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A search for heavy resonances decaying to a pair of Z bosons is performed using data collected with the CMS detector at the LHC. Events are selected by requiring two oppositely charged leptons (electrons or muons), consistent with the decay of a Z boson, and large missing transverse momentum, which is interpreted as arising from the decay of a second Z boson to two neutrinos. The analysis uses data from proton-proton collisions at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 35.9 fb$^{-1}$. The hypothesis of a spin-2 bulk graviton (X) decaying to a pair of Z bosons is examined for 600 $\le m_\mathrm{X} \le$ 2500 GeV and upper limits at 95% confidence level are set on the product of the production cross section and branching fraction of X $\to$ ZZ ranging from 100 to 4 fb. For bulk graviton models characterized by a curvature scale parameter $\tilde{k} =$ 0.5 in the extra dimension, the region $m_\mathrm{X} < $ 800 GeV is excluded, providing the most stringent limit reported to date. Variations of the model considering the possibility of a wide resonance produced exclusively via gluon-gluon fusion or $\mathrm{q}\overline{\mathrm{q}}$ annihilation are also examined.
The $p_T^Z$ distributions for electron channel comparing the data and background model with systematic uncertainty.
The $p_T^Z$ distributions for muon channel comparing the data and background model with systematic uncertainty.
The $p_T ^{miss}$ distributions for electron channel comparing the data and background model with systematic uncertainty.
The $p_T ^{miss}$ distributions for muon channel comparing the data and background model with systematic uncertainty.
The $m_T$ distributions for electron channel comparing the data and background model with systematic uncertainty, after fitting the background-only model to the data.
The $m_T$ distributions for muon channel comparing the data and background model with systematic uncertainty, after fitting the background-only model to the data.
Expected and observed limits on the product of cross section and branching fraction of a new spin-2 heavy resonance X$\rightarrow$ZZ, assuming zero width, based on the combined analysis of the electron and muon channels.
Expected and observed limits on the product of cross section and branching fraction of a new spin-2 heavy resonance X$\rightarrow$ZZ, assuming zero width, based on the combined analysis of the electron channels.
Expected and observed limits on the product of cross section and branching fraction of a new spin-2 heavy resonance X$\rightarrow$ZZ, assuming zero width, based on the combined analysis of the muon channels.
Expected and observed limits on the product of cross section and branching fraction of a new spin-2 heavy resonance X$\rightarrow$ZZ based on a combined analysis of the electron and muon channels. The more generic version of the bulk graviton model takes 0/10%/20%/30% mass width of the resonance into consideration, assuming gluon-gluon fusion production.
Expected and observed limits on the product of cross section and branching fraction of a new spin-2 heavy resonance X$\rightarrow$ZZ based on a combined analysis of the electron and muon channels. The more generic version of the bulk graviton model takes 0/10%/20%/30% mass width of the resonance into consideration, assuming qq annihilation production.
This paper presents a measurement of the underlying event activity in proton-proton collisions at a center-of-mass energy of 13 TeV, performed using inclusive Z boson production events collected with the CMS experiment at the LHC. The analyzed data correspond to an integrated luminosity of 2.1 fb$^{-1}$. The underlying event activity is quantified in terms of the charged particle multiplicity, as well as of the scalar sum of the charged particles' transverse momenta in different topological regions defined with respect to the Z boson direction. The distributions are unfolded to the stable particle level and compared with predictions from various Monte Carlo event generators, as well as with similar CDF and CMS measurements at center-of-mass energies of 1.96 and 7 TeV respectively.
Unfolded distributions of particle density in Z events, as a function of $p_{T}^{\mu\mu}$ in the towards ($\Delta\phi< 60^{\circ}$) region. Error bars represent the statistical and systematic uncertainties added in quadrature.
Unfolded distributions of particle density in Z events, as a function of $p_{T}^{\mu\mu}$ in the transverse ($60^{\circ} <\Delta\phi< 120^{\circ}$) region. Error bars represent the statistical and systematic uncertainties added in quadrature.
Unfolded distributions of particle density in Z events, as a function of $p_{T}^{\mu\mu}$ in the away ($\Delta\phi> 120^{\circ}$) region. Error bars represent the statistical and systematic uncertainties added in quadrature.
Unfolded distributions of $\Sigma p_{T}$ density in Z events, as a function of $p_{T}^{\mu\mu}$ in the towards ($\Delta\phi< 60^{\circ}$) region. Error bars represent the statistical and systematic uncertainties added in quadrature.
Unfolded distributions of $\Sigma p_{T}$ density in Z events, as a function of $p_{T}^{\mu\mu}$ in the transverse ($60^{\circ} <\Delta\phi< 120^{\circ}$) region. Error bars represent the statistical and systematic uncertainties added in quadrature.
Unfolded distributions of $\Sigma p_{T}$ density in Z events, as a function of $p_{T}^{\mu\mu}$ in the away ($\Delta\phi> 120^{\circ}$) region. Error bars represent the statistical and systematic uncertainties added in quadrature.
Event-by-event fluctuations in the elliptic-flow coefficient $v_2$ are studied in PbPb collisions at $\sqrt{s_{_\text{NN}}} = 5.02$ TeV using the CMS detector at the CERN LHC. Elliptic-flow probability distributions ${p}(v_2)$ for charged particles with transverse momentum 0.3$< p_\mathrm{T} <$3.0 GeV and pseudorapidity $| \eta | <$ 1.0 are determined for different collision centrality classes. The moments of the ${p}(v_2)$ distributions are used to calculate the $v_{2}$ coefficients based on cumulant orders 2, 4, 6, and 8. A rank ordering of the higher-order cumulant results and nonzero standardized skewness values obtained for the ${p}(v_2)$ distributions indicate non-Gaussian initial-state fluctuation behavior. Bessel-Gaussian and elliptic power fits to the flow distributions are studied to characterize the initial-state spatial anisotropy.
Unfolded elliptic flow probability density (p(v_2)) for 15-20\% collision centralities
Unfolded elliptic flow probability density (p(v_2)) for 30-35\% collision centralities
Unfolded elliptic flow probability density (p(v_2)) for 55-60\% collision centralities
The dependence of the second-order elliptic flow cumulant coefficient (v_2{2}) on centrality
The dependence of the fourth-order elliptic flow cumulant coefficient (v_2{4}) on centrality
The dependence of the sixth-order elliptic flow cumulant coefficient (v_2{6}) on centrality
The dependence of the eigth-order elliptic flow cumulant coefficient (v_2{8}) on centrality
The dependence of the ratio of the sixth-order to the fourth-order elliptic flow cumulant coefficients (v_2{6} / v_2{4}) on centrality
The dependence of the ratio of the eigth-order to the fourth-order elliptic flow cumulant coefficients (v_2{8} / v_2{4}) on centrality
The dependence of the ratio of the eigth-order to the sixth-order elliptic flow cumulant coefficients (v_2{8} / v_2{6}) on centrality
The dependence of the standardized skewness estimate (\gamma_1^exp) on centrality
The dependence of the k_2 parameter obtained from elliptic power law fits to unfolded elliptic flow probability densities on centrality
The dependence of the \epsilon_0 parameter obtained from elliptic power law fits to unfolded elliptic flow probability densities on centrality
The dependence of the \alpha parameter obtained from elliptic power law fits to unfolded elliptic flow probability densities on centrality
Jet substructure observables have significantly extended the search program for physics beyond the Standard Model at the Large Hadron Collider. The state-of-the-art tools have been motivated by theoretical calculations, but there has never been a direct comparison between data and calculations of jet substructure observables that are accurate beyond leading-logarithm approximation. Such observables are significant not only for probing the collinear regime of QCD that is largely unexplored at a hadron collider, but also for improving the understanding of jet substructure properties that are used in many studies at the Large Hadron Collider. This Letter documents a measurement of the first jet substructure quantity at a hadron collider to be calculated at next-to-next-to-leading-logarithm accuracy. The normalized, differential cross-section is measured as a function of log$_{10}\rho^2$, where $\rho$ is the ratio of the soft-drop mass to the ungroomed jet transverse momentum. This quantity is measured in dijet events from 32.9 fb$^{-1}$ of $\sqrt{s} = 13$ TeV proton-proton collisions recorded by the ATLAS detector. The data are unfolded to correct for detector effects and compared to precise QCD calculations and leading-logarithm particle-level Monte Carlo simulations.
Data from Fig 3a. The unfolded $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$(lead) > 600 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data; the uncertainties from the calculations are shown on each one. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 3a. The unfolded $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$(lead) > 600 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data; the uncertainties from the calculations are shown on each one. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 3b. The unfolded $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$(lead) > 600 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data; the uncertainties from the calculations are shown on each one. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 3b. The unfolded $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$(lead) > 600 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data; the uncertainties from the calculations are shown on each one. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 3c. The unfolded $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$(lead) > 600 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data; the uncertainties from the calculations are shown on each one. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. The uncertainties are applied symmetrically, though the cross section cannot go below zero in the first bin.
Data from Fig 3c. The unfolded $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$(lead) > 600 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data; the uncertainties from the calculations are shown on each one. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. The uncertainties are applied symmetrically, though the cross section cannot go below zero in the first bin.
Data from Fig 4 and Fig 8a-16a. The unfolded $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$(lead) > 600 GeV, after the soft drop algorithm is applied for beta = 0, in data. All uncertainties described in the text are shown on the data; the uncertainties from the calculations are shown on each one. The distributions are normalized to the integrated cross section, sigma(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {600, 650, 700, 750, 800, 850, 900, 950, 1000, ∞ } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 4 and FigAux 8a-16a. The unfolded $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$(lead) > 600 GeV, after the soft drop algorithm is applied for beta = 0, in data. All uncertainties described in the text are shown on the data; the uncertainties from the calculations are shown on each one. The distributions are normalized to the integrated cross section, sigma(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {600, 650, 700, 750, 800, 850, 900, 950, 1000, ∞ } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 4 and Fig 8b-16b. The unfolded $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$(lead) > 600 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data; the uncertainties from the calculations are shown on each one. The distributions are normalized to the integrated cross section, sigma(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {600, 650, 700, 750, 800, 850, 900, 950, 1000, ∞ } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 4 and FigAux 8b-16b. The unfolded $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$(lead) > 600 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data; the uncertainties from the calculations are shown on each one. The distributions are normalized to the integrated cross section, sigma(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {600, 650, 700, 750, 800, 850, 900, 950, 1000, ∞ } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 8c-16c. The unfolded $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$(lead) > 600 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data; the uncertainties from the calculations are shown on each one. The distributions are normalized to the integrated cross section, sigma(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {600, 650, 700, 750, 800, 850, 900, 950, 1000, ∞ } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 8c-16c. The unfolded $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$(lead) > 600 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data; the uncertainties from the calculations are shown on each one. The distributions are normalized to the integrated cross section, sigma(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {600, 650, 700, 750, 800, 850, 900, 950, 1000, ∞ } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 6a. The summed covariance matrices of the systematic and statistical uncertainties for the combined $p_T$ and $log_{10}(\rho^2)$ bins for $\beta$ = 0. Each group of 10 bins corresponds to a bin of $p_T$ in {600, 650, 700, 750, 800, 850, 900, 950, 1000, ∞ }; each bin within the $p_T$ bin corresponds to 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 6a. The summed covariance matrices of the systematic and statistical uncertainties for the combined $p_T$ and $log_{10}(\rho^2)$ bins for $\beta$ = 0. Each group of 10 bins corresponds to a bin of $p_T$ in {600, 650, 700, 750, 800, 850, 900, 950, 1000, ∞ }; each bin within the $p_T$ bin corresponds to 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 6b. The summed covariance matrices of the systematic and statistical uncertainties for the combined $p_T$ and $log_{10}(\rho^2)$ bins for $\beta$ = 1. Each group of 10 bins corresponds to a bin of $p_T$ in {600, 650, 700, 750, 800, 850, 900, 950, 1000, ∞ }; each bin within the $p_T$ bin corresponds to 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 6b. The summed covariance matrices of the systematic and statistical uncertainties for the combined $p_T$ and $log_{10}(\rho^2)$ bins for $\beta$ = 1. Each group of 10 bins corresponds to a bin of $p_T$ in {600, 650, 700, 750, 800, 850, 900, 950, 1000, ∞ }; each bin within the $p_T$ bin corresponds to 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 6c. The summed covariance matrices of the systematic and statistical uncertainties for the combined $p_T$ and $log_{10}(\rho^2)$ bins for $\beta$ = 2. Each group of 10 bins corresponds to a bin of $p_T$ in {600, 650, 700, 750, 800, 850, 900, 950, 1000, ∞ }; each bin within the $p_T$ bin corresponds to 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 6c. The summed covariance matrices of the systematic and statistical uncertainties for the combined $p_T$ and $log_{10}(\rho^2)$ bins for $\beta$ = 2. Each group of 10 bins corresponds to a bin of $p_T$ in {600, 650, 700, 750, 800, 850, 900, 950, 1000, ∞ }; each bin within the $p_T$ bin corresponds to 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 7a. The summed covariance matrices of the systematic and statistical uncertainties for the $log_{10}(\rho^2)$ bins for $\beta$ = 0, inclusive in $p_T$.
Data from FigAux 7a. The summed covariance matrices of the systematic and statistical uncertainties for the $log_{10}(\rho^2)$ bins for $\beta$ = 0, inclusive in $p_T$.
