LFV branching ratios of the Higgs boson $\hat{B}$($H\to \mu\tau$). The results from standalone channel/categories fits are compared with the results of the combined fit.
Fit results of the independent searches (1 POI) showing best-fit values of the LFV branching ratios of the Higgs boson $\hat{B}$($H\to \mu\tau$). The results from standalone channel/categories fits are compared with the results of the combined fit.
BDT score distribution, after the simultaneous fit of the $H\to e\tau$ and $H\to \mu\tau$ signals, obtained by fitting the data of the MC-template $\ell\tau_{\ell'}$ channel for $e\tau_{\mu}$ final state in the non-VBF category.
BDT score distribution, after the simultaneous fit of the $H\to e\tau$ and $H\to \mu\tau$ signals, obtained by fitting the data of the MC-template $\ell\tau_{\ell'}$ channel for $e\tau_{\mu}$ final state in the non-VBF category.
BDT score distribution, after the simultaneous fit of the $H\to e\tau$ and $H\to \mu\tau$ signals, obtained by fitting the data of the MC-template $\ell\tau_{\ell'}$ channel for $\mu\tau_{e}$ final state in the non-VBF category.
BDT score distribution, after the simultaneous fit of the $H\to e\tau$ and $H\to \mu\tau$ signals, obtained by fitting the data of the MC-template $\ell\tau_{\ell'}$ channel for $\mu\tau_{e}$ final state in the non-VBF category.
BDT score distribution, after the simultaneous fit of the $H\to e\tau$ and $H\to \mu\tau$ signals, obtained by fitting the data of the MC-template $\ell\tau_{\ell'}$ channel for $e\tau_{\mu}$ final state in the VBF category.
BDT score distribution, after the simultaneous fit of the $H\to e\tau$ and $H\to \mu\tau$ signals, obtained by fitting the data of the MC-template $\ell\tau_{\ell'}$ channel for $e\tau_{\mu}$ final state in the VBF category.
BDT score distribution, after the simultaneous fit of the $H\to e\tau$ and $H\to \mu\tau$ signals, obtained by fitting the data of the MC-template $\ell\tau_{\ell'}$ channel for $\mu\tau_{e}$ final state in the VBF category.
BDT score distribution, after the simultaneous fit of the $H\to e\tau$ and $H\to \mu\tau$ signals, obtained by fitting the data of the MC-template $\ell\tau_{\ell'}$ channel for $\mu\tau_{e}$ final state in the VBF category.
BDT score distribution, after the simultaneous fit of the $H\to e\tau$ and $H\to \mu\tau$ signals, obtained by fitting the data of the MC-template $\ell\tau_{had}$ channel for $e\tau_{had}$ final state in the non-VBF category.
BDT score distribution, after the simultaneous fit of the $H\to e\tau$ and $H\to \mu\tau$ signals, obtained by fitting the data of the MC-template $\ell\tau_{had}$ channel for $e\tau_{had}$ final state in the non-VBF category.
BDT score distribution, after the simultaneous fit of the $H\to e\tau$ and $H\to \mu\tau$ signals, obtained by fitting the data of the MC-template $\ell\tau_{had}$ channel for $\mu\tau_{had}$ final state in the non-VBF category.
BDT score distribution, after the simultaneous fit of the $H\to e\tau$ and $H\to \mu\tau$ signals, obtained by fitting the data of the MC-template $\ell\tau_{had}$ channel for $\mu\tau_{had}$ final state in the non-VBF category.
BDT score distribution, after the simultaneous fit of the $H\to e\tau$ and $H\to \mu\tau$ signals, obtained by fitting the data of the MC-template $\ell\tau_{had}$ channel for $e\tau_{had}$ final state in the VBF category.
BDT score distribution, after the simultaneous fit of the $H\to e\tau$ and $H\to \mu\tau$ signals, obtained by fitting the data of the MC-template $\ell\tau_{had}$ channel for $e\tau_{had}$ final state in the VBF category.
BDT score distribution, after the simultaneous fit of the $H\to e\tau$ and $H\to \mu\tau$ signals, obtained by fitting the data of the MC-template $\ell\tau_{had}$ channel for $\mu\tau_{had}$ final state in the VBF category.
BDT score distribution, after the simultaneous fit of the $H\to e\tau$ and $H\to \mu\tau$ signals, obtained by fitting the data of the MC-template $\ell\tau_{had}$ channel for $\mu\tau_{had}$ final state in the VBF category.
NN score distribution, after an independent fit of the $H\to \mu\tau$ signal, obtained by fitting the data of the Symmetry $\ell\tau_{\ell'}$ channel, for the $\mu\tau_{e}$ final state in the non-VBF category.
NN score distribution, after an independent fit of the $H\to \mu\tau$ signal, obtained by fitting the data of the Symmetry $\ell\tau_{\ell'}$ channel, for the $\mu\tau_{e}$ final state in the non-VBF category.
NN score distribution, after an independent fit of the $H\to \mu\tau$ signal, obtained by fitting the data of the Symmetry $\ell\tau_{\ell'}$ channel, for the $\mu\tau_{e}$ final state in the VBF category.
NN score distribution, after an independent fit of the $H\to \mu\tau$ signal, obtained by fitting the data of the Symmetry $\ell\tau_{\ell'}$ channel, for the $\mu\tau_{e}$ final state in the VBF category.
Best-fit $\mathcal{B}(H\to \mu\tau)- \mathcal{B}(H\to e\tau)$ values, given in %, obtained from the standalone fits of the $\ell\tau_\ell'$ final state with either background estimation method. For the MC-template method, the correlated uncertainties are fixed to their best-fit values and the uncertainties are re-derived considering only the uncorrelated sources. For the Symmetry method, the full uncertainty is considered.
Best-fit $\mathcal{B}(H\to \mu\tau)- \mathcal{B}(H\to e\tau)$ values, given in %, obtained from the standalone fits of the $\ell\tau_\ell'$ final state with either background estimation method. For the MC-template method, the correlated uncertainties are fixed to their best-fit values and the uncertainties are re-derived considering only the uncorrelated sources. For the Symmetry method, the full uncertainty is considered.
Best-fit value of the branching ratios $\mathcal{B}(H\to e\tau)$ and $\mathcal{B}(H\to \mu\tau)$, given in %, and likelihood contours at 68% and 95% C.L. Obtained from the simultaneous fit of $H\to e\tau$ and $H\to \mu\tau$ signals based on the MC-template method, compared to the SM expectation.
Best-fit value of the branching ratios $\mathcal{B}(H\to e\tau)$ and $\mathcal{B}(H\to \mu\tau)$, given in %, and likelihood contours at 68% and 95% C.L. Obtained from the simultaneous fit of $H\to e\tau$ and $H\to \mu\tau$ signals based on the MC-template method, compared to the SM expectation.