Data from Fig 7b. The summed covariance matrices of the systematic and statistical uncertainties for the $log_{10}(\rho^2)$ bins for $\beta$ = 1, inclusive in $p_T$.
Data from FigAux 7b. The summed covariance matrices of the systematic and statistical uncertainties for the $log_{10}(\rho^2)$ bins for $\beta$ = 1, inclusive in $p_T$.
Data from Fig 7c. The summed covariance matrices of the systematic and statistical uncertainties for the $log_{10}(\rho^2)$ bins for $\beta$ = 2, inclusive in $p_T$.
Data from FigAux 7c. The summed covariance matrices of the systematic and statistical uncertainties for the $log_{10}(\rho^2)$ bins for $\beta$ = 2, inclusive in $p_T$.
Measurements of azimuthal angle and transverse momentum ($p_\mathrm{T}$) correlations of isolated photons and associated jets are reported for pp and PbPb collisions at $\sqrt{s_{_{\mathrm{NN}}}} =$ 5.02 TeV. The data were recorded with the CMS detector at the CERN LHC. For events containing a leading isolated photon with $p_\mathrm{T}^\gamma >$ 40 GeV$/c$ and an associated jet with $p_\mathrm{T}^\text{jet} >$ 30 GeV$/c$, the photon+jet azimuthal correlation and $p_\mathrm{T}$ imbalance in PbPb collisions are studied as functions of collision centrality and $p_\mathrm{T}^\gamma$. The results are compared to pp reference data collected at the same collision energy and to predictions from several theoretical models for parton energy loss. No evidence of broadening of the photon+jet azimuthal correlations is observed, while the ratio $p_\mathrm{T}^\text{jet}/p_\mathrm{T}^\gamma$ decreases significantly for PbPb data relative to the pp reference. All models considered agree within uncertainties with the data. The number of associated jets per photon with $p_\mathrm{T}^\gamma >$ 80 GeV$/c$ is observed to be shifted towards lower $p_\mathrm{T}^\text{jet}$ values in central PbPb collisions compared to pp collisions.
Jet resolution parameters for pp and PbPb collisions in various centrality bins.
The azimuthal correlation of photons and jets in five $p_{\mathrm{T}}^{\gamma}$ intervals for 0-30% and 30-100% centrality PbPb collisions. The smeared pp data are included for comparison.
Distribution of $x_{\mathrm{j}\gamma} = p_{\mathrm{T}}^{\mathrm{jet}} / p_{\mathrm{T}}^{\gamma}$ in five $p_{\mathrm{T}}^{\gamma}$ intervals for 0-30% and 30-100% centrality PbPb collisions. The smeared pp data are included for comparison. Empty bins are denoted as 'empty' in the table.
The $\langle x_{\mathrm{j}\gamma} \rangle$ and $R_{\mathrm{j}\gamma}$, the number of associated jets per photon, in 0-30% and 30-100% centrality PbPb collisions. The smeared pp data are added for comparison. A value of 999 in the bin range indicates that there is no upper limit.
The $I_{\mathrm{AA}}^{\mathrm{jet}}$ vs. $p_{\mathrm{T}}^{\mathrm{jet}}$ for 0-30% and 30-100% centrality PbPb collisions. Bins for which there are no data points are denoted as 'empty'.
The centrality dependence of $x_{\mathrm{j}\gamma}$ of photon+jet pairs normalized by the number of photons for PbPb and smeared pp data. Empty bins are denoted as 'empty' in the table.
The $\langle x_{\mathrm{j}\gamma} \rangle$ and $R_{\mathrm{j}\gamma}$ as a function of $\langle N_{\mathrm{part}} \rangle$ for $p_{\mathrm{T}}^{\gamma} > 60$ and 80 GeV. The PbPb results are compared to pp results smeared by the relative jet energy resolution corresponding to each centrality interval.
The results of a search for the direct pair production of top squarks, the supersymmetric partner of the top quark, in final states with one isolated electron or muon, several energetic jets, and missing transverse momentum are reported. The analysis also targets spin-0 mediator models, where the mediator decays into a pair of dark-matter particles and is produced in association with a pair of top quarks. The search uses data from proton-proton collisions delivered by the Large Hadron Collider in 2015 and 2016 at a centre-of-mass energy of $\sqrt{s}=13$ TeV and recorded by the ATLAS detector, corresponding to an integrated luminosity of 36 fb$^{-1}$. A wide range of signal scenarios with different mass-splittings between the top squark, the lightest neutralino and possible intermediate supersymmetric particles are considered, including cases where the W bosons or the top quarks produced in the decay chain are off-shell. No significant excess over the Standard Model prediction is observed. The null results are used to set exclusion limits at 95% confidence level in several supersymmetry benchmark models. For pair-produced top-squarks decaying into top quarks, top-squark masses up to 940 GeV are excluded. Stringent exclusion limits are also derived for all other considered top-squark decay scenarios. For the spin-0 mediator models, upper limits are set on the visible cross-section.
$\textbf{Distribution 1 } -$ Kinematic distribution of $m_{\rm top}^{\rm reclustered}$ in tN_high. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 1 } -$ Kinematic distribution of $m_{\rm top}^{\rm reclustered}$ in tN_high. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 1 } -$ Kinematic distribution of $m_{\rm top}^{\rm reclustered}$ in tN_high. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 1 } -$ Kinematic distribution of $m_{\rm top}^{\rm reclustered}$ in tN_high. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 2 } -$ Kinematic distribution of amT2 in bC2x_med. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 2 } -$ Kinematic distribution of amT2 in bC2x_med. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 2 } -$ Kinematic distribution of amT2 in bC2x_med. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 2 } -$ Kinematic distribution of amT2 in bC2x_med. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 3 } -$ Kinematic distribution of mT in bC2x_diag. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 3 } -$ Kinematic distribution of mT in bC2x_diag. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 3 } -$ Kinematic distribution of mT in bC2x_diag. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 3 } -$ Kinematic distribution of mT in bC2x_diag. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 4 } -$ Kinematic distribution of ETmiss in bCbv. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 4 } -$ Kinematic distribution of ETmiss in bCbv. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 4 } -$ Kinematic distribution of ETmiss in bCbv. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 4 } -$ Kinematic distribution of ETmiss in bCbv. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 5 } -$ Kinematic distribution of mT in DM_low. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 5 } -$ Kinematic distribution of mT in DM_low. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 5 } -$ Kinematic distribution of mT in DM_low. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 5 } -$ Kinematic distribution of mT in DM_low. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 6 } -$ Kinematic distribution of ETmiss in DM_high. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 6 } -$ Kinematic distribution of ETmiss in DM_high. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 6 } -$ Kinematic distribution of ETmiss in DM_high. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 6 } -$ Kinematic distribution of ETmiss in DM_high. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 7 } -$ Distributions of BDT score for the tN_diag_low region. The SM background predictions are obtained using the background-only fit configuration.
$\textbf{Distribution 7 } -$ Distributions of BDT score for the tN_diag_low region. The SM background predictions are obtained using the background-only fit configuration.
$\textbf{Distribution 7 } -$ Distributions of BDT score for the tN_diag_low region. The SM background predictions are obtained using the background-only fit configuration.
$\textbf{Distribution 7 } -$ Distributions of BDT score for the tN_diag_low region. The SM background predictions are obtained using the background-only fit configuration.
$\textbf{Distribution 8 } -$ Distributions of BDT score for the tN_diag_med region. The SM background predictions are obtained using the background-only fit configuration.
$\textbf{Distribution 8 } -$ Distributions of BDT score for the tN_diag_med region. The SM background predictions are obtained using the background-only fit configuration.
$\textbf{Distribution 8 } -$ Distributions of BDT score for the tN_diag_med region. The SM background predictions are obtained using the background-only fit configuration.
$\textbf{Distribution 8 } -$ Distributions of BDT score for the tN_diag_med region. The SM background predictions are obtained using the background-only fit configuration.
$\textbf{Distribution 9 } -$ Distributions of BDT score for the tN_diag_high region. The SM background predictions are obtained using the background-only fit configuration.
$\textbf{Distribution 9 } -$ Distributions of BDT score for the tN_diag_high region. The SM background predictions are obtained using the background-only fit configuration.
$\textbf{Distribution 9 } -$ Distributions of BDT score for the tN_diag_high region. The SM background predictions are obtained using the background-only fit configuration.
$\textbf{Distribution 9 } -$ Distributions of BDT score for the tN_diag_high region. The SM background predictions are obtained using the background-only fit configuration.
$\textbf{Distribution 10 } -$ Kinematic distribution of ETmiss in tN_med. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 10 } -$ Kinematic distribution of ETmiss in tN_med. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 10 } -$ Kinematic distribution of ETmiss in tN_med. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 10 } -$ Kinematic distribution of ETmiss in tN_med. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 11 } -$ Kinematic distribution of amT2 in bWN. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 11 } -$ Kinematic distribution of amT2 in bWN. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 11 } -$ Kinematic distribution of amT2 in bWN. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 11 } -$ Kinematic distribution of amT2 in bWN. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 12 } -$ Kinematic distribution of pT(l)/ETmiss in bffN. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 12 } -$ Kinematic distribution of pT(l)/ETmiss in bffN. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 12 } -$ Kinematic distribution of pT(l)/ETmiss in bffN. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 12 } -$ Kinematic distribution of pT(l)/ETmiss in bffN. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 13 } -$ Kinematic distribution of pT(l)/ETmiss in bCsoft_diag. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 13 } -$ Kinematic distribution of pT(l)/ETmiss in bCsoft_diag. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 13 } -$ Kinematic distribution of pT(l)/ETmiss in bCsoft_diag. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 13 } -$ Kinematic distribution of pT(l)/ETmiss in bCsoft_diag. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 14 } -$ Kinematic distribution of pT(l)/ETmiss in bCsoft_med. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 14 } -$ Kinematic distribution of pT(l)/ETmiss in bCsoft_med. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 14 } -$ Kinematic distribution of pT(l)/ETmiss in bCsoft_med. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 14 } -$ Kinematic distribution of pT(l)/ETmiss in bCsoft_med. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 15 } -$ Kinematic distribution of pT(l)/ETmiss in bCsoft_high. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 15 } -$ Kinematic distribution of pT(l)/ETmiss in bCsoft_high. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 15 } -$ Kinematic distribution of pT(l)/ETmiss in bCsoft_high. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Distribution 15 } -$ Kinematic distribution of pT(l)/ETmiss in bCsoft_high. The full event selection in the corresponding signal region is applied, except for the requirement that is imposed on the variable being plotted. The predicted SM backgrounds are scaled with the normalisation factors obtained from the corresponding control regions. The last bin contains overflows.
$\textbf{Exclusion contour 1 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop pair production assuming either stop -> t N1, stop -> b W C1 or stop -> b f f' N1 decay with a branching ratio of 100%.
$\textbf{Exclusion contour 1 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop pair production assuming either stop -> t N1, stop -> b W C1 or stop -> b f f' N1 decay with a branching ratio of 100%.
$\textbf{Exclusion contour 1 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop pair production assuming either stop -> t N1, stop -> b W C1 or stop -> b f f' N1 decay with a branching ratio of 100%.
$\textbf{Exclusion contour 1 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop pair production assuming either stop -> t N1, stop -> b W C1 or stop -> b f f' N1 decay with a branching ratio of 100%.
$\textbf{Exclusion contour 1 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop pair production assuming either stop -> t N1, stop -> b W C1 or stop -> b f f' N1 decay with a branching ratio of 100%.
$\textbf{Exclusion contour 1 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop pair production assuming either stop -> t N1, stop -> b W C1 or stop -> b f f' N1 decay with a branching ratio of 100%.
$\textbf{Exclusion contour 1 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop pair production assuming either stop -> t N1, stop -> b W C1 or stop -> b f f' N1 decay with a branching ratio of 100%.
$\textbf{Exclusion contour 1 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop pair production assuming either stop -> t N1, stop -> b W C1 or stop -> b f f' N1 decay with a branching ratio of 100%.
$\textbf{Selected SR 1 } -$ Selected signal regions for the bino LSP model in the m(STOP) vs m(NEUTRALINO) plane.
$\textbf{Selected SR 1 } -$ Selected signal regions for the bino LSP model in the m(STOP) vs m(NEUTRALINO) plane.
$\textbf{Selected SR 1 } -$ Selected signal regions for the bino LSP model in the m(STOP) vs m(NEUTRALINO) plane.
$\textbf{Selected SR 1 } -$ Selected signal regions for the bino LSP model in the m(STOP) vs m(NEUTRALINO) plane.
$\textbf{Exclusion contour 2 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(STOP)-m(NEUTRALINO) for the direct stop pair production assuming either stop -> t N1, stop -> b W C1 or stop -> b f f' N1 decay with a branching ratio of 100%.
$\textbf{Exclusion contour 2 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(STOP)-m(NEUTRALINO) for the direct stop pair production assuming either stop -> t N1, stop -> b W C1 or stop -> b f f' N1 decay with a branching ratio of 100%.
$\textbf{Exclusion contour 2 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(STOP)-m(NEUTRALINO) for the direct stop pair production assuming either stop -> t N1, stop -> b W C1 or stop -> b f f' N1 decay with a branching ratio of 100%.
$\textbf{Exclusion contour 2 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(STOP)-m(NEUTRALINO) for the direct stop pair production assuming either stop -> t N1, stop -> b W C1 or stop -> b f f' N1 decay with a branching ratio of 100%.
$\textbf{Exclusion contour 2 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(STOP)-m(NEUTRALINO) for the direct stop pair production assuming either stop -> t N1, stop -> b W C1 or stop -> b f f' N1 decay with a branching ratio of 100%.
$\textbf{Exclusion contour 2 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(STOP)-m(NEUTRALINO) for the direct stop pair production assuming either stop -> t N1, stop -> b W C1 or stop -> b f f' N1 decay with a branching ratio of 100%.
$\textbf{Exclusion contour 2 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(STOP)-m(NEUTRALINO) for the direct stop pair production assuming either stop -> t N1, stop -> b W C1 or stop -> b f f' N1 decay with a branching ratio of 100%.
$\textbf{Exclusion contour 2 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(STOP)-m(NEUTRALINO) for the direct stop pair production assuming either stop -> t N1, stop -> b W C1 or stop -> b f f' N1 decay with a branching ratio of 100%.
$\textbf{Selected SR 2 } -$ Selected signal regions for the bino LSP model in the m(STOP) versus m(STOP)-m(NEUTRALINO) plane.
$\textbf{Selected SR 2 } -$ Selected signal regions for the bino LSP model in the m(STOP) versus m(STOP)-m(NEUTRALINO) plane.
$\textbf{Selected SR 2 } -$ Selected signal regions for the bino LSP model in the m(STOP) versus m(STOP)-m(NEUTRALINO) plane.
$\textbf{Selected SR 2 } -$ Selected signal regions for the bino LSP model in the m(STOP) versus m(STOP)-m(NEUTRALINO) plane.
$\textbf{Exclusion contour 3 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop/sbottom pair production in the wino NLSP model under the hypothesis of mq3L < mtR and mu < 0, where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, sbottom -> t C1, sbottom -> b N1, and sbottom -> b N2) are considered with different branching ratios for each signal point. N2 decays to N1 predominantly via either Z boson or Higgs boson depending on the sign of the μ parameter.
$\textbf{Exclusion contour 3 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop/sbottom pair production in the wino NLSP model under the hypothesis of mq3L < mtR and mu < 0, where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, sbottom -> t C1, sbottom -> b N1, and sbottom -> b N2) are considered with different branching ratios for each signal point. N2 decays to N1 predominantly via either Z boson or Higgs boson depending on the sign of the μ parameter.
$\textbf{Exclusion contour 3 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop/sbottom pair production in the wino NLSP model under the hypothesis of mq3L < mtR and mu < 0, where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, sbottom -> t C1, sbottom -> b N1, and sbottom -> b N2) are considered with different branching ratios for each signal point. N2 decays to N1 predominantly via either Z boson or Higgs boson depending on the sign of the μ parameter.
$\textbf{Exclusion contour 3 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop/sbottom pair production in the wino NLSP model under the hypothesis of mq3L < mtR and mu < 0, where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, sbottom -> t C1, sbottom -> b N1, and sbottom -> b N2) are considered with different branching ratios for each signal point. N2 decays to N1 predominantly via either Z boson or Higgs boson depending on the sign of the μ parameter.
$\textbf{Exclusion contour 3 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop/sbottom pair production in the wino NLSP model under the hypothesis of mq3L < mtR and mu < 0, where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, sbottom -> t C1, sbottom -> b N1, and sbottom -> b N2) are considered with different branching ratios for each signal point. N2 decays to N1 predominantly via either Z boson or Higgs boson depending on the sign of the μ parameter.
$\textbf{Exclusion contour 3 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop/sbottom pair production in the wino NLSP model under the hypothesis of mq3L < mtR and mu < 0, where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, sbottom -> t C1, sbottom -> b N1, and sbottom -> b N2) are considered with different branching ratios for each signal point. N2 decays to N1 predominantly via either Z boson or Higgs boson depending on the sign of the μ parameter.
$\textbf{Exclusion contour 3 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop/sbottom pair production in the wino NLSP model under the hypothesis of mq3L < mtR and mu < 0, where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, sbottom -> t C1, sbottom -> b N1, and sbottom -> b N2) are considered with different branching ratios for each signal point. N2 decays to N1 predominantly via either Z boson or Higgs boson depending on the sign of the μ parameter.
$\textbf{Exclusion contour 3 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop/sbottom pair production in the wino NLSP model under the hypothesis of mq3L < mtR and mu < 0, where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, sbottom -> t C1, sbottom -> b N1, and sbottom -> b N2) are considered with different branching ratios for each signal point. N2 decays to N1 predominantly via either Z boson or Higgs boson depending on the sign of the μ parameter.
$\textbf{Selected SR 3 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop/sbottom pair production in the wino NLSP model under the hypothesis of mq3L < mtR and mu < 0, where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, sbottom -> t C1, sbottom -> b N1, and sbottom -> b N2) are considered with different branching ratios for each signal point. N2 decays to N1 predominantly via either Z boson or Higgs boson depending on the sign of the μ parameter.
$\textbf{Selected SR 3 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop/sbottom pair production in the wino NLSP model under the hypothesis of mq3L < mtR and mu < 0, where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, sbottom -> t C1, sbottom -> b N1, and sbottom -> b N2) are considered with different branching ratios for each signal point. N2 decays to N1 predominantly via either Z boson or Higgs boson depending on the sign of the μ parameter.
$\textbf{Selected SR 3 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop/sbottom pair production in the wino NLSP model under the hypothesis of mq3L < mtR and mu < 0, where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, sbottom -> t C1, sbottom -> b N1, and sbottom -> b N2) are considered with different branching ratios for each signal point. N2 decays to N1 predominantly via either Z boson or Higgs boson depending on the sign of the μ parameter.
$\textbf{Selected SR 3 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop/sbottom pair production in the wino NLSP model under the hypothesis of mq3L < mtR and mu < 0, where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, sbottom -> t C1, sbottom -> b N1, and sbottom -> b N2) are considered with different branching ratios for each signal point. N2 decays to N1 predominantly via either Z boson or Higgs boson depending on the sign of the μ parameter.
$\textbf{Exclusion contour 4 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop/sbottom pair production in the wino NLSP model under the hypothesis of mq3L < mtR and mu > 0, where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, sbottom -> t C1, sbottom -> b N1, and sbottom -> b N2) are considered with different branching ratios for each signal point. N2 decays to N1 predominantly via either Z boson or Higgs boson depending on the sign of the μ parameter.
$\textbf{Exclusion contour 4 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop/sbottom pair production in the wino NLSP model under the hypothesis of mq3L < mtR and mu > 0, where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, sbottom -> t C1, sbottom -> b N1, and sbottom -> b N2) are considered with different branching ratios for each signal point. N2 decays to N1 predominantly via either Z boson or Higgs boson depending on the sign of the μ parameter.
$\textbf{Exclusion contour 4 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop/sbottom pair production in the wino NLSP model under the hypothesis of mq3L < mtR and mu > 0, where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, sbottom -> t C1, sbottom -> b N1, and sbottom -> b N2) are considered with different branching ratios for each signal point. N2 decays to N1 predominantly via either Z boson or Higgs boson depending on the sign of the μ parameter.
$\textbf{Exclusion contour 4 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop/sbottom pair production in the wino NLSP model under the hypothesis of mq3L < mtR and mu > 0, where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, sbottom -> t C1, sbottom -> b N1, and sbottom -> b N2) are considered with different branching ratios for each signal point. N2 decays to N1 predominantly via either Z boson or Higgs boson depending on the sign of the μ parameter.
$\textbf{Exclusion contour 4 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop/sbottom pair production in the wino NLSP model under the hypothesis of mq3L < mtR and mu > 0, where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, sbottom -> t C1, sbottom -> b N1, and sbottom -> b N2) are considered with different branching ratios for each signal point. N2 decays to N1 predominantly via either Z boson or Higgs boson depending on the sign of the μ parameter.
$\textbf{Exclusion contour 4 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop/sbottom pair production in the wino NLSP model under the hypothesis of mq3L < mtR and mu > 0, where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, sbottom -> t C1, sbottom -> b N1, and sbottom -> b N2) are considered with different branching ratios for each signal point. N2 decays to N1 predominantly via either Z boson or Higgs boson depending on the sign of the μ parameter.
$\textbf{Exclusion contour 4 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop/sbottom pair production in the wino NLSP model under the hypothesis of mq3L < mtR and mu > 0, where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, sbottom -> t C1, sbottom -> b N1, and sbottom -> b N2) are considered with different branching ratios for each signal point. N2 decays to N1 predominantly via either Z boson or Higgs boson depending on the sign of the μ parameter.
$\textbf{Exclusion contour 4 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop/sbottom pair production in the wino NLSP model under the hypothesis of mq3L < mtR and mu > 0, where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, sbottom -> t C1, sbottom -> b N1, and sbottom -> b N2) are considered with different branching ratios for each signal point. N2 decays to N1 predominantly via either Z boson or Higgs boson depending on the sign of the μ parameter.
$\textbf{Selected SR 4 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop/sbottom pair production in the wino NLSP model under the hypothesis of mq3L < mtR and mu > 0, where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, sbottom -> t C1, sbottom -> b N1, and sbottom -> b N2) are considered with different branching ratios for each signal point. N2 decays to N1 predominantly via either Z boson or Higgs boson depending on the sign of the μ parameter.
$\textbf{Selected SR 4 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop/sbottom pair production in the wino NLSP model under the hypothesis of mq3L < mtR and mu > 0, where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, sbottom -> t C1, sbottom -> b N1, and sbottom -> b N2) are considered with different branching ratios for each signal point. N2 decays to N1 predominantly via either Z boson or Higgs boson depending on the sign of the μ parameter.
$\textbf{Selected SR 4 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop/sbottom pair production in the wino NLSP model under the hypothesis of mq3L < mtR and mu > 0, where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, sbottom -> t C1, sbottom -> b N1, and sbottom -> b N2) are considered with different branching ratios for each signal point. N2 decays to N1 predominantly via either Z boson or Higgs boson depending on the sign of the μ parameter.
$\textbf{Selected SR 4 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for the direct stop/sbottom pair production in the wino NLSP model under the hypothesis of mq3L < mtR and mu > 0, where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, sbottom -> t C1, sbottom -> b N1, and sbottom -> b N2) are considered with different branching ratios for each signal point. N2 decays to N1 predominantly via either Z boson or Higgs boson depending on the sign of the μ parameter.
$\textbf{Exclusion contour 5 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production assuming b C1 decay with a branching ratio of 100%. The chargino mass is assumed to be close to the stop mass, m(C1) = m(STOP) - 10 GeV.
$\textbf{Exclusion contour 5 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production assuming b C1 decay with a branching ratio of 100%. The chargino mass is assumed to be close to the stop mass, m(C1) = m(STOP) - 10 GeV.
$\textbf{Exclusion contour 5 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production assuming b C1 decay with a branching ratio of 100%. The chargino mass is assumed to be close to the stop mass, m(C1) = m(STOP) - 10 GeV.
$\textbf{Exclusion contour 5 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production assuming b C1 decay with a branching ratio of 100%. The chargino mass is assumed to be close to the stop mass, m(C1) = m(STOP) - 10 GeV.
$\textbf{Exclusion contour 5 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production assuming b C1 decay with a branching ratio of 100%. The chargino mass is assumed to be close to the stop mass, m(C1) = m(STOP) - 10 GeV.
$\textbf{Exclusion contour 5 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production assuming b C1 decay with a branching ratio of 100%. The chargino mass is assumed to be close to the stop mass, m(C1) = m(STOP) - 10 GeV.
$\textbf{Exclusion contour 5 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production assuming b C1 decay with a branching ratio of 100%. The chargino mass is assumed to be close to the stop mass, m(C1) = m(STOP) - 10 GeV.
$\textbf{Exclusion contour 5 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production assuming b C1 decay with a branching ratio of 100%. The chargino mass is assumed to be close to the stop mass, m(C1) = m(STOP) - 10 GeV.