A search for pair-produced vector-like quarks using events with exactly one lepton ($e$ or $\mu$), at least four jets including at least one $b$-tagged jet, and large missing transverse momentum is presented. Data from proton-proton collisions at a centre-of-mass energy of $\sqrt{s} = 13$ TeV, recorded by the ATLAS detector at the LHC from 2015 to 2018 and corresponding to an integrated luminosity of 139 fb$^{-1}$, are analysed. Vector-like partners $T$ and $B$ of the top and bottom quarks are considered, as is a vector-like $X$ with charge +5/3, assuming their decay into a $W$, $Z$, or Higgs boson and a third-generation quark. No significant deviations from the Standard Model expectation are observed. Upper limits on the production cross-section of $T$ and $B$ quark pairs as a function of their mass are derived for various decay branching ratio scenarios. The strongest lower limits on the masses are 1.59 TeV assuming mass-degenerate VLQs and branching ratios corresponding to the weak-isospin doublet model, and 1.47 TeV (1.46 TeV) for exclusive $T \rightarrow Zt$ ($B/X \rightarrow Wt$) decays. In addition, lower limits on the $T$ and $B$ quark masses are derived for all possible branching ratios.
Expected and observed upper limits at 95% CL on the cross section of vector-like quark pair production for $T\bar{T}$ and $\mathcal{B}(T\rightarrow Zt) = 100$%.
Expected and observed upper limits at 95% CL on the cross section of vector-like quark pair production for $B\bar{B}$ and $\mathcal{B}(B\rightarrow Wt) = 100$%.
Expected and observed upper limits at 95% CL on the cross section of vector-like quark pair production for $T\bar{T}$ in the singlet model.
Expected and observed upper limits at 95% CL on the cross section of vector-like quark pair production for $B\bar{B}$ in the singlet model.
Expected and observed upper limits at 95% CL on the cross section of vector-like quark pair production for $T\bar{T}$ in the doublet model.
Expected and observed upper limits at 95% CL on the cross section of vector-like quark pair production, considereing both $T\bar{T}$ and $B\bar{B}$, in the $(T,B)$ doublet model.
Expected 95% CL lower limits on the vector-like top quark mass as a function of the branching ratios into $Wb$ and $Ht$.
Observed 95% CL lower limits on the vector-like top quark mass as a function of the branching ratios into $Wb$ and $Ht$.
Expected 95% CL lower limits on the vector-like bottom quark mass as a function of the branching ratios into $Hb$ and $Wt$.
Observed 95% CL lower limits on the vector-like top quark mass as a function of the branching ratios into $Hb$ and $Wt$.
A search for a new heavy scalar or pseudo-scalar Higgs boson ($H/A$) produced in association with a pair of top quarks, with the Higgs boson decaying into a pair of top quarks ($H/A\rightarrow t\bar{t}$) is reported. The search targets a final state with exactly two leptons with same-sign electric charges or at least three leptons. The analysed dataset corresponds to an integrated luminosity of 139 fb$^{-1}$ of proton-proton collisions collected at a centre-of-mass energy of 13 TeV with the ATLAS detector at the LHC. Two multivariate classifiers are used to separate the signal from the background. No significant excess of events over the Standard Model expectation is observed. The results are interpreted in the context of a type-II two-Higgs-doublet model. The observed (expected) upper limits at 95% confidence level on the $t\bar{t}H/A$ production cross-section times the branching ratio of $H/A\rightarrow t\bar{t}$ range between 14 (10) fb and 6 (5) fb for a heavy Higgs boson with mass between 400 GeV and 1000 GeV, respectively. Assuming that only one particle, either the scalar $H$ or the pseudo-scalar $A$, contributes to the $t\bar{t}t\bar{t}$ final state, values of $\tan\beta$ below 1.2 or 0.5 are excluded for a mass of 400 GeV or 1000 GeV, respectively. These exclusion ranges increase to $\tan\beta$ below 1.6 or 0.6 when both particles are considered.
Pre-fit comparison between data and background in the baseline SR for two of the variables used as input for the SM BDT: the sum of the leading four jets b-tagging scores.
Pre-fit comparison between data and background in the baseline SR for two of the variables used as input for the SM BDT: the number of jets.
Pre-fit comparison between data and background in the baseline SR for two of the variables used as input for the BSM pBDT: SM BDT.
Pre-fit comparison between data and background in the baseline SR for two of the variables used as input for the BSM pBDT: HT.
Data and post-fit background comparison for the distributions of the discriminant variables fitted in the control regions obtained with the background-only fit: CR HF e.
Data and post-fit background comparison for the distributions of the discriminant variables fitted in the control regions obtained with the background-only fit: CR HF mu.
Data and post-fit background comparison for the distributions of the discriminant variables fitted in the control regions obtained with the background-only fit: CR Conv.
Data and post-fit background comparison for the distributions of the discriminant variables fitted in the control regions obtained with the background-only fit: CR ttW.
Data and post-fit background comparison for the distributions of the discriminant variables fitted in the control regions obtained with the background-only fit: CR lowBDT.
Data and post-fit background comparison obtained with the background-only fit in the validation region defined for ttW+jets events: number of jets.
Data and post-fit background comparison obtained with the background-only fit in the validation region defined for ttW+jets events: SM BDT.
Data and post-fit background comparison obtained with the background-only fit to the BSM SR for the BSM pBDT distribution used for mH = 400 GeV.
Data and post-fit background comparison obtained with the background-only fit to the BSM SR for the BSM pBDT distribution used for mH = 1000 GeV.
Observed (black solid line) and expected (black dashed line) 95% CL upper limits on the ttH/A cross-section times branching fraction of H/A->tt as a function of mH/A.
Observed (red line) and expected (black dashed line) exclusion regions at 95% CL in the tan(beta) versus mass plane assuming that both, a heavy scalar H and pseudo-scalar A, contribute to the tttt final state and have the same mass mH=mA.
Observed (red line) and expected (black dashed line) exclusion regions at 95% CL in the tan(beta) versus mass plane assuming that only the scalar H contributes to the tttt final state.
Data and post-fit background comparison obtained with the background-only fit to the BSM SR for the BSM pBDT distribution used for mH = 500 GeV.
Data and post-fit background comparison obtained with the background-only fit to the BSM SR for the BSM pBDT distribution used for mH = 600 GeV.
Data and post-fit background comparison obtained with the background-only fit to the BSM SR for the BSM pBDT distribution used for mH = 700 GeV.
Data and post-fit background comparison obtained with the background-only fit to the BSM SR for the BSM pBDT distribution used for mH = 800 GeV.
Data and post-fit background comparison obtained with the background-only fit to the BSM SR for the BSM pBDT distribution used for mH = 900 GeV.
Observed (red line) and expected (black dashed line) exclusion regions at 95% CL in the tan(beta) versus mass plane assuming that only the pseudo-scalar A contributes to the tttt final state.
The product of acceptance and efficiency (A×ε), defined as the number of signal events satisfying the full set of selection criteria of the BSM SR, divided by the total number of generated signal events, for the tt̄H(→ tt̄ ) process in a type-II 2HDM for tanβ = 1 for the different heavy Higgs mass hypotheses.
A search for decays of pair-produced neutral long-lived particles (LLPs) is presented using 139 fb$^{-1}$ of proton-proton collision data collected by the ATLAS detector at the LHC in 2015-2018 at a centre-of-mass energy of 13 TeV. Dedicated techniques were developed for the reconstruction of displaced jets produced by LLPs decaying hadronically in the ATLAS hadronic calorimeter. Two search regions are defined for different LLP kinematic regimes. The observed numbers of events are consistent with the expected background, and limits for several benchmark signals are determined. For a SM Higgs boson with a mass of 125 GeV, branching ratios above 10% are excluded at 95% confidence level for values of $c$ times LLP mean proper lifetime in the range between 20 mm and 10 m depending on the model. Upper limits are also set on the cross-section times branching ratio for scalars with a mass of 60 GeV and for masses between 200 GeV and 1 TeV.
CalRatio triggers which were available during the LHC Run 2 data-taking, and corresponding integrated luminosity collected in each period. The high-E<sub>T</sub> CalRatio trigger with E<sub>T</sub> > 60 GeV was disabled in 2017 for instantaneous luminosities higher than 1.4 × 10<sup>34</sup> cm<sup>-2</sup> s<sup>-1</sup>. Two versions of the low-E<sub>T</sub> CalRatio trigger were used, with slight differences in their algorithms. The details are reported in Section 4.
Trigger efficiency for simulated signal events as a function of the LLP p<sub>T</sub> for one of the low-E<sub>T</sub> signal samples for HLT CalRatio triggers seeded by the high-E<sub>T</sub> L1 triggers with E<sub>T</sub> thresholds of 60 GeV and 100 GeV and by the two versions of the low-E<sub>T</sub> L1 triggers. Only statistical uncertainties are shown.
Trigger efficiency for simulated signal events as a function of the LLP p<sub>T</sub> for one of the high-E<sub>T</sub> signal samples for HLT CalRatio triggers seeded by the high-E<sub>T</sub> L1 triggers with E<sub>T</sub> thresholds of 60 GeV and 100 GeV and by the two versions of the low-E<sub>T</sub> L1 triggers. Only statistical uncertainties are shown.
Trigger efficiency for simulated signal events as a function of the LLP decay position in the x–y plane (L<sub>xy</sub>) for LLPs decaying in the barrel (|η|<1.4) for one of the low-E<sub>T</sub> signal samples for HLT CalRatio triggers seeded by the high-E<sub>T</sub> L1 triggers with E<sub>T</sub> thresholds of 60 GeV and 100 GeV and by the two versions of the low-E<sub>T</sub> L1 triggers. Only statistical uncertainties are shown.
Trigger efficiency for simulated signal events as a function of the LLP decay position in the x–y plane (L<sub>xy</sub>) for LLPs decaying in the barrel (|η|<1.4) for one of the high-E<sub>T</sub> signal samples for HLT CalRatio triggers seeded by the high-E<sub>T</sub> L1 triggers with E<sub>T</sub> thresholds of 60 GeV and 100 GeV and by the two versions of the low-E<sub>T</sub> L1 triggers. Only statistical uncertainties are shown.
The NN output scores in the dijet control region for the low-E<sub>T</sub> training with no adversary network. Statistical uncertainties are shown in all plots. In cases where training with adversary networks is considered, the systematic uncertainty related to modelling discrepancies is included as well.
The NN output scores in the dijet control region for the low-E<sub>T</sub> training with an adversary network included. Statistical uncertainties are shown in all plots. In cases where training with adversary networks is considered, the systematic uncertainty related to modelling discrepancies is included as well.
The NN output scores in the dijet control region for the high-E<sub>T</sub> training with no adversary network. Statistical uncertainties are shown in all plots. In cases where training with adversary networks is considered, the systematic uncertainty related to modelling discrepancies is included as well.
The NN output scores in the dijet control region for the high-E<sub>T</sub> training with an adversary network included. Statistical uncertainties are shown in all plots. In cases where training with adversary networks is considered, the systematic uncertainty related to modelling discrepancies is included as well.
Distribution of the low-E<sub>T</sub> per-event BDT in main data, BIB data and some of the benchmark signal samples after preselection. Only statistical uncertainties are shown.
Distribution of the high-E<sub>T</sub> per-event BDT outputs in main data, BIB data and some of the benchmark signal samples after preselection. Only statistical uncertainties are shown.
Sequential impact of each requirement on the number of events passing the selection for the high-E<sub>T</sub> selections. The signal columns represent the cumulative fraction of events passing the selection than the number of events.
Sequential impact of each requirement on the number of events passing the selection for the low-E<sub>T</sub> selections. The signal columns represent the cumulative fraction of events passing the selection than the number of events.
Application of the modified ABCD method to the final high-E<sub>T</sub> selections. The a priori estimate refers to the "pre-unblinding" case, where the data in region A are ignored by removing the Poisson constraint in that region and the signal strength is fixed to zero. This matches the simple N<sup>bkg</sup><sub>A</sub>=(N<sup>bkg</sup><sub>B</sub>· N<sup>bkg</sup><sub>C</sub>)/N<sup>bkg</sup><sub>D</sub> relation. The a posteriori estimate refers to the "post-unblinding" case, including the observed data in region A in the background-only global fit, obtained by fixing the signal strength to 0 (background-only fit) or allowing it to float (signal-plus-background fit). The table also shows one set of representative signal yields in each selection for the signal-plus-background fit. Only statistical uncertainties are included in the quoted error of the background, while the uncertainties in the signal include those from both statistical and experimental sources.
Application of the modified ABCD method to the final low-E<sub>T</sub> selections. The a priori estimate refers to the "pre-unblinding" case, where the data in region A are ignored by removing the Poisson constraint in that region and the signal strength is fixed to zero. This matches the simple N<sup>bkg</sup><sub>A</sub>=(N<sup>bkg</sup><sub>B</sub>· N<sup>bkg</sup><sub>C</sub>)/N<sup>bkg</sup><sub>D</sub> relation. The a posteriori estimate refers to the "post-unblinding" case, including the observed data in region A in the background-only global fit, obtained by fixing the signal strength to 0 (background-only fit) or allowing it to float (signal-plus-background fit). The table also shows one set of representative signal yields in each selection for the signal-plus-background fit. Only statistical uncertainties are included in the quoted error of the background, while the uncertainties in the signal include those from both statistical and experimental sources.