$\textbf{Exclusion contour 6 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly left-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 6 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly left-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 6 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly left-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 6 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly left-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 6 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly left-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 6 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly left-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 6 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly left-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 6 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly left-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Selected SR 6 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly left-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Selected SR 6 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly left-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Selected SR 6 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly left-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Selected SR 6 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly left-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 7 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly right-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 7 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly right-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 7 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly right-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 7 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly right-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 7 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly right-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 7 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly right-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 7 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly right-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 7 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly right-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Selected SR 7 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly right-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Selected SR 7 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly right-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Selected SR 7 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly right-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Selected SR 7 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly right-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 8 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for large $\tan\beta$. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 8 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for large $\tan\beta$. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 8 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for large $\tan\beta$. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 8 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for large $\tan\beta$. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 8 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for large $\tan\beta$. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 8 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for large $\tan\beta$. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 8 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for large $\tan\beta$. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 8 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for large $\tan\beta$. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Selected SR 8 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for large $\tan\beta$. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Selected SR 8 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for large $\tan\beta$. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Selected SR 8 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for large $\tan\beta$. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Selected SR 8 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for large $\tan\beta$. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 9 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2) are considered with different branching ratios depending on the hypothesis being considered. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 9 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2) are considered with different branching ratios depending on the hypothesis being considered. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 9 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2) are considered with different branching ratios depending on the hypothesis being considered. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 9 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2) are considered with different branching ratios depending on the hypothesis being considered. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 9 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2) are considered with different branching ratios depending on the hypothesis being considered. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 9 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2) are considered with different branching ratios depending on the hypothesis being considered. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 9 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2) are considered with different branching ratios depending on the hypothesis being considered. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 9 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2) are considered with different branching ratios depending on the hypothesis being considered. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 10 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly left-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 10 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly left-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 10 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly left-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 10 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly left-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 10 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly left-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 10 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly left-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 10 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly left-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 10 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly left-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Selected SR 10 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly left-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Selected SR 10 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly left-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Selected SR 10 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly left-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Selected SR 10 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly left-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 11 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly right-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 11 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly right-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 11 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly right-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 11 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly right-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 11 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly right-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 11 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly right-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 11 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly right-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 11 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly right-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Selected SR 11 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly right-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Selected SR 11 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly right-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Selected SR 11 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly right-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Selected SR 11 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for a mostly right-handed stop. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 12 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for large $\tan\beta$. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 12 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for large $\tan\beta$. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 12 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for large $\tan\beta$. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 12 (exp.) } -$ Expected 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for large $\tan\beta$. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 12 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for large $\tan\beta$. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 12 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for large $\tan\beta$. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 12 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for large $\tan\beta$. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 12 (obs.) } -$ Observed 95% excluded regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for large $\tan\beta$. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Selected SR 12 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for large $\tan\beta$. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Selected SR 12 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for large $\tan\beta$. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Selected SR 12 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for large $\tan\beta$. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Selected SR 12 } -$ Selected signal regions in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model for large $\tan\beta$. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{Exclusion contour 13 (exp.) } -$ Expected 95% excluded regions in the plane of mm(STOP) versus m(NEUTRALINO) or the direct stop/sbottom pair production in the well-tempered neutralino model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, b1 -> t C1, b1 -> b N1, and b1 -> b N2) are considered with different branching ratio for each signal point for the $m_{q_{3L}} < m_{t_{R}}$ hypothesis. Both stop/sbottom pair productions are considered.
$\textbf{Exclusion contour 13 (exp.) } -$ Expected 95% excluded regions in the plane of mm(STOP) versus m(NEUTRALINO) or the direct stop/sbottom pair production in the well-tempered neutralino model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, b1 -> t C1, b1 -> b N1, and b1 -> b N2) are considered with different branching ratio for each signal point for the $m_{q_{3L}} < m_{t_{R}}$ hypothesis. Both stop/sbottom pair productions are considered.
$\textbf{Exclusion contour 13 (exp.) } -$ Expected 95% excluded regions in the plane of mm(STOP) versus m(NEUTRALINO) or the direct stop/sbottom pair production in the well-tempered neutralino model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, b1 -> t C1, b1 -> b N1, and b1 -> b N2) are considered with different branching ratio for each signal point for the $m_{q_{3L}} < m_{t_{R}}$ hypothesis. Both stop/sbottom pair productions are considered.
$\textbf{Exclusion contour 13 (exp.) } -$ Expected 95% excluded regions in the plane of mm(STOP) versus m(NEUTRALINO) or the direct stop/sbottom pair production in the well-tempered neutralino model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, b1 -> t C1, b1 -> b N1, and b1 -> b N2) are considered with different branching ratio for each signal point for the $m_{q_{3L}} < m_{t_{R}}$ hypothesis. Both stop/sbottom pair productions are considered.
$\textbf{Exclusion contour 13 (obs.) } -$ Observed 95% excluded regions in the plane of mm(STOP) versus m(NEUTRALINO) or the direct stop/sbottom pair production in the well-tempered neutralino model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, b1 -> t C1, b1 -> b N1, and b1 -> b N2) are considered with different branching ratio for each signal point for the $m_{q_{3L}} < m_{t_{R}}$ hypothesis. Both stop/sbottom pair productions are considered.
$\textbf{Exclusion contour 13 (obs.) } -$ Observed 95% excluded regions in the plane of mm(STOP) versus m(NEUTRALINO) or the direct stop/sbottom pair production in the well-tempered neutralino model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, b1 -> t C1, b1 -> b N1, and b1 -> b N2) are considered with different branching ratio for each signal point for the $m_{q_{3L}} < m_{t_{R}}$ hypothesis. Both stop/sbottom pair productions are considered.
$\textbf{Exclusion contour 13 (obs.) } -$ Observed 95% excluded regions in the plane of mm(STOP) versus m(NEUTRALINO) or the direct stop/sbottom pair production in the well-tempered neutralino model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, b1 -> t C1, b1 -> b N1, and b1 -> b N2) are considered with different branching ratio for each signal point for the $m_{q_{3L}} < m_{t_{R}}$ hypothesis. Both stop/sbottom pair productions are considered.
$\textbf{Exclusion contour 13 (obs.) } -$ Observed 95% excluded regions in the plane of mm(STOP) versus m(NEUTRALINO) or the direct stop/sbottom pair production in the well-tempered neutralino model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, b1 -> t C1, b1 -> b N1, and b1 -> b N2) are considered with different branching ratio for each signal point for the $m_{q_{3L}} < m_{t_{R}}$ hypothesis. Both stop/sbottom pair productions are considered.
$\textbf{Selected SR 13 } -$ Selected signal regions in the plane of mm(STOP) versus m(NEUTRALINO) or the direct stop/sbottom pair production in the well-tempered neutralino model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, b1 -> t C1, b1 -> b N1, and b1 -> b N2) are considered with different branching ratio for each signal point for the $m_{q_{3L}} < m_{t_{R}}$ hypothesis. Both stop/sbottom pair productions are considered.
$\textbf{Selected SR 13 } -$ Selected signal regions in the plane of mm(STOP) versus m(NEUTRALINO) or the direct stop/sbottom pair production in the well-tempered neutralino model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, b1 -> t C1, b1 -> b N1, and b1 -> b N2) are considered with different branching ratio for each signal point for the $m_{q_{3L}} < m_{t_{R}}$ hypothesis. Both stop/sbottom pair productions are considered.
$\textbf{Selected SR 13 } -$ Selected signal regions in the plane of mm(STOP) versus m(NEUTRALINO) or the direct stop/sbottom pair production in the well-tempered neutralino model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, b1 -> t C1, b1 -> b N1, and b1 -> b N2) are considered with different branching ratio for each signal point for the $m_{q_{3L}} < m_{t_{R}}$ hypothesis. Both stop/sbottom pair productions are considered.
$\textbf{Selected SR 13 } -$ Selected signal regions in the plane of mm(STOP) versus m(NEUTRALINO) or the direct stop/sbottom pair production in the well-tempered neutralino model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, b1 -> t C1, b1 -> b N1, and b1 -> b N2) are considered with different branching ratio for each signal point for the $m_{q_{3L}} < m_{t_{R}}$ hypothesis. Both stop/sbottom pair productions are considered.
$\textbf{Exclusion contour 14 (exp.) } -$ Expected 95% excluded regions in the plane of mm(STOP) versus m(NEUTRALINO) or the direct stop/sbottom pair production in the well-tempered neutralino model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, b1 -> t C1, b1 -> b N1, and b1 -> b N2) are considered with different branching ratio for each signal point for the $m_{q_{3L}} > m_{t_{R}}$. Only stop pair production is considered.
$\textbf{Exclusion contour 14 (exp.) } -$ Expected 95% excluded regions in the plane of mm(STOP) versus m(NEUTRALINO) or the direct stop/sbottom pair production in the well-tempered neutralino model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, b1 -> t C1, b1 -> b N1, and b1 -> b N2) are considered with different branching ratio for each signal point for the $m_{q_{3L}} > m_{t_{R}}$. Only stop pair production is considered.
$\textbf{Exclusion contour 14 (exp.) } -$ Expected 95% excluded regions in the plane of mm(STOP) versus m(NEUTRALINO) or the direct stop/sbottom pair production in the well-tempered neutralino model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, b1 -> t C1, b1 -> b N1, and b1 -> b N2) are considered with different branching ratio for each signal point for the $m_{q_{3L}} > m_{t_{R}}$. Only stop pair production is considered.
$\textbf{Exclusion contour 14 (exp.) } -$ Expected 95% excluded regions in the plane of mm(STOP) versus m(NEUTRALINO) or the direct stop/sbottom pair production in the well-tempered neutralino model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, b1 -> t C1, b1 -> b N1, and b1 -> b N2) are considered with different branching ratio for each signal point for the $m_{q_{3L}} > m_{t_{R}}$. Only stop pair production is considered.
$\textbf{Exclusion contour 14 (obs.) } -$ Observed 95% excluded regions in the plane of mm(STOP) versus m(NEUTRALINO) or the direct stop/sbottom pair production in the well-tempered neutralino model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, b1 -> t C1, b1 -> b N1, and b1 -> b N2) are considered with different branching ratio for each signal point for the $m_{q_{3L}} > m_{t_{R}}$. Only stop pair production is considered.<br><b>Note:</b> As no observed exclusion is found for this model, the contour is empty.
$\textbf{Exclusion contour 14 (obs.) } -$ Observed 95% excluded regions in the plane of mm(STOP) versus m(NEUTRALINO) or the direct stop/sbottom pair production in the well-tempered neutralino model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, b1 -> t C1, b1 -> b N1, and b1 -> b N2) are considered with different branching ratio for each signal point for the $m_{q_{3L}} > m_{t_{R}}$. Only stop pair production is considered.<br><b>Note:</b> As no observed exclusion is found for this model, the contour is empty.
$\textbf{Exclusion contour 14 (obs.) } -$ Observed 95% excluded regions in the plane of mm(STOP) versus m(NEUTRALINO) or the direct stop/sbottom pair production in the well-tempered neutralino model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, b1 -> t C1, b1 -> b N1, and b1 -> b N2) are considered with different branching ratio for each signal point for the $m_{q_{3L}} > m_{t_{R}}$. Only stop pair production is considered.<br><b>Note:</b> As no observed exclusion is found for this model, the contour is empty.
$\textbf{Exclusion contour 14 (obs.) } -$ Observed 95% excluded regions in the plane of mm(STOP) versus m(NEUTRALINO) or the direct stop/sbottom pair production in the well-tempered neutralino model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, b1 -> t C1, b1 -> b N1, and b1 -> b N2) are considered with different branching ratio for each signal point for the $m_{q_{3L}} > m_{t_{R}}$. Only stop pair production is considered.<br><b>Note:</b> As no observed exclusion is found for this model, the contour is empty.
$\textbf{Selected SR 14 } -$ Selected signal regions in the plane of mm(STOP) versus m(NEUTRALINO) or the direct stop/sbottom pair production in the well-tempered neutralino model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, b1 -> t C1, b1 -> b N1, and b1 -> b N2) are considered with different branching ratio for each signal point for the $m_{q_{3L}} > m_{t_{R}}$. Only stop pair production is considered.
$\textbf{Selected SR 14 } -$ Selected signal regions in the plane of mm(STOP) versus m(NEUTRALINO) or the direct stop/sbottom pair production in the well-tempered neutralino model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, b1 -> t C1, b1 -> b N1, and b1 -> b N2) are considered with different branching ratio for each signal point for the $m_{q_{3L}} > m_{t_{R}}$. Only stop pair production is considered.
$\textbf{Selected SR 14 } -$ Selected signal regions in the plane of mm(STOP) versus m(NEUTRALINO) or the direct stop/sbottom pair production in the well-tempered neutralino model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, b1 -> t C1, b1 -> b N1, and b1 -> b N2) are considered with different branching ratio for each signal point for the $m_{q_{3L}} > m_{t_{R}}$. Only stop pair production is considered.
$\textbf{Selected SR 14 } -$ Selected signal regions in the plane of mm(STOP) versus m(NEUTRALINO) or the direct stop/sbottom pair production in the well-tempered neutralino model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2, b1 -> t C1, b1 -> b N1, and b1 -> b N2) are considered with different branching ratio for each signal point for the $m_{q_{3L}} > m_{t_{R}}$. Only stop pair production is considered.
$\textbf{DM Upper Limit 1 } -$ Upper limit on the ratio of the DM production cross-section to the simplified model expectation under the hypothesis of a scalar mediator. The limit is shown as a function of the mediator mass for a fixed mass of the DM candidate of 1 GeV. The coupling of the mediator to SM and DM particles is assumed to be g=1.
$\textbf{DM Upper Limit 1 } -$ Upper limit on the ratio of the DM production cross-section to the simplified model expectation under the hypothesis of a scalar mediator. The limit is shown as a function of the mediator mass for a fixed mass of the DM candidate of 1 GeV. The coupling of the mediator to SM and DM particles is assumed to be g=1.
$\textbf{DM Upper Limit 1 } -$ Upper limit on the ratio of the DM production cross-section to the simplified model expectation under the hypothesis of a scalar mediator. The limit is shown as a function of the mediator mass for a fixed mass of the DM candidate of 1 GeV. The coupling of the mediator to SM and DM particles is assumed to be g=1.
$\textbf{DM Upper Limit 1 } -$ Upper limit on the ratio of the DM production cross-section to the simplified model expectation under the hypothesis of a scalar mediator. The limit is shown as a function of the mediator mass for a fixed mass of the DM candidate of 1 GeV. The coupling of the mediator to SM and DM particles is assumed to be g=1.
$\textbf{DM Upper Limit 2 } -$ Upper limit on the ratio of the DM production cross-section to the simplified model expectation under the hypothesis of a pseudoscalar mediator. The limit is shown as a function of the mediator mass for a fixed mass of the DM candidate of 1 GeV. The coupling of the mediator to SM and DM particles is assumed to be g=1.