95% CL expected and observed limits on the BR of SM Higgs bosons to pairs of neutral LLPs (B<sub>H→ ss</sub>), showing the ± 1 σ (green) and ± 2 σ (yellow) expected limit bands, as well as a comparison with the results from previous ATLAS searches [36,78]. The cross-section for SM Higgs boson gluon--gluon fusion production is assumed to be 48.6 pb.
Trigger efficiency of simulated signal events as a function of the LLP decay position in the z direction for LLPs decaying in the calorimeter endcaps (1.4 ≤ |η| < 2.5) for one of the low-E<sub>T</sub> signal samples for HLT CalRatio triggers seeded by the 60 GeV-high-E<sub>T</sub> trigger and by the two versions of the low-E<sub>T</sub> triggers.
Trigger efficiency of simulated signal events as a function of the LLP decay position in the z direction for LLPs decaying in the calorimeter endcaps (1.4 ≤ |η| < 2.5) for one of the high-E<sub>T</sub> signal samples for HLT CalRatio triggers seeded by the 60 GeV-high-E<sub>T</sub> trigger and by the two versions of the low-E<sub>T</sub> triggers.
The simulated efficiencies as a function of c times the mean proper lifetime (cτ) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.
The simulated efficiencies as a function of c times the mean proper lifetime (cτ) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.
The simulated efficiencies as a function of c times the mean proper lifetime (cτ) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.
The simulated efficiencies as a function of c times the mean proper lifetime (cτ) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.
The simulated efficiencies as a function of c times the mean proper lifetime (cτ) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.
The simulated efficiencies as a function of c times the mean proper lifetime (cτ) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.
The simulated efficiencies as a function of c times the mean proper lifetime (cτ) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.
The simulated efficiencies as a function of c times the mean proper lifetime (cτ) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.
The simulated efficiencies as a function of c times the mean proper lifetime (cτ) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.
The simulated efficiencies as a function of c times the mean proper lifetime (cτ) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.
The simulated efficiencies as a function of c times the mean proper lifetime (cτ) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.
The simulated efficiencies as a function of c times the mean proper lifetime (cτ) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.
The simulated efficiencies as a function of c times the mean proper lifetime (cτ) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.
The simulated efficiencies as a function of c times the mean proper lifetime (cτ) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.
The event BDT in the dijet control region for the low-E<sub>T</sub> training training. The uncertainties are combined statistical and ML modelling systematic uncertainty.
The event BDT in the dijet control region for the high-E<sub>T</sub> training. The uncertainties are combined statistical and ML modelling systematic uncertainty.
The 95% CL observed limits, expected limits and ± 1 σ and 2 σ bands for the Φ mass of 60 GeV compared to the results from the 2016-data analysis and subsequent combinations, where available.
The 95% CL observed limits, expected limits and ± 1 σ and 2 σ bands for the Φ mass of 60 GeV compared to the results from the 2016-data analysis and subsequent combinations, where available.
The 95% CL observed limits, expected limits and ± 1 σ and 2 σ bands for the Φ mass 125 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available.
The 95% CL observed limits, expected limits and ± 1 σ and 2 σ bands for the Φ mass 125 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available. The 125 GeV mediator is assumed to be the SM Higgs boson.
The 95% CL observed limits, expected limits and ± 1 σ and 2 σ bands for the Φ mass 125 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available. The 125 GeV mediator is assumed to be the SM Higgs boson.
The 95% CL observed limits, expected limits and ± 1 σ and 2 σ bands for the Φ mass of 200 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available.
The 95% CL observed limits, expected limits and ± 1 σ and 2 σ bands for the Φ mass of 400 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available.
The 95% CL observed limits, expected limits and ± 1 σ and 2 σ bands for the Φ mass 600 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available.
The 95% CL observed limits, expected limits and ± 1 σ and 2 σ bands for the Φ mass of 600 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available.
The 95% CL observed limits, expected limits and ± 1 σ and 2 σ bands for the Φ masses of of 1000 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available.
The 95% CL observed limits, expected limits and ± 1 σ and 2 σ bands for the Φ masses of of 1000 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available.
The 95% CL observed limits, expected limits and ± 1 σ and 2 σ bands for the Φ masses of of 1000 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available.
The 95% CL observed limits, expected limits and ± 1 σ and 2 σ bands for the Φ masses of of 1000 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available.
Efficiency for an event to enter Region A of the high-E<sub>T</sub> selection, as a function of the two LLP kinematics, decay type and decay position. LLP p<sub>T</sub> is binned in the ranges of [0, 50 , 100, 200 , 400, 1600] GeV (5 bins), the LLP decay position is binned in decay position in L<sub>xy</sub> in [0, 1.5, 2, 2.5, 3, 3.5, 3.9, ∞] m for LLPs with |η| < 1.5 and L<sub>z</sub> in [0, 3.6, 4.2, 4.8, 5.5, 6, ∞ ] m for LLPs with |η|geq1.5, 13 bins in all. Finally, four decay types are considered: LLPs decaying to pairs of c, b, t, or τ in bins 0, 1, 2, 3 respectively. The efficiency is presented as a function of "Bin Index", which is calculated as follows: Bin Index = (decay position bin index ) × (number of p<sub>T</sub> bins × number of decay type bins) + p<sub>T</sub> bin index * (number of decay type bin) + decay type bin index. The efficiency for a given pair-produced LLP sample can be obtained by summing the efficiency values for each event as extracted from this map, and dividing it by the total number of events in the sample. The efficiency map is symmetric between the LLPs, so the choice of LLP1 and LLP2 is arbitrary. For the high-E<sub>T</sub> selections, for overall efficiencies above 0.5%, the results are typically accurate to around 25%, but below this the efficiency can be overestimated and therefore should not be used for re-interpration.
Efficiency for an event to enter Region A of the low-E<sub>T</sub> selection, as a function of the two LLP kinematics, decay type and decay position. LLP p<sub>T</sub> is binned in the ranges of [0, 50 , 100, 200 , 400, 1600] GeV (5 bins), the LLP decay position is binned in L<sub>xy</sub> in [0, 1.5, 2, 2.5, 3, 3.5, 3.9, ∞] m for LLPs with |η| < 1.5 and L<sub>z</sub> in [0, 3.6, 4.2, 4.8, 5.5, 6, ∞ ] m for LLPs with |η|geq1.5, 13 bins in all. Finally, four decay types are considered: LLPs decaying to pairs of c, b, t, or τ in bins 0, 1, 2, 3 respectively. The efficiency is presented as a function of "Bin Index", which is calculated as follows: Bin Index = (decay position bin index ) × (number of p<sub>T</sub> bins × number of decay type bins) + p<sub>T</sub> bin index * (number of decay type bin) + decay type bin index. The efficiency for a given pair-produced LLP sample can be obtained by summing the efficiency values for each event as extracted from this map, and dividing it by the total number of events in the sample. The efficiency map is symmetric between the LLPs, so the choice of LLP1 and LLP2 is arbitrary. For the low-E<sub>T</sub> selections, for overall efficiencies above 0.15%, the results are typically accurate to around 33%, and below this the efficiency is typically accurate up to a factor of 3.