$\textbf{DM Upper Limit 2 } -$ Upper limit on the ratio of the DM production cross-section to the simplified model expectation under the hypothesis of a pseudoscalar mediator. The limit is shown as a function of the mediator mass for a fixed mass of the DM candidate of 1 GeV. The coupling of the mediator to SM and DM particles is assumed to be g=1.
$\textbf{DM Upper Limit 2 } -$ Upper limit on the ratio of the DM production cross-section to the simplified model expectation under the hypothesis of a pseudoscalar mediator. The limit is shown as a function of the mediator mass for a fixed mass of the DM candidate of 1 GeV. The coupling of the mediator to SM and DM particles is assumed to be g=1.
$\textbf{DM Upper Limit 2 } -$ Upper limit on the ratio of the DM production cross-section to the simplified model expectation under the hypothesis of a pseudoscalar mediator. The limit is shown as a function of the mediator mass for a fixed mass of the DM candidate of 1 GeV. The coupling of the mediator to SM and DM particles is assumed to be g=1.
$\textbf{DM Upper Limit 3 } -$ Upper limit on the ratio of the DM production cross-section to the simplified model expectation under the hypothesis of a scalar mediator. The limit is shown as a function of the DM candidate mass for a fixed mediator mass of 10 GeV. The coupling of the mediator to SM and DM particles is assumed to be g=1.
$\textbf{DM Upper Limit 3 } -$ Upper limit on the ratio of the DM production cross-section to the simplified model expectation under the hypothesis of a scalar mediator. The limit is shown as a function of the DM candidate mass for a fixed mediator mass of 10 GeV. The coupling of the mediator to SM and DM particles is assumed to be g=1.
$\textbf{DM Upper Limit 3 } -$ Upper limit on the ratio of the DM production cross-section to the simplified model expectation under the hypothesis of a scalar mediator. The limit is shown as a function of the DM candidate mass for a fixed mediator mass of 10 GeV. The coupling of the mediator to SM and DM particles is assumed to be g=1.
$\textbf{DM Upper Limit 3 } -$ Upper limit on the ratio of the DM production cross-section to the simplified model expectation under the hypothesis of a scalar mediator. The limit is shown as a function of the DM candidate mass for a fixed mediator mass of 10 GeV. The coupling of the mediator to SM and DM particles is assumed to be g=1.
$\textbf{DM Upper Limit 4 } -$ Upper limit on the ratio of the DM production cross-section to the simplified model expectation under the hypothesis a pseudoscalar mediator. The limit is shown as a function of the DM candidate mass for a fixed mediator mass of 10 GeV. The coupling of the mediator to SM and DM particles is assumed to be g=1.
$\textbf{DM Upper Limit 4 } -$ Upper limit on the ratio of the DM production cross-section to the simplified model expectation under the hypothesis a pseudoscalar mediator. The limit is shown as a function of the DM candidate mass for a fixed mediator mass of 10 GeV. The coupling of the mediator to SM and DM particles is assumed to be g=1.
$\textbf{DM Upper Limit 4 } -$ Upper limit on the ratio of the DM production cross-section to the simplified model expectation under the hypothesis a pseudoscalar mediator. The limit is shown as a function of the DM candidate mass for a fixed mediator mass of 10 GeV. The coupling of the mediator to SM and DM particles is assumed to be g=1.
$\textbf{DM Upper Limit 4 } -$ Upper limit on the ratio of the DM production cross-section to the simplified model expectation under the hypothesis a pseudoscalar mediator. The limit is shown as a function of the DM candidate mass for a fixed mediator mass of 10 GeV. The coupling of the mediator to SM and DM particles is assumed to be g=1.
$\textbf{X-section U.L. 1 } -$ Observed upper limit on the signal cross section for the bino LSP model in the m(STOP) vs m(NEUTRALINO) plane.
$\textbf{X-section U.L. 1 } -$ Observed upper limit on the signal cross section for the bino LSP model in the m(STOP) vs m(NEUTRALINO) plane.
$\textbf{X-section U.L. 1 } -$ Observed upper limit on the signal cross section for the bino LSP model in the m(STOP) vs m(NEUTRALINO) plane.
$\textbf{X-section U.L. 1 } -$ Observed upper limit on the signal cross section for the bino LSP model in the m(STOP) vs m(NEUTRALINO) plane.
$\textbf{X-section U.L. 2 } -$ Observed upper limit on the signal cross section for the bino LSP model in the m(STOP) vs m(STOP)-m(NEUTRALINO) plane.
$\textbf{X-section U.L. 2 } -$ Observed upper limit on the signal cross section for the bino LSP model in the m(STOP) vs m(STOP)-m(NEUTRALINO) plane.
$\textbf{X-section U.L. 2 } -$ Observed upper limit on the signal cross section for the bino LSP model in the m(STOP) vs m(STOP)-m(NEUTRALINO) plane.
$\textbf{X-section U.L. 2 } -$ Observed upper limit on the signal cross section for the bino LSP model in the m(STOP) vs m(STOP)-m(NEUTRALINO) plane.
$\textbf{X-section U.L. 3 } -$ Observed upper limit on the signal cross section for the wino NLSP model with mu < 0
$\textbf{X-section U.L. 3 } -$ Observed upper limit on the signal cross section for the wino NLSP model with mu < 0
$\textbf{X-section U.L. 3 } -$ Observed upper limit on the signal cross section for the wino NLSP model with mu < 0
$\textbf{X-section U.L. 3 } -$ Observed upper limit on the signal cross section for the wino NLSP model with mu < 0
$\textbf{X-section U.L. 4 } -$ Observed upper limit on the signal cross section for the wino NLSP model with mu > 0
$\textbf{X-section U.L. 4 } -$ Observed upper limit on the signal cross section for the wino NLSP model with mu > 0
$\textbf{X-section U.L. 4 } -$ Observed upper limit on the signal cross section for the wino NLSP model with mu > 0
$\textbf{X-section U.L. 4 } -$ Observed upper limit on the signal cross section for the wino NLSP model with mu > 0
$\textbf{X-section U.L. 5 } -$ Observed upper limit on the signal cross section for the higgsino LSP model with left-handed stop squarks.
$\textbf{X-section U.L. 5 } -$ Observed upper limit on the signal cross section for the higgsino LSP model with left-handed stop squarks.
$\textbf{X-section U.L. 5 } -$ Observed upper limit on the signal cross section for the higgsino LSP model with left-handed stop squarks.
$\textbf{X-section U.L. 5 } -$ Observed upper limit on the signal cross section for the higgsino LSP model with left-handed stop squarks.
$\textbf{X-section U.L. 6 } -$ Observed upper limit on the signal cross section for the higgsino LSP model with right-handed stop squarks.
$\textbf{X-section U.L. 6 } -$ Observed upper limit on the signal cross section for the higgsino LSP model with right-handed stop squarks.
$\textbf{X-section U.L. 6 } -$ Observed upper limit on the signal cross section for the higgsino LSP model with right-handed stop squarks.
$\textbf{X-section U.L. 6 } -$ Observed upper limit on the signal cross section for the higgsino LSP model with right-handed stop squarks.
$\textbf{X-section U.L. 7 } -$ Observed upper limit on the signal cross section for the higgsino LSP model with large tan beta.
$\textbf{X-section U.L. 7 } -$ Observed upper limit on the signal cross section for the higgsino LSP model with large tan beta.
$\textbf{X-section U.L. 7 } -$ Observed upper limit on the signal cross section for the higgsino LSP model with large tan beta.
$\textbf{X-section U.L. 7 } -$ Observed upper limit on the signal cross section for the higgsino LSP model with large tan beta.
$\textbf{X-section U.L. 8 } -$ Observed upper limit on the signal cross section for the variable m(CHARGINO) - m(NEUTRALINO) higgsino LSP model with left-handed stop squarks.
$\textbf{X-section U.L. 8 } -$ Observed upper limit on the signal cross section for the variable m(CHARGINO) - m(NEUTRALINO) higgsino LSP model with left-handed stop squarks.
$\textbf{X-section U.L. 8 } -$ Observed upper limit on the signal cross section for the variable m(CHARGINO) - m(NEUTRALINO) higgsino LSP model with left-handed stop squarks.
$\textbf{X-section U.L. 8 } -$ Observed upper limit on the signal cross section for the variable m(CHARGINO) - m(NEUTRALINO) higgsino LSP model with left-handed stop squarks.
$\textbf{X-section U.L. 9 } -$ Observed upper limit on the signal cross section for the variable m(CHARGINO) - m(NEUTRALINO) higgsino LSP model with right-handed stop squarks.
$\textbf{X-section U.L. 9 } -$ Observed upper limit on the signal cross section for the variable m(CHARGINO) - m(NEUTRALINO) higgsino LSP model with right-handed stop squarks.
$\textbf{X-section U.L. 9 } -$ Observed upper limit on the signal cross section for the variable m(CHARGINO) - m(NEUTRALINO) higgsino LSP model with right-handed stop squarks.
$\textbf{X-section U.L. 9 } -$ Observed upper limit on the signal cross section for the variable m(CHARGINO) - m(NEUTRALINO) higgsino LSP model with right-handed stop squarks.
$\textbf{X-section U.L. 10 } -$ Observed upper limit on the signal cross section for the variable m(CHARGINO) - m(NEUTRALINO) higgsino LSP model with large tan beta.
$\textbf{X-section U.L. 10 } -$ Observed upper limit on the signal cross section for the variable m(CHARGINO) - m(NEUTRALINO) higgsino LSP model with large tan beta.
$\textbf{X-section U.L. 10 } -$ Observed upper limit on the signal cross section for the variable m(CHARGINO) - m(NEUTRALINO) higgsino LSP model with large tan beta.
$\textbf{X-section U.L. 10 } -$ Observed upper limit on the signal cross section for the variable m(CHARGINO) - m(NEUTRALINO) higgsino LSP model with large tan beta.
$\textbf{X-section U.L. 11 } -$ Observed upper limit on the signal cross section for the simplified model with m(STOP) - m(CHARGINO) = 10 GeV.
$\textbf{X-section U.L. 11 } -$ Observed upper limit on the signal cross section for the simplified model with m(STOP) - m(CHARGINO) = 10 GeV.
$\textbf{X-section U.L. 11 } -$ Observed upper limit on the signal cross section for the simplified model with m(STOP) - m(CHARGINO) = 10 GeV.
$\textbf{X-section U.L. 11 } -$ Observed upper limit on the signal cross section for the simplified model with m(STOP) - m(CHARGINO) = 10 GeV.
$\textbf{X-section U.L. 12 } -$ Observed 95% upper cross-section limit in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2) are considered with different branching ratios depending on the hypothesis being considered. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{X-section U.L. 12 } -$ Observed 95% upper cross-section limit in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2) are considered with different branching ratios depending on the hypothesis being considered. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{X-section U.L. 12 } -$ Observed 95% upper cross-section limit in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2) are considered with different branching ratios depending on the hypothesis being considered. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{X-section U.L. 12 } -$ Observed 95% upper cross-section limit in the plane of m(STOP) versus m(NEUTRALINO) for direct stop pair production in the higgsino LSP model where various decay modes (stop -> b C1, stop -> t N1, stop -> t N2) are considered with different branching ratios depending on the hypothesis being considered. In this model, dm(C1,N1) =5 GeV and dm(N2,N1)=10 GeV are assumed.
$\textbf{X-section U.L. 13 } -$ Observed upper limit on the signal cross section for the well-tempered neutralino model with left-handed stop squarks.
$\textbf{X-section U.L. 13 } -$ Observed upper limit on the signal cross section for the well-tempered neutralino model with left-handed stop squarks.
$\textbf{X-section U.L. 13 } -$ Observed upper limit on the signal cross section for the well-tempered neutralino model with left-handed stop squarks.
$\textbf{X-section U.L. 13 } -$ Observed upper limit on the signal cross section for the well-tempered neutralino model with left-handed stop squarks.
$\textbf{X-section U.L. 14 } -$ Observed upper limit on the signal cross section for the well-tempered neutralino model with right-handed stop squarks.
$\textbf{X-section U.L. 14 } -$ Observed upper limit on the signal cross section for the well-tempered neutralino model with right-handed stop squarks.
$\textbf{X-section U.L. 14 } -$ Observed upper limit on the signal cross section for the well-tempered neutralino model with right-handed stop squarks.
$\textbf{X-section U.L. 14 } -$ Observed upper limit on the signal cross section for the well-tempered neutralino model with right-handed stop squarks.
$\textbf{Cutflow 1 } -$ Cutflow for tN_med for the pure bino LSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{0}_{1} )$ = (600, 300) GeV. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV. Numbers are provided for the discovery SR, even if a shape fit is used for placing exclusion limits.
$\textbf{Cutflow 1 } -$ Cutflow for tN_med for the pure bino LSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{0}_{1} )$ = (600, 300) GeV. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV. Numbers are provided for the discovery SR, even if a shape fit is used for placing exclusion limits.
$\textbf{Cutflow 1 } -$ Cutflow for tN_med for the pure bino LSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{0}_{1} )$ = (600, 300) GeV. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV. Numbers are provided for the discovery SR, even if a shape fit is used for placing exclusion limits.
$\textbf{Cutflow 1 } -$ Cutflow for tN_med for the pure bino LSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{0}_{1} )$ = (600, 300) GeV. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV. Numbers are provided for the discovery SR, even if a shape fit is used for placing exclusion limits.