A measurement of observables sensitive to effects of colour reconnection in top-quark pair-production events is presented using 139 fb$^{-1}$ of 13$\,$TeV proton-proton collision data collected by the ATLAS detector at the LHC. Events are selected by requiring exactly one isolated electron and one isolated muon with opposite charge and two or three jets, where exactly two jets are required to be $b$-tagged. For the selected events, measurements are presented for the charged-particle multiplicity, the scalar sum of the transverse momenta of the charged particles, and the same scalar sum in bins of charged-particle multiplicity. These observables are unfolded to the stable-particle level, thereby correcting for migration effects due to finite detector resolution, acceptance and efficiency effects. The particle-level measurements are compared with different colour reconnection models in Monte Carlo generators. These measurements disfavour some of the colour reconnection models and provide inputs to future optimisation of the parameters in Monte Carlo generators.
Binning used for the measured $\sum_{n_{\text{ch}}} p_{\text{T}}$ in bins of $n_\text{ch}$ observable.
Event yields obtained after the event selection. The expected event yields from $t\bar{t}$ production and the various background processes are compared with the observed event yield. The fractional contributions from $t\bar{t}$ production and the background processes to the expected event yield is given in %. The processes labelled by `Others' include production of $Z$+jets and diboson background events. The uncertainties include the MC statistical uncertainty and the normalisation uncertainty.
Summary of the estimated pile-up scale factors $c_{\text{PU}}$, parameterisd in $\mu$ and $n_{\text{trk,out}}$. All values have a statistical precision of 0.01.
Naming convention for the observables at different levels of the analysis. At the background-subtracted level the contributions of tracks from pile-up collisions and tracks from secondary vertices are subtracted. At the corrected level the tracking-efficiency correction (TEC) is applied. The observables at particle level are the analysis results.
The total pile-up scale-factor relative uncertainty parameterised in $\mu$ and $n_\text{trk,out}$ and expressed in percent.
The $\chi^2$ and NDF for measured normalised differential cross-sections obtained by comparing the different predictions with the unfolded data. Global($n_\text{ch},\Sigma_{n_{\text{ch}}} p_{\text{T}}$) denotes the scenario in which the covariance matrix is built including the correlations of systematic uncertainties between the two observables $n_{\text{ch}}$ and $\Sigma_{n_{\text{ch}}} p_{\text{T}}$
Normalised differential cross-section as a function of $n_\text{ch}$.
Normalised differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$.
Normalised double-differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$.
Normalised double-differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$.
Normalised double-differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 40 \leq n_\text{ch} < 60$.
Normalised double-differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 60 \leq n_\text{ch} < 80$.
Normalised double-differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n\text{ch}$ in $ n_\text{ch} \geq 80$.
The $\chi^2$ and NDF for the measured normalised differential cross-sections obtained by comparing the different predictions with the unfolded data. The values corresponding to the `Total' scenario are given. In this scenario, only uncertainties described in Section 8 of the paper are included, while the extra theory uncertainties defined in Section 9 are omitted.
The $\chi^2$ and NDF for the measured normalised differential cross-sections obtained by comparing the different predictions with the unfolded data. The values corresponding to the `De-correlate modelling' scenario are given. This scenario uses the detector covariance matrix, and adding modelling uncertainties, scale variations in the matrix element and parton shower as well as the $h_{\text{damp}}$ variation only to the diagonal elements of the covariance matrix.
The $\chi^2$ and NDF for measured absolute differential cross-sections obtained by comparing the different predictions with the unfolded data. Global($n_\text{ch},\Sigma_{n_{\text{ch}}} p_{\text{T}}$) denotes the scenario in which the covariance matrix is built including the correlations of systematic uncertainties between the two observables $n_{\text{ch}}$ and $\Sigma_{n_{\text{ch}}} p_{\text{T}}$
The $\chi^2$ and NDF for the measured absolute differential cross-sections obtained by comparing the different predictions with the unfolded data. The values corresponding to the `Total' scenario are given. In this scenario, only uncertainties described in Section 8 of the paper are included, while the extra theory uncertainties defined in Section 9 are omitted.
The $\chi^2$ and NDF for the measured normalised differential cross-sections obtained by comparing the different predictions with the unfolded data. The values corresponding to the `De-correlate modelling' scenario are given. This scenario uses the detector covariance matrix, and adding modelling uncertainties, scale variations in the matrix element and parton shower as well as the $h_{\text{damp}}$ variation only to the diagonal elements of the covariance matrix.
Absolute differential cross-section as a function of $n_\text{ch}$.
Absolute differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$.
Absolute double-differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$.
Absolute double-differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$.
Absolute double-differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 40 \leq n_\text{ch} < 60$.
Absolute double-differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 60 \leq n_\text{ch} < 80$.
Absolute double-differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n\text{ch}$ in $ n_\text{ch} \geq 80$.