$\textbf{Cutflow 2 } -$ Cutflow for tN_high for the pure bino LSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{0}_{1} )$ = (1000, 1) GeV. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV.
$\textbf{Cutflow 2 } -$ Cutflow for tN_high for the pure bino LSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{0}_{1} )$ = (1000, 1) GeV. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV.
$\textbf{Cutflow 2 } -$ Cutflow for tN_high for the pure bino LSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{0}_{1} )$ = (1000, 1) GeV. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV.
$\textbf{Cutflow 2 } -$ Cutflow for tN_high for the pure bino LSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{0}_{1} )$ = (1000, 1) GeV. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV.
$\textbf{Cutflow 3 } -$ Cutflow for bWN for the pure bino LSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{0}_{1} )$ = (350, 230) GeV in bWN. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV. Numbers are provided for the discovery SR, even if a shape fit is used for placing exclusion limits.
$\textbf{Cutflow 3 } -$ Cutflow for bWN for the pure bino LSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{0}_{1} )$ = (350, 230) GeV in bWN. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV. Numbers are provided for the discovery SR, even if a shape fit is used for placing exclusion limits.
$\textbf{Cutflow 3 } -$ Cutflow for bWN for the pure bino LSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{0}_{1} )$ = (350, 230) GeV in bWN. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV. Numbers are provided for the discovery SR, even if a shape fit is used for placing exclusion limits.
$\textbf{Cutflow 3 } -$ Cutflow for bWN for the pure bino LSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{0}_{1} )$ = (350, 230) GeV in bWN. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV. Numbers are provided for the discovery SR, even if a shape fit is used for placing exclusion limits.
$\textbf{Cutflow 4 } -$ Cutflow for bffN for the pure bino LSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{0}_{1} )$ = (350, 300) GeV. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV. Numbers are provided for the discovery SR, even if a shape fit is used for placing exclusion limits.
$\textbf{Cutflow 4 } -$ Cutflow for bffN for the pure bino LSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{0}_{1} )$ = (350, 300) GeV. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV. Numbers are provided for the discovery SR, even if a shape fit is used for placing exclusion limits.
$\textbf{Cutflow 4 } -$ Cutflow for bffN for the pure bino LSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{0}_{1} )$ = (350, 300) GeV. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV. Numbers are provided for the discovery SR, even if a shape fit is used for placing exclusion limits.
$\textbf{Cutflow 4 } -$ Cutflow for bffN for the pure bino LSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{0}_{1} )$ = (350, 300) GeV. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV. Numbers are provided for the discovery SR, even if a shape fit is used for placing exclusion limits.
$\textbf{Cutflow 5 } -$ Cutflow for bC2x_diag for the wino NLSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{\pm}_{1} , \tilde{\chi}^{0}_{1} )$ = (737, 500, 250) GeV. Only stop pair production is considered in the cutflow. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV.
$\textbf{Cutflow 5 } -$ Cutflow for bC2x_diag for the wino NLSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{\pm}_{1} , \tilde{\chi}^{0}_{1} )$ = (737, 500, 250) GeV. Only stop pair production is considered in the cutflow. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV.
$\textbf{Cutflow 5 } -$ Cutflow for bC2x_diag for the wino NLSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{\pm}_{1} , \tilde{\chi}^{0}_{1} )$ = (737, 500, 250) GeV. Only stop pair production is considered in the cutflow. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV.
$\textbf{Cutflow 5 } -$ Cutflow for bC2x_diag for the wino NLSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{\pm}_{1} , \tilde{\chi}^{0}_{1} )$ = (737, 500, 250) GeV. Only stop pair production is considered in the cutflow. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV.
$\textbf{Cutflow 6 } -$ Cutflow for bC2x_med for the wino NLSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{\pm}_{1} , \tilde{\chi}^{0}_{1} )$ = (842, 300, 150) GeV. Only stop pair production is considered in the cutflow. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV.
$\textbf{Cutflow 6 } -$ Cutflow for bC2x_med for the wino NLSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{\pm}_{1} , \tilde{\chi}^{0}_{1} )$ = (842, 300, 150) GeV. Only stop pair production is considered in the cutflow. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV.
$\textbf{Cutflow 6 } -$ Cutflow for bC2x_med for the wino NLSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{\pm}_{1} , \tilde{\chi}^{0}_{1} )$ = (842, 300, 150) GeV. Only stop pair production is considered in the cutflow. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV.
$\textbf{Cutflow 6 } -$ Cutflow for bC2x_med for the wino NLSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{\pm}_{1} , \tilde{\chi}^{0}_{1} )$ = (842, 300, 150) GeV. Only stop pair production is considered in the cutflow. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV.
$\textbf{Cutflow 7 } -$ Cutflow for the simplified signal model with $\Delta m( \tilde{\chi}^{\pm}_{1} , \tilde{\chi}^{0}_{1} )$ = 10 GeV, considering $m(\tilde{t}_{1} , \tilde{\chi}^{\pm}_{1} , \tilde{\chi}^{0}_{1} )$ = (700, 690, 1). The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV.
$\textbf{Cutflow 7 } -$ Cutflow for the simplified signal model with $\Delta m( \tilde{\chi}^{\pm}_{1} , \tilde{\chi}^{0}_{1} )$ = 10 GeV, considering $m(\tilde{t}_{1} , \tilde{\chi}^{\pm}_{1} , \tilde{\chi}^{0}_{1} )$ = (700, 690, 1). The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV.
$\textbf{Cutflow 7 } -$ Cutflow for the simplified signal model with $\Delta m( \tilde{\chi}^{\pm}_{1} , \tilde{\chi}^{0}_{1} )$ = 10 GeV, considering $m(\tilde{t}_{1} , \tilde{\chi}^{\pm}_{1} , \tilde{\chi}^{0}_{1} )$ = (700, 690, 1). The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV.
$\textbf{Cutflow 7 } -$ Cutflow for the simplified signal model with $\Delta m( \tilde{\chi}^{\pm}_{1} , \tilde{\chi}^{0}_{1} )$ = 10 GeV, considering $m(\tilde{t}_{1} , \tilde{\chi}^{\pm}_{1} , \tilde{\chi}^{0}_{1} )$ = (700, 690, 1). The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV.
$\textbf{Cutflow 8 } -$ Cutflow for bCsoft_diag for the higgsino LSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{\pm}_{1} , \tilde{\chi}^{0}_{1} )$ = (400, 355, 350) GeV, assuming $\tilde{t}_{1} \sim \tilde{t}_{\mathrm{L}}$ and large $\tan\beta$. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV. Numbers are provided for the discovery SR, even if a shape fit is used for placing exclusion limits.
$\textbf{Cutflow 8 } -$ Cutflow for bCsoft_diag for the higgsino LSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{\pm}_{1} , \tilde{\chi}^{0}_{1} )$ = (400, 355, 350) GeV, assuming $\tilde{t}_{1} \sim \tilde{t}_{\mathrm{L}}$ and large $\tan\beta$. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV. Numbers are provided for the discovery SR, even if a shape fit is used for placing exclusion limits.
$\textbf{Cutflow 8 } -$ Cutflow for bCsoft_diag for the higgsino LSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{\pm}_{1} , \tilde{\chi}^{0}_{1} )$ = (400, 355, 350) GeV, assuming $\tilde{t}_{1} \sim \tilde{t}_{\mathrm{L}}$ and large $\tan\beta$. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV. Numbers are provided for the discovery SR, even if a shape fit is used for placing exclusion limits.
$\textbf{Cutflow 8 } -$ Cutflow for bCsoft_diag for the higgsino LSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{\pm}_{1} , \tilde{\chi}^{0}_{1} )$ = (400, 355, 350) GeV, assuming $\tilde{t}_{1} \sim \tilde{t}_{\mathrm{L}}$ and large $\tan\beta$. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV. Numbers are provided for the discovery SR, even if a shape fit is used for placing exclusion limits.
$\textbf{Cutflow 9 } -$ Cutflow for bCsoft_med for the higgsino LSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{\pm}_{1} , \tilde{\chi}^{0}_{1} )$ = (600, 205, 200) GeV, assuming $\tilde{t}_{1} \sim \tilde{t}_{\mathrm{L}}$ and large $\tan\beta$. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV. Numbers are provided for the discovery SR, even if a shape fit is used for placing exclusion limits.
$\textbf{Cutflow 9 } -$ Cutflow for bCsoft_med for the higgsino LSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{\pm}_{1} , \tilde{\chi}^{0}_{1} )$ = (600, 205, 200) GeV, assuming $\tilde{t}_{1} \sim \tilde{t}_{\mathrm{L}}$ and large $\tan\beta$. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV. Numbers are provided for the discovery SR, even if a shape fit is used for placing exclusion limits.
$\textbf{Cutflow 9 } -$ Cutflow for bCsoft_med for the higgsino LSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{\pm}_{1} , \tilde{\chi}^{0}_{1} )$ = (600, 205, 200) GeV, assuming $\tilde{t}_{1} \sim \tilde{t}_{\mathrm{L}}$ and large $\tan\beta$. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV. Numbers are provided for the discovery SR, even if a shape fit is used for placing exclusion limits.
$\textbf{Cutflow 9 } -$ Cutflow for bCsoft_med for the higgsino LSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{\pm}_{1} , \tilde{\chi}^{0}_{1} )$ = (600, 205, 200) GeV, assuming $\tilde{t}_{1} \sim \tilde{t}_{\mathrm{L}}$ and large $\tan\beta$. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV. Numbers are provided for the discovery SR, even if a shape fit is used for placing exclusion limits.
$\textbf{Cutflow 10 } -$ Cutflow for bCsoft_high for the higgsino LSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{\pm}_{1} , \tilde{\chi}^{0}_{1} )$ = (800, 155, 150) GeV, assuming $\tilde{t}_{1} \sim \tilde{t}_{\mathrm{L}}$ and large $\tan\beta$. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV. Numbers are provided for the discovery SR, even if a shape fit is used for placing exclusion limits.
$\textbf{Cutflow 10 } -$ Cutflow for bCsoft_high for the higgsino LSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{\pm}_{1} , \tilde{\chi}^{0}_{1} )$ = (800, 155, 150) GeV, assuming $\tilde{t}_{1} \sim \tilde{t}_{\mathrm{L}}$ and large $\tan\beta$. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV. Numbers are provided for the discovery SR, even if a shape fit is used for placing exclusion limits.
$\textbf{Cutflow 10 } -$ Cutflow for bCsoft_high for the higgsino LSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{\pm}_{1} , \tilde{\chi}^{0}_{1} )$ = (800, 155, 150) GeV, assuming $\tilde{t}_{1} \sim \tilde{t}_{\mathrm{L}}$ and large $\tan\beta$. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV. Numbers are provided for the discovery SR, even if a shape fit is used for placing exclusion limits.
$\textbf{Cutflow 10 } -$ Cutflow for bCsoft_high for the higgsino LSP signal model with $m(\tilde{t}_{1} , \tilde{\chi}^{\pm}_{1} , \tilde{\chi}^{0}_{1} )$ = (800, 155, 150) GeV, assuming $\tilde{t}_{1} \sim \tilde{t}_{\mathrm{L}}$ and large $\tan\beta$. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV. Numbers are provided for the discovery SR, even if a shape fit is used for placing exclusion limits.
$\textbf{Cutflow 11 } -$ Cutflow for DM_high for the spin-0 mediator model with $m(\phi, \chi)$ = (300, 1) GeV, assuming g=1 and a scalar mediator. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV.
$\textbf{Cutflow 11 } -$ Cutflow for DM_high for the spin-0 mediator model with $m(\phi, \chi)$ = (300, 1) GeV, assuming g=1 and a scalar mediator. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV.
$\textbf{Cutflow 11 } -$ Cutflow for DM_high for the spin-0 mediator model with $m(\phi, \chi)$ = (300, 1) GeV, assuming g=1 and a scalar mediator. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV.
$\textbf{Cutflow 11 } -$ Cutflow for DM_high for the spin-0 mediator model with $m(\phi, \chi)$ = (300, 1) GeV, assuming g=1 and a scalar mediator. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV.
$\textbf{Cutflow 12 } -$ Cutflow for DM_low for the spin-0 mediator model with $m(\phi, \chi)$ = (20, 1) GeV, assuming g=1 and a scalar mediator. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV.
$\textbf{Cutflow 12 } -$ Cutflow for DM_low for the spin-0 mediator model with $m(\phi, \chi)$ = (20, 1) GeV, assuming g=1 and a scalar mediator. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV.
$\textbf{Cutflow 12 } -$ Cutflow for DM_low for the spin-0 mediator model with $m(\phi, \chi)$ = (20, 1) GeV, assuming g=1 and a scalar mediator. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV.
$\textbf{Cutflow 12 } -$ Cutflow for DM_low for the spin-0 mediator model with $m(\phi, \chi)$ = (20, 1) GeV, assuming g=1 and a scalar mediator. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV.
$\textbf{Cutflow 13 } -$ Cutflow for DM_low_loose for the spin-0 mediator model with $m(\phi, \chi)$ = (20, 1) GeV, assuming g=1 and a scalar mediator. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV.
$\textbf{Cutflow 13 } -$ Cutflow for DM_low_loose for the spin-0 mediator model with $m(\phi, \chi)$ = (20, 1) GeV, assuming g=1 and a scalar mediator. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV.