Covariance matrix of the normalised differential cross-section as function of $n_\text{ch}$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix of the normalised differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ n_\text{ch} < 20$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $40 \leq n_\text{ch} < 60$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $60 \leq n_\text{ch} < 80$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $40 \leq n_\text{ch} < 60$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $60 \leq n_\text{ch} < 80$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 40 \leq n_\text{ch} < 60$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 40 \leq n_\text{ch} < 60$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 40 \leq n_\text{ch} < 60$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $40 \leq n_\text{ch} < 60$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 40 \leq n_\text{ch} < 60$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $60 \leq n_\text{ch} < 80$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 40 \leq n_\text{ch} < 60$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 60 \leq n_\text{ch} < 80$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 60 \leq n_\text{ch} < 80$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 60 \leq n_\text{ch} < 80$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $40 \leq n_\text{ch} < 60$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 60 \leq n_\text{ch} < 80$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $60 \leq n_\text{ch} < 80$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 60 \leq n_\text{ch} < 80$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $40 \leq n_\text{ch} < 60$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $60 \leq n_\text{ch} < 80$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Global covariance matrix of the normalised differential cross-section as function of $n_\text{ch}$ and $\sum_{n_{\text{ch}}} p_{\text{T}}$ in $n_\text{ch}$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Global covariance matrix of the normalised differential cross-section as function of $n_\text{ch}$ and $\sum_{n_{\text{ch}}} p_{\text{T}}$ in $n_\text{ch}$ vs. $\sum_{n_{\text{ch}}} p_{\text{T}}$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Global covariance matrix of the normalised differential cross-section as function of $n_\text{ch}$ and $\sum_{n_{\text{ch}}} p_{\text{T}}$ in $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Global covariance matrix of the normalised differential cross-section as function of $n_\text{ch}$ and $\sum_{n_{\text{ch}}} p_{\text{T}}$ in $\sum_{n_{\text{ch}}} p_{\text{T}}$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix of the normalised differential cross-section as function of $n_\text{ch}$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix of the normalised differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ n_\text{ch} < 20$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $40 \leq n_\text{ch} < 60$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $60 \leq n_\text{ch} < 80$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $40 \leq n_\text{ch} < 60$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $60 \leq n_\text{ch} < 80$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 40 \leq n_\text{ch} < 60$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 40 \leq n_\text{ch} < 60$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 40 \leq n_\text{ch} < 60$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $40 \leq n_\text{ch} < 60$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 40 \leq n_\text{ch} < 60$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $60 \leq n_\text{ch} < 80$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 40 \leq n_\text{ch} < 60$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 60 \leq n_\text{ch} < 80$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 60 \leq n_\text{ch} < 80$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 60 \leq n_\text{ch} < 80$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $40 \leq n_\text{ch} < 60$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 60 \leq n_\text{ch} < 80$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $60 \leq n_\text{ch} < 80$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 60 \leq n_\text{ch} < 80$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $40 \leq n_\text{ch} < 60$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $60 \leq n_\text{ch} < 80$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ and the normalised double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Global covariance matrix of the normalised differential cross-section as function of $n_\text{ch}$ and $\sum_{n_{\text{ch}}} p_{\text{T}}$ in $n_\text{ch}$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Global covariance matrix of the normalised differential cross-section as function of $n_\text{ch}$ and $\sum_{n_{\text{ch}}} p_{\text{T}}$ in $n_\text{ch}$ vs. $\sum_{n_{\text{ch}}} p_{\text{T}}$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Global covariance matrix of the normalised differential cross-section as function of $n_\text{ch}$ and $\sum_{n_{\text{ch}}} p_{\text{T}}$ in $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Global covariance matrix of the normalised differential cross-section as function of $n_\text{ch}$ and $\sum_{n_{\text{ch}}} p_{\text{T}}$ in $\sum_{n_{\text{ch}}} p_{\text{T}}$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix of the absolute differential cross-section as function of $n_\text{ch}$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix of the absolute differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ n_\text{ch} < 20$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $40 \leq n_\text{ch} < 60$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $60 \leq n_\text{ch} < 80$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $40 \leq n_\text{ch} < 60$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $60 \leq n_\text{ch} < 80$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 40 \leq n_\text{ch} < 60$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 40 \leq n_\text{ch} < 60$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 40 \leq n_\text{ch} < 60$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $40 \leq n_\text{ch} < 60$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 40 \leq n_\text{ch} < 60$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $60 \leq n_\text{ch} < 80$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 40 \leq n_\text{ch} < 60$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 60 \leq n_\text{ch} < 80$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 60 \leq n_\text{ch} < 80$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 60 \leq n_\text{ch} < 80$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $40 \leq n_\text{ch} < 60$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 60 \leq n_\text{ch} < 80$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $60 \leq n_\text{ch} < 80$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 60 \leq n_\text{ch} < 80$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $40 \leq n_\text{ch} < 60$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $60 \leq n_\text{ch} < 80$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Global covariance matrix of the absolute differential cross-section as function of $n_\text{ch}$ and $\sum_{n_{\text{ch}}} p_{\text{T}}$ in $n_\text{ch}$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Global covariance matrix of the absolute differential cross-section as function of $n_\text{ch}$ and $\sum_{n_{\text{ch}}} p_{\text{T}}$ in $n_\text{ch}$ vs. $\sum_{n_{\text{ch}}} p_{\text{T}}$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Global covariance matrix of the absolute differential cross-section as function of $n_\text{ch}$ and $\sum_{n_{\text{ch}}} p_{\text{T}}$ in $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Global covariance matrix of the absolute differential cross-section as function of $n_\text{ch}$ and $\sum_{n_{\text{ch}}} p_{\text{T}}$ in $\sum_{n_{\text{ch}}} p_{\text{T}}$ at particle level, accounting for the statistical, systematic uncertainties, and uncertainties in the theoretical predictions.
Covariance matrix of the absolute differential cross-section as function of $n_\text{ch}$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix of the absolute differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ n_\text{ch} < 20$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $40 \leq n_\text{ch} < 60$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $60 \leq n_\text{ch} < 80$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $40 \leq n_\text{ch} < 60$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $60 \leq n_\text{ch} < 80$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 40 \leq n_\text{ch} < 60$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 40 \leq n_\text{ch} < 60$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 40 \leq n_\text{ch} < 60$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $40 \leq n_\text{ch} < 60$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 40 \leq n_\text{ch} < 60$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $60 \leq n_\text{ch} < 80$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 40 \leq n_\text{ch} < 60$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 60 \leq n_\text{ch} < 80$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 60 \leq n_\text{ch} < 80$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 60 \leq n_\text{ch} < 80$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $40 \leq n_\text{ch} < 60$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 60 \leq n_\text{ch} < 80$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $60 \leq n_\text{ch} < 80$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 60 \leq n_\text{ch} < 80$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $40 \leq n_\text{ch} < 60$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $60 \leq n_\text{ch} < 80$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Covariance matrix between the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ and the absolute double-differential cross-section as function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} \geq 80$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Global covariance matrix of the absolute differential cross-section as function of $n_\text{ch}$ and $\sum_{n_{\text{ch}}} p_{\text{T}}$ in $n_\text{ch}$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Global covariance matrix of the absolute differential cross-section as function of $n_\text{ch}$ and $\sum_{n_{\text{ch}}} p_{\text{T}}$ in $n_\text{ch}$ vs. $\sum_{n_{\text{ch}}} p_{\text{T}}$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Global covariance matrix of the absolute differential cross-section as function of $n_\text{ch}$ and $\sum_{n_{\text{ch}}} p_{\text{T}}$ in $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
Global covariance matrix of the absolute differential cross-section as function of $n_\text{ch}$ and $\sum_{n_{\text{ch}}} p_{\text{T}}$ in $\sum_{n_{\text{ch}}} p_{\text{T}}$ at particle level, accounting for the statistical and systematic uncertainties, but excluding uncertainties in the theoretical predictions.
This paper presents a search for dark matter, $\chi$, using events with a single top quark and an energetic $W$ boson. The analysis is based on proton-proton collision data collected with the ATLAS experiment at $\sqrt{s}=$ 13 TeV during LHC Run 2 (2015-2018), corresponding to an integrated luminosity of 139 fb$^{-1}$. The search considers final states with zero or one charged lepton (electron or muon), at least one $b$-jet and large missing transverse momentum. In addition, a result from a previous search considering two-charged-lepton final states is included in the interpretation of the results. The data are found to be in good agreement with the Standard Model predictions and the results are interpreted in terms of 95% confidence-level exclusion limits in the context of a class of dark matter models involving an extended two-Higgs-doublet sector together with a pseudoscalar mediator particle. The search is particularly sensitive to on-shell production of the charged Higgs boson state, $H^{\pm}$, arising from the two-Higgs-doublet mixing, and its semi-invisible decays via the mediator particle, $a$: $H^{\pm} \rightarrow W^\pm a (\rightarrow \chi\chi)$. Signal models with $H^{\pm}$ masses up to 1.5 TeV and $a$ masses up to 350 GeV are excluded assuming a tan$\beta$ value of 1. For masses of $a$ of 150 (250) GeV, tan$\beta$ values up to 2 are excluded for $H^{\pm}$ masses between 200 (400) GeV and 1.5 TeV. Signals with tan$\beta$ values between 20 and 30 are excluded for $H^{\pm}$ masses between 500 and 800 GeV.
The observed exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour.
The observed exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour.
The observed exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour.
The observed exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour.
The observed exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The observed exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The observed exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The observed exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The observed exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The observed exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The observed exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The observed exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The observed exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The observed exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
Model dependent upper limit on the cross section for the $m_a$ vs. $ m_{H^{\pm}}$ signal grid assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 150 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 250 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_a$ vs. $ m_{H^{\pm}}$ signal grid assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 150 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 250 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_a$ vs. $ m_{H^{\pm}}$ signal grid assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 150 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 250 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_a$ vs. $ m_{H^{\pm}}$ signal grid assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 150 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 250 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_a$ vs. $ m_{H^{\pm}}$ signal grid assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 150 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 250 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_a$ vs. $ m_{H^{\pm}}$ signal grid assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 150 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 250 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_a$ vs. $ m_{H^{\pm}}$ signal grid assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 150 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 250 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_a$ vs. $ m_{H^{\pm}}$ signal grid assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 150 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 250 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_a$ vs. $ m_{H^{\pm}}$ signal grid assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 150 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 250 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_a$ vs. $ m_{H^{\pm}}$ signal grid assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 150 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 250 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_a$ vs. $ m_{H^{\pm}}$ signal grid assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 150 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 250 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_a$ vs. $ m_{H^{\pm}}$ signal grid assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 150 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 250 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
The distributions of $m_{\mathrm{b1},\mathrm{W-tagged}}$ in the 0L inclusive signal region. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.
The distributions of $m_{\mathrm{T}}^{\mathrm{b,E_{\mathrm{T}^{\mathrm{miss}}}}}$ in the 0L inclusive signal region. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.
The distributions of $N_{\mathrm{W-tagged}}$ in the 0L inclusive signal region. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.
The distributions of $m_{\mathrm{b1},\mathrm{\cancel{b1}}}$ in the hadronic top inclusive signal region. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.
The distributions of $m_{\mathrm{b1},\mathrm{\cancel{b1}}}$ in the leptonic top inclusive signal region. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.
The distributions of $m_{\mathrm{b1},\mathrm{\cancel{b1}}}$ in the leptonic top inclusive signal region. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.
Cutflow for the reference point $(\it{m}_{\mathrm{H^{\pm}}}, \it{m}_{a}, tan\beta, sin\theta )=$ (500,100,1,0.7) , (800,150,20,0.7), (600,250,30,0.7), (1000,400,1,0.7) in 0L regions. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.
Cutflow for the reference point $(\it{m}_{\mathrm{H^{\pm}}}, \it{m}_{a}, tan\beta, sin\theta )=$ (500,100,1,0.7) , (800,150,20,0.7), (600,250,30,0.7), (1000,400,1,0.7) in 1L leptonic top regions. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.
Cutflow for the reference point $(\it{m}_{\mathrm{H^{\pm}}}, \it{m}_{a}, tan\beta, sin\theta )=$ (500,100,1,0.7) , (800,150,20,0.7), (600,250,30,0.7), (1000,400,1,0.7) in 1L hadronic top regions. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.
Signal acceptance in the 0L region for 2HDM+a model DM signals on the plane defined by m$_a$--m$_{H^{\pm}}$ assuming tan$\beta$ = 1, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.7. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in the 0L region for 2HDM+a model DM signals on the plane defined by m$_a$--m$_{H^{\pm}}$ assuming tan$\beta$ = 1, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.7. Please mind that the efficiency given in the table is multiplied by factor of $10^{2}$
Signal acceptance in the 0L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 150 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.7. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in the 0L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 150 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.7. Please mind that the efficiency given in the table is multiplied by factor of $10^{2}$
Signal acceptance in the 0L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 250 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.7. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in the 0L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 250 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.7. Please mind that the efficiency given in the table is multiplied by factor of $10^{2}$
Signal acceptance in the 1L region for 2HDM+a model DM signals on the plane defined by m$_a$--m$_{H^{\pm}}$ assuming tan$\beta$ = 1, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.7. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in the 1L region for 2HDM+a model DM signals on the plane defined by m$_a$--m$_{H^{\pm}}$ assuming tan$\beta$ = 1, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.7. Please mind that the efficiency given in the table is multiplied by factor of $10^{2}$
Signal acceptance in the 1L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 150 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.7. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in the 1L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 150 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.7. Please mind that the efficiency given in the table is multiplied by factor of $10^{2}$
Signal acceptance in the 1L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 250 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.7. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in the 1L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 250 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.7. Please mind that the efficiency given in the table is multiplied by factor of $10^{2}$
Signal acceptance in the 0L region for 2HDM+a model DM signals on the plane defined by m$_a$--m$_{H^{\pm}}$ assuming tan$\beta$ = 1, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.35. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in the 0L region for 2HDM+a model DM signals on the plane defined by m$_a$--m$_{H^{\pm}}$ assuming tan$\beta$ = 1, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.35. Please mind that the efficiency given in the table is multiplied by factor of $10^{2}$
Signal acceptance in the 0L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 150 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.35. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in the 0L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 150 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.35. Please mind that the efficiency given in the table is multiplied by factor of $10^{2}$
Signal acceptance in the 0L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 250 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.35. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in the 0L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 250 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.35. Please mind that the efficiency given in the table is multiplied by factor of $10^{2}$
Signal acceptance in the 1L region for 2HDM+a model DM signals on the plane defined by m$_a$--m$_{H^{\pm}}$ assuming tan$\beta$ = 1, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.35. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in the 1L region for 2HDM+a model DM signals on the plane defined by m$_a$--m$_{H^{\pm}}$ assuming tan$\beta$ = 1, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.35. Please mind that the efficiency given in the table is multiplied by factor of $10^{2}$
Signal acceptance in the 1L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 150 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.35. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in the 1L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 150 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.35. Please mind that the efficiency given in the table is multiplied by factor of $10^{2}$
Signal acceptance in the 1L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 250 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.35. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in the 1L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 250 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.35. Please mind that the efficiency given in the table is multiplied by factor of $10^{2}$
This paper presents measurements of charged-hadron spectra obtained in $pp$, $p$+Pb, and Pb+Pb collisions at $\sqrt{s}$ or $\sqrt{s_{_\text{NN}}}=5.02$ TeV, and in Xe+Xe collisions at $\sqrt{s_{_\text{NN}}}=5.44$ TeV. The data recorded by the ATLAS detector at the LHC have total integrated luminosities of 25 pb${}^{-1}$, 28 nb${}^{-1}$, 0.50 nb${}^{-1}$, and 3 $\mu$b${}^{-1}$, respectively. The nuclear modification factors $R_{p\text{Pb}}$ and $R_\text{AA}$ are obtained by comparing the spectra in heavy-ion and $pp$ collisions in a wide range of charged-particle transverse momenta and pseudorapidity. The nuclear modification factor $R_{p\text{Pb}}$ shows a moderate enhancement above unity with a maximum at $p_{\mathrm{T}} \approx 3$ GeV; the enhancement is stronger in the Pb-going direction. The nuclear modification factors in both Pb+Pb and Xe+Xe collisions feature a significant, centrality-dependent suppression. They show a similar distinct $p_{\mathrm{T}}$-dependence with a local maximum at $p_{\mathrm{T}} \approx 2$ GeV and a local minimum at $p_{\mathrm{T}} \approx 7$ GeV. This dependence is more distinguishable in more central collisions. No significant $|\eta|$-dependence is found. A comprehensive comparison with several theoretical predictions is also provided. They typically describe $R_\text{AA}$ better in central collisions and in the $p_{\mathrm{T}}$ range from about 10 to 100 GeV.