$\textbf{Cutflow 13 } -$ Cutflow for DM_low_loose for the spin-0 mediator model with $m(\phi, \chi)$ = (20, 1) GeV, assuming g=1 and a scalar mediator. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV.
$\textbf{Cutflow 13 } -$ Cutflow for DM_low_loose for the spin-0 mediator model with $m(\phi, \chi)$ = (20, 1) GeV, assuming g=1 and a scalar mediator. The DxAOD skimming step requires at least one of the following criteria to be fullfilled: one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ triggers has fired and there is at least one loose muon (electron) with $p_{\mathrm{T}}$ > 3.5 (4.5) GeV; or one of the $E_{\mathrm{T}}^{\mathrm{miss}}$ or lepton triggers has fired and there is at least one loose lepton with $p_{\mathrm{T}}$ > 25 GeV.
$\textbf{Acceptance 1 } -$ Acceptance and efficiency for the bino LSP model in the $m_{\tilde{t}_{1}}$ vs $m_{\tilde{\chi}^{0}_{1}}$ plane. Efficiencies larger than 100% are observed in the bWN SR due differences in $am_{\mathrm{T2}}$ between truth and reconstruction level, in the absence of $b$-tagging inefficiencies. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Acceptance 1 } -$ Acceptance and efficiency for the bino LSP model in the $m_{\tilde{t}_{1}}$ vs $m_{\tilde{\chi}^{0}_{1}}$ plane. Efficiencies larger than 100% are observed in the bWN SR due differences in $am_{\mathrm{T2}}$ between truth and reconstruction level, in the absence of $b$-tagging inefficiencies. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Acceptance 1 } -$ Acceptance and efficiency for the bino LSP model in the $m_{\tilde{t}_{1}}$ vs $m_{\tilde{\chi}^{0}_{1}}$ plane. Efficiencies larger than 100% are observed in the bWN SR due differences in $am_{\mathrm{T2}}$ between truth and reconstruction level, in the absence of $b$-tagging inefficiencies. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Acceptance 1 } -$ Acceptance and efficiency for the bino LSP model in the $m_{\tilde{t}_{1}}$ vs $m_{\tilde{\chi}^{0}_{1}}$ plane. Efficiencies larger than 100% are observed in the bWN SR due differences in $am_{\mathrm{T2}}$ between truth and reconstruction level, in the absence of $b$-tagging inefficiencies. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Efficiency 1 } -$ Acceptance and efficiency for the bino LSP model in the $m_{\tilde{t}_{1}}$ vs $m_{\tilde{\chi}^{0}_{1}}$ plane. Efficiencies larger than 100% are observed in the bWN SR due differences in $am_{\mathrm{T2}}$ between truth and reconstruction level, in the absence of $b$-tagging inefficiencies. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Efficiency 1 } -$ Acceptance and efficiency for the bino LSP model in the $m_{\tilde{t}_{1}}$ vs $m_{\tilde{\chi}^{0}_{1}}$ plane. Efficiencies larger than 100% are observed in the bWN SR due differences in $am_{\mathrm{T2}}$ between truth and reconstruction level, in the absence of $b$-tagging inefficiencies. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Efficiency 1 } -$ Acceptance and efficiency for the bino LSP model in the $m_{\tilde{t}_{1}}$ vs $m_{\tilde{\chi}^{0}_{1}}$ plane. Efficiencies larger than 100% are observed in the bWN SR due differences in $am_{\mathrm{T2}}$ between truth and reconstruction level, in the absence of $b$-tagging inefficiencies. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Efficiency 1 } -$ Acceptance and efficiency for the bino LSP model in the $m_{\tilde{t}_{1}}$ vs $m_{\tilde{\chi}^{0}_{1}}$ plane. Efficiencies larger than 100% are observed in the bWN SR due differences in $am_{\mathrm{T2}}$ between truth and reconstruction level, in the absence of $b$-tagging inefficiencies. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Acceptance 2 } -$ Acceptance and efficiency for the bino LSP model in the $m_{\tilde{t}_{1}}$ vs $\Delta m(\tilde{t}_{1},\tilde{\chi}^{0}_{1})$ plane. Efficiencies larger than 100% are observed in the bWN SR due differences in $am_{\mathrm{T2}}$ between truth and reconstruction level, in the absence of $b$-tagging inefficiencies. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Acceptance 2 } -$ Acceptance and efficiency for the bino LSP model in the $m_{\tilde{t}_{1}}$ vs $\Delta m(\tilde{t}_{1},\tilde{\chi}^{0}_{1})$ plane. Efficiencies larger than 100% are observed in the bWN SR due differences in $am_{\mathrm{T2}}$ between truth and reconstruction level, in the absence of $b$-tagging inefficiencies. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Acceptance 2 } -$ Acceptance and efficiency for the bino LSP model in the $m_{\tilde{t}_{1}}$ vs $\Delta m(\tilde{t}_{1},\tilde{\chi}^{0}_{1})$ plane. Efficiencies larger than 100% are observed in the bWN SR due differences in $am_{\mathrm{T2}}$ between truth and reconstruction level, in the absence of $b$-tagging inefficiencies. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Acceptance 2 } -$ Acceptance and efficiency for the bino LSP model in the $m_{\tilde{t}_{1}}$ vs $\Delta m(\tilde{t}_{1},\tilde{\chi}^{0}_{1})$ plane. Efficiencies larger than 100% are observed in the bWN SR due differences in $am_{\mathrm{T2}}$ between truth and reconstruction level, in the absence of $b$-tagging inefficiencies. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Efficiency 2 } -$ Acceptance and efficiency for the bino LSP model in the $m_{\tilde{t}_{1}}$ vs $\Delta m(\tilde{t}_{1},\tilde{\chi}^{0}_{1})$ plane. Efficiencies larger than 100% are observed in the bWN SR due differences in $am_{\mathrm{T2}}$ between truth and reconstruction level, in the absence of $b$-tagging inefficiencies. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Efficiency 2 } -$ Acceptance and efficiency for the bino LSP model in the $m_{\tilde{t}_{1}}$ vs $\Delta m(\tilde{t}_{1},\tilde{\chi}^{0}_{1})$ plane. Efficiencies larger than 100% are observed in the bWN SR due differences in $am_{\mathrm{T2}}$ between truth and reconstruction level, in the absence of $b$-tagging inefficiencies. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Efficiency 2 } -$ Acceptance and efficiency for the bino LSP model in the $m_{\tilde{t}_{1}}$ vs $\Delta m(\tilde{t}_{1},\tilde{\chi}^{0}_{1})$ plane. Efficiencies larger than 100% are observed in the bWN SR due differences in $am_{\mathrm{T2}}$ between truth and reconstruction level, in the absence of $b$-tagging inefficiencies. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Efficiency 2 } -$ Acceptance and efficiency for the bino LSP model in the $m_{\tilde{t}_{1}}$ vs $\Delta m(\tilde{t}_{1},\tilde{\chi}^{0}_{1})$ plane. Efficiencies larger than 100% are observed in the bWN SR due differences in $am_{\mathrm{T2}}$ between truth and reconstruction level, in the absence of $b$-tagging inefficiencies. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Acceptance 3 } -$ Acceptance and efficiency for the wino NLSP model with $\mu > 0$.
$\textbf{Acceptance 3 } -$ Acceptance and efficiency for the wino NLSP model with $\mu > 0$.
$\textbf{Acceptance 3 } -$ Acceptance and efficiency for the wino NLSP model with $\mu > 0$.
$\textbf{Acceptance 3 } -$ Acceptance and efficiency for the wino NLSP model with $\mu > 0$.
$\textbf{Efficiency 3 } -$ Acceptance and efficiency for the wino NLSP model with $\mu > 0$.
$\textbf{Efficiency 3 } -$ Acceptance and efficiency for the wino NLSP model with $\mu > 0$.
$\textbf{Efficiency 3 } -$ Acceptance and efficiency for the wino NLSP model with $\mu > 0$.
$\textbf{Efficiency 3 } -$ Acceptance and efficiency for the wino NLSP model with $\mu > 0$.
$\textbf{Acceptance 4 } -$ Acceptance and efficiency for the higgsino LSP model with $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{0}_{1}) = 5$ GeV. The model assumes large $\tan\beta$ and the $\tilde{t}_{1}$ to be mostly $\tilde{t}_{L}$. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Acceptance 4 } -$ Acceptance and efficiency for the higgsino LSP model with $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{0}_{1}) = 5$ GeV. The model assumes large $\tan\beta$ and the $\tilde{t}_{1}$ to be mostly $\tilde{t}_{L}$. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Acceptance 4 } -$ Acceptance and efficiency for the higgsino LSP model with $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{0}_{1}) = 5$ GeV. The model assumes large $\tan\beta$ and the $\tilde{t}_{1}$ to be mostly $\tilde{t}_{L}$. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Acceptance 4 } -$ Acceptance and efficiency for the higgsino LSP model with $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{0}_{1}) = 5$ GeV. The model assumes large $\tan\beta$ and the $\tilde{t}_{1}$ to be mostly $\tilde{t}_{L}$. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Efficiency 4 } -$ Acceptance and efficiency for the higgsino LSP model with $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{0}_{1}) = 5$ GeV. The model assumes large $\tan\beta$ and the $\tilde{t}_{1}$ to be mostly $\tilde{t}_{L}$. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Efficiency 4 } -$ Acceptance and efficiency for the higgsino LSP model with $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{0}_{1}) = 5$ GeV. The model assumes large $\tan\beta$ and the $\tilde{t}_{1}$ to be mostly $\tilde{t}_{L}$. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Efficiency 4 } -$ Acceptance and efficiency for the higgsino LSP model with $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{0}_{1}) = 5$ GeV. The model assumes large $\tan\beta$ and the $\tilde{t}_{1}$ to be mostly $\tilde{t}_{L}$. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Efficiency 4 } -$ Acceptance and efficiency for the higgsino LSP model with $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{0}_{1}) = 5$ GeV. The model assumes large $\tan\beta$ and the $\tilde{t}_{1}$ to be mostly $\tilde{t}_{L}$. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Acceptance 5 } -$ Acceptance and efficiency for the higgsino LSP model with $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{0}_{1}) = 5$ GeV, in the region where $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{0}_{1}) < m_{\textrm{top}}$. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Acceptance 5 } -$ Acceptance and efficiency for the higgsino LSP model with $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{0}_{1}) = 5$ GeV, in the region where $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{0}_{1}) < m_{\textrm{top}}$. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Acceptance 5 } -$ Acceptance and efficiency for the higgsino LSP model with $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{0}_{1}) = 5$ GeV, in the region where $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{0}_{1}) < m_{\textrm{top}}$. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Acceptance 5 } -$ Acceptance and efficiency for the higgsino LSP model with $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{0}_{1}) = 5$ GeV, in the region where $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{0}_{1}) < m_{\textrm{top}}$. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Efficiency 5 } -$ Acceptance and efficiency for the higgsino LSP model with $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{0}_{1}) = 5$ GeV, in the region where $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{0}_{1}) < m_{\textrm{top}}$. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Efficiency 5 } -$ Acceptance and efficiency for the higgsino LSP model with $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{0}_{1}) = 5$ GeV, in the region where $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{0}_{1}) < m_{\textrm{top}}$. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Efficiency 5 } -$ Acceptance and efficiency for the higgsino LSP model with $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{0}_{1}) = 5$ GeV, in the region where $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{0}_{1}) < m_{\textrm{top}}$. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Efficiency 5 } -$ Acceptance and efficiency for the higgsino LSP model with $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{0}_{1}) = 5$ GeV, in the region where $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{0}_{1}) < m_{\textrm{top}}$. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Acceptance 6 } -$ Acceptance and efficiency for the simplified model with $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{\pm}_{1}) = 10$ GeV.
$\textbf{Acceptance 6 } -$ Acceptance and efficiency for the simplified model with $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{\pm}_{1}) = 10$ GeV.
$\textbf{Acceptance 6 } -$ Acceptance and efficiency for the simplified model with $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{\pm}_{1}) = 10$ GeV.
$\textbf{Acceptance 6 } -$ Acceptance and efficiency for the simplified model with $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{\pm}_{1}) = 10$ GeV.
$\textbf{Efficiency 6 } -$ Acceptance and efficiency for the simplified model with $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{\pm}_{1}) = 10$ GeV.
$\textbf{Efficiency 6 } -$ Acceptance and efficiency for the simplified model with $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{\pm}_{1}) = 10$ GeV.
$\textbf{Efficiency 6 } -$ Acceptance and efficiency for the simplified model with $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{\pm}_{1}) = 10$ GeV.
$\textbf{Efficiency 6 } -$ Acceptance and efficiency for the simplified model with $\Delta m (\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{\pm}_{1}) = 10$ GeV.
$\textbf{Acceptance 7 } -$ Acceptance and efficiency for the spin-0 mediator model, assuming a scalar mediator. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Acceptance 7 } -$ Acceptance and efficiency for the spin-0 mediator model, assuming a scalar mediator. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Acceptance 7 } -$ Acceptance and efficiency for the spin-0 mediator model, assuming a scalar mediator. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Acceptance 7 } -$ Acceptance and efficiency for the spin-0 mediator model, assuming a scalar mediator. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Efficiency 7 } -$ Acceptance and efficiency for the spin-0 mediator model, assuming a scalar mediator. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Efficiency 7 } -$ Acceptance and efficiency for the spin-0 mediator model, assuming a scalar mediator. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Efficiency 7 } -$ Acceptance and efficiency for the spin-0 mediator model, assuming a scalar mediator. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
$\textbf{Efficiency 7 } -$ Acceptance and efficiency for the spin-0 mediator model, assuming a scalar mediator. Acceptance and efficiency numbers are provided for discovery SRs even if shape fits are used for placing exclusion limits.
The differential cross-section for the production of a $W$ boson in association with a top quark is measured for several particle-level observables. The measurements are performed using 36.1 fb$^{-1}$ of $pp$ collision data collected with the ATLAS detector at the LHC in 2015 and 2016. Differential cross-sections are measured in a fiducial phase space defined by the presence of two charged leptons and exactly one jet matched to a $b$-hadron, and are normalised with the fiducial cross-section. Results are found to be in good agreement with predictions from several Monte Carlo event generators.
Fiducial region definition.
Absolute cross-sections differential in E(b). Uncertainties are signed to show correlations.
Absolute cross-sections differential in m(l1b). Uncertainties are signed to show correlations.
Absolute cross-sections differential in m(l2b). Uncertainties are signed to show correlations.
Absolute cross-sections differential in E(llb). Uncertainties are signed to show correlations.
Absolute cross-sections differential in mT(llvvb). Uncertainties are signed to show correlations.
Absolute cross-sections differential in m(llb). Uncertainties are signed to show correlations.
Normalised cross-sections differential in E(b). Uncertainties are signed to show correlations.
Normalised cross-sections differential in m(l1b). Uncertainties are signed to show correlations.
Normalised cross-sections differential in m(l2b). Uncertainties are signed to show correlations.
Normalised cross-sections differential in E(llb). Uncertainties are signed to show correlations.
Normalised cross-sections differential in mT(llvvb). Uncertainties are signed to show correlations.
Normalised cross-sections differential in m(llb). Uncertainties are signed to show correlations.
A search for new physics using events containing an imbalance in transverse momentum and one or more energetic jets arising from initial-state radiation or the hadronic decay of W or Z bosons is presented. A data sample of proton-proton collisions at $\sqrt{s} = $ 13 TeV, collected with the CMS detector at the LHC and corresponding to an integrated luminosity of 35.9 fb$^{-1}$, is used. The observed data are found to be in agreement with the expectation from standard model processes. The results are interpreted as limits on the dark matter production cross section in simplified models with vector, axial-vector, scalar, and pseudoscalar mediators. Interpretations in the context of fermion portal and nonthermal dark matter models are also provided. In addition, the results are interpreted in terms of invisible decays of the Higgs boson and set stringent limits on the fundamental Planck scale in the Arkani-Hamed, Dimopoulos, and Dvali model with large extra spatial dimensions.
Comparison between data and MC simulation in the $\gamma$+jets control sample before and after performing the simultaneous fit across all the control samples and the signal region assuming the absence of any signal. The plot shows the monojet category. The hadronic recoil $p_{T}$ in $\gamma$+jets events is used as a proxy for $p_{T}^{miss}$ in the signal region. The last bin includes all events with hadronic recoil $p_{T}$ larger than 1250 GeV in the monojet category.
Comparison between data and MC simulation in the $\gamma$+jets control sample before and after performing the simultaneous fit across all the control samples and the signal region assuming the absence of any signal. The plot shows the mono-V category. The hadronic recoil $p_{T}$ in $\gamma$+jets events is used as a proxy for $p_{T}^{miss}$ in the signal region. The last bin includes all events with hadronic recoil $p_{T}$ larger than 750 GeV in the mono-V category.
Comparison between data and MC simulation in the dimuon control samples before and after performing the simultaneous fit across all the control samples and the signal region assuming the absence of any signal. Plot correspond to the monojet category. The hadronic recoil $p_{T}$ in dilepton events is used as a proxy for $p_{T}^{miss}$ in the signal region. The leading contribution is represented by Z+jets production. The other backgrounds include top quark, diboson, and W+jets processes.
Comparison between data and MC simulation in the dimuon control samples before and after performing the simultaneous fit across all the control samples and the signal region assuming the absence of any signal. Plot correspond to the mono-V category. The hadronic recoil $p_{T}$ in dilepton events is used as a proxy for $p_{T}^{miss}$ in the signal region. The leading contribution is represented by Z+jets production. The other backgrounds include top quark, diboson, and W+jets processes.
Comparison between data and MC simulation in the dielectron control samples before and after performing the simultaneous fit across all the control samples and the signal region assuming the absence of any signal. Plot correspond to the monojet category. The hadronic recoil $p_{T}$ in dilepton events is used as a proxy for $p_{T}^{miss}$ in the signal region. The leading contribution is represented by Z+jets production. The other backgrounds include top quark, diboson, and W+jets processes.
Comparison between data and MC simulation in the dielectron control samples before and after performing the simultaneous fit across all the control samples and the signal region assuming the absence of any signal. Plot correspond to the mono-V category. The hadronic recoil $p_{T}$ in dilepton events is used as a proxy for $p_{T}^{miss}$ in the signal region. The leading contribution is represented by Z+jets production. The other backgrounds include top quark, diboson, and W+jets processes.
Comparison between data and MC simulation in the single-muon control samples before and after performing the simultaneous fit across all the control samples and the signal region assuming the absence of any signal. Plot correspond to the monojet category. The hadronic recoil $p_{T}$ in dilepton events is used as a proxy for $p_{T}^{miss}$ in the signal region. The leading contribution is represented by W+jets production. The other backgrounds include top quark, diboson, Z+jets, and QCD multijet processes.
Comparison between data and MC simulation in the single-muon control samples before and after performing the simultaneous fit across all the control samples and the signal region assuming the absence of any signal. Plot correspond to the mono-V category. The hadronic recoil $p_{T}$ in dilepton events is used as a proxy for $p_{T}^{miss}$ in the signal region. The leading contribution is represented by W+jets production. The other backgrounds include top quark, diboson, Z+jets, and QCD multijet processes.
Comparison between data and MC simulation in the single-electron control samples before and after performing the simultaneous fit across all the control samples and the signal region assuming the absence of any signal. Plot correspond to the monojet category. The hadronic recoil $p_{T}$ in dilepton events is used as a proxy for $p_{T}^{miss}$ in the signal region. The leading contribution is represented by Z+jets production. The other backgrounds include top quark, diboson, Z+jets, and QCD multijet processes.
Comparison between data and MC simulation in the single-electron control samples before and after performing the simultaneous fit across all the control samples and the signal region assuming the absence of any signal. Plot correspond to the mono-V category. The hadronic recoil $p_{T}$ in dilepton events is used as a proxy for $p_{T}^{miss}$ in the signal region. The leading contribution is represented by W+jets production. The other backgrounds include top quark, diboson, Z+jets, and QCD multijet processes.
Observed $p_{T}^{miss}$ distribution in the monojet signal region compared with the post-fit background expectations for various SM processes. The last bin includes all events with $p_{T}^{miss} > 1250$ GeV for the monojet category. The expected background distributions are evaluated after performing a combined fit to the data in all the control samples, not including the signal region. Expected signal distribution for a 2 TeV axial-vector mediator, decaying to 1 GeV DM particles, is overlaid.
Observed $p_{T}^{miss}$ distribution in the mono-V signal region compared with the post-fit background expectations for various SM processes. The last bin includes all events with $p_{T}^{miss} > 750$ GeV for the mono-V category. The expected background distributions are evaluated after performing a combined fit to the data in all the control samples, not including the signal region. Expected signal distribution for a 2 TeV axial-vector mediator, decaying to 1 GeV DM particles, is overlaid.
Observed $p_{T}^{miss}$ distribution in the monojet signal region compared with the post-fit background expectations for various SM processes. The last bin includes all events with $p_{T}^{miss} > 1250$ GeV for the monojet category. The expected background distributions are evaluated after performing a combined fit to the data in all the control samples, as well as in the signal region. The fit is performed assuming the absence of any signal. Expected signal distribution for a 2 TeV axial-vector mediator, decaying to 1 GeV DM particles, is overlaid.
Observed $p_{T}^{miss}$ distribution in the mono-V signal region compared with the post-fit background expectations for various SM processes. The last bin includes all events with $p_{T}^{miss} > 750$ GeV for the mono-V category. The expected background distributions are evaluated after performing a combined fit to the data in all the control samples, not including as well as in the signal region. The fit is performed assuming the absence of any signal. Expected signal distribution for a 2 TeV axial-vector mediator, decaying to 1 GeV DM particles, is overlaid.
Observed exclusion limits at 95% CL on $\mu = \sigma/\sigma_{th}$ in the $m_{med}-m_{DM}$ plane assuming a vector mediator. N.B.: the granularity in the presented limit values is reduced with respect to the published result.
Expected exclusion limits at 95% CL on $\mu = \sigma/\sigma_{th}$ in the $m_{med}-m_{DM}$ plane assuming a vector mediator. N.B.: the granularity in the presented limit values is reduced with respect to the published result.
Observed exclusion limits at 95% CL on $\mu = \sigma/\sigma_{th}$ in the $m_{med}-m_{DM}$ plane assuming an axial-vector mediator. N.B.: the granularity in the presented limit values is reduced with respect to the published result.
Expected exclusion limits at 95% CL on $\mu = \sigma/\sigma_{th}$ in the $m_{med}-m_{DM}$ plane assuming an axial-vector mediator. N.B.: the granularity in the presented limit values is reduced with respect to the published result.
Observed exclusion contour at 95% CL on $\mu = \sigma/\sigma_{th}$ in the $m_{med}-m_{DM}$ plane assuming a vector mediator.
Expected exclusion contour at 95% CL on $\mu = \sigma/\sigma_{th}$ in the $m_{med}-m_{DM}$ plane assuming a vector mediator.
Observed exclusion contour at 95% CL on $\mu = \sigma/\sigma_{th}$ in the $m_{med}-m_{DM}$ plane assuming an axial-vector mediator.
Expected exclusion contour at 95% CL on $\mu = \sigma/\sigma_{th}$ in the $m_{med}-m_{DM}$ plane assuming an axial-vector mediator.
Exclusion limits at 95% CL on $\mu = \sigma/\sigma_{th}$ vs $m_{med}$ for $m_{DM} = 1$ GeV assuming a scalar mediator.
Observed exclusion limits at 95% CL on $\mu = \sigma/\sigma_{th}$ in the $m_{med}-m_{DM}$ plane assuming a pseudoscalar mediator. N.B.: the granularity in the presented limit values is reduced with respect to the published result.
Expected exclusion limits at 95% CL on $\mu = \sigma/\sigma_{th}$ in the $m_{med}-m_{DM}$ plane assuming a pseudoscalar mediator. N.B.: the granularity in the presented limit values is reduced with respect to the published result.
Observed exclusion contour at 95% CL on $\mu = \sigma/\sigma_{th}$ in the $m_{med}-m_{DM}$ plane assuming a pseudoscalar mediator.
Expected exclusion contour at 95% CL on $\mu = \sigma/\sigma_{th}$ in the $m_{med}-m_{DM}$ plane assuming a pseudoscalar mediator.
Observed exclusion contour at 95% CL in the $g_{q}-m_{med}$ plane assuming a vector mediator.
Exclusion exclusion contour at 95% CL in the $g_{q}-m_{med}$ plane assuming a vector mediator.
Observed exclusion contour at 95% CL in the $g_{q}-m_{med}$ plane assuming an axial-vector mediator.
Exclusion exclusion contour at 95% CL in the $g_{q}-m_{med}$ plane assuming an axial-vector mediator.
Observed upper limits at 90% CL on $\sigma_{DM-nucleon}$ vs $m_{med}$ for vector mediator
Expected upper limits at 90% CL on $\sigma_{DM-nucleon}$ vs $m_{med}$ for vector mediator
Observed upper limits at 90% CL on $\sigma_{DM-nucleon}$ vs $m_{med}$ for axial-vector mediator
Expected upper limits at 90% CL on $\sigma_{DM-nucleon}$ vs $m_{med}$ for axial-vector mediator
Observed upper limits at 90% CL on velocity averaged DM annihilation cross section derived from those placed for pseudoscalar mediators.
Expected upper limits at 90% CL on velocity averaged DM annihilation cross section derived from those placed for pseudoscalar mediators.
Correlations between the predicted background yields in all the $p_{T}^{miss}$ bins of the monojet signal region.
Correlations between the predicted background yields in all the $p_{T}^{miss}$ bins of the mono-V signal region.
The coupling properties of the Higgs boson are studied in the four-lepton decay channel using 36.1 fb$^{-1}$ of $pp$ collision data from the LHC at a centre-of-mass energy of 13 TeV collected by the ATLAS detector. Cross sections are measured for the four key production modes in several exclusive regions of the Higgs boson production phase space and are interpreted in terms of coupling modifiers. The inclusive cross section times branching ratio for $H \rightarrow ZZ^*$ decay and for a Higgs boson absolute rapidity below 2.5 is measured to be $1.73^{+0.24}_{-0.23}$(stat.)$^{+0.10}_{-0.08}$(exp.)$\pm 0.04$(th.) pb compared to the Standard Model prediction of $1.34\pm0.09$ pb. In addition, the tensor structure of the Higgs boson couplings is studied using an effective Lagrangian approach for the description of interactions beyond the Standard Model. Constraints are placed on the non-Standard-Model CP-even and CP-odd couplings to $Z$ bosons and on the CP-odd coupling to gluons.
The expected