Charged-hadron cross-section in pp collisions. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Charged-hadron spectrum in the centrality interval 0-5% for p+Pb, divided by 〈TPPB〉. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Charged-hadron spectrum in the centrality interval 5-10% for p+Pb, divided by 〈TPPB〉. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Charged-hadron spectrum in the centrality interval 10-20% for p+Pb, divided by 〈TPPB〉. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Charged-hadron spectrum in the centrality interval 20-30% for p+Pb, divided by 〈TPPB〉. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Charged-hadron spectrum in the centrality interval 30-40% for p+Pb, divided by 〈TPPB〉. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Charged-hadron spectrum in the centrality interval 40-60% for p+Pb, divided by 〈TPPB〉. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Charged-hadron spectrum in the centrality interval 60-90% for p+Pb, divided by 〈TPPB〉. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Charged-hadron spectrum in the centrality interval 0-90% for p+Pb, divided by 〈TPPB〉. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Charged-hadron cross-section in pp collisions. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Charged-hadron spectrum in the centrality interval 0-5% for Pb+Pb, divided by 〈TAA〉. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.
Charged-hadron spectrum in the centrality interval 5-10% for Pb+Pb, divided by 〈TAA〉. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.
Charged-hadron spectrum in the centrality interval 10-20% for Pb+Pb, divided by 〈TAA〉. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.
Charged-hadron spectrum in the centrality interval 20-30% for Pb+Pb, divided by 〈TAA〉. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.
Charged-hadron spectrum in the centrality interval 30-40% for Pb+Pb, divided by 〈TAA〉. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.
Charged-hadron spectrum in the centrality interval 40-50% for Pb+Pb, divided by 〈TAA〉. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.
Charged-hadron spectrum in the centrality interval 50-60% for Pb+Pb, divided by 〈TAA〉. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.
Charged-hadron spectrum in the centrality interval 60-80% for Pb+Pb, divided by 〈TAA〉. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.
Charged-hadron cross-section in pp collisions. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Charged-hadron spectrum in the centrality interval 0-5% for Xe+Xe, divided by 〈TAA〉. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Charged-hadron spectrum in the centrality interval 5-10% for Xe+Xe, divided by 〈TAA〉. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Charged-hadron spectrum in the centrality interval 10-20% for Xe+Xe, divided by 〈TAA〉. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Charged-hadron spectrum in the centrality interval 20-30% for Xe+Xe, divided by 〈TAA〉. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Charged-hadron spectrum in the centrality interval 30-40% for Xe+Xe, divided by 〈TAA〉. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Charged-hadron spectrum in the centrality interval 40-50% for Xe+Xe, divided by 〈TAA〉. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Charged-hadron spectrum in the centrality interval 50-60% for Xe+Xe, divided by 〈TAA〉. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Charged-hadron spectrum in the centrality interval 60-80% for Xe+Xe, divided by 〈TAA〉. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 0-5% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 5-10% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 10-20% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 20-30% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 30-40% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 40-60% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 60-90% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 0-90% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 0-5% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.
Nuclear modification factor in centrality interval 5-10% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.
Nuclear modification factor in centrality interval 10-20% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.
Nuclear modification factor in centrality interval 20-30% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.
Nuclear modification factor in centrality interval 30-40% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.
Nuclear modification factor in centrality interval 40-50% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.
Nuclear modification factor in centrality interval 50-60% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.
Nuclear modification factor in centrality interval 60-80% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature. The systematic uncertainty on momentum bias is negligible at low pT; in such cases, it is omitted in the table below.
Nuclear modification factor in centrality interval 0-5% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 5-10% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 10-20% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 20-30% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 30-40% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 40-50% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 50-60% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 60-80% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 0-5% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 0-5% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 0-5% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 0-5% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 5-10% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 5-10% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 5-10% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 5-10% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 10-20% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 10-20% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 10-20% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 10-20% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 20-30% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 20-30% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 20-30% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 20-30% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 30-40% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 30-40% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 30-40% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 30-40% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 40-60% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 40-60% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 40-60% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 40-60% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 60-90% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 60-90% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 60-90% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 60-90% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 0-90% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 0-90% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 0-90% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 0-90% for p+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 0-5% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 0-5% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 0-5% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 0-5% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 5-10% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 5-10% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 5-10% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 5-10% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 10-20% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 10-20% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 10-20% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 10-20% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 20-30% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 20-30% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 20-30% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 20-30% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 30-40% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 30-40% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 30-40% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 30-40% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 40-50% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 40-50% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 40-50% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 40-50% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 50-60% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 50-60% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 50-60% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 50-60% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 60-80% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 60-80% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 60-80% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 60-80% for Pb+Pb. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 0-5% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 0-5% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 0-5% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 5-10% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 5-10% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 5-10% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 10-20% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 10-20% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 10-20% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 20-30% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 20-30% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 20-30% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 30-40% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 30-40% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 30-40% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 40-50% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 40-50% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 40-50% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 50-60% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 50-60% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 50-60% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 60-80% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 60-80% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
Nuclear modification factor in centrality interval 60-80% for Xe+Xe. The systematic uncertainties are described in the section 7 of the paper. The total systematic uncertainties are determined by adding the contributions from all relevant sources in quadrature.
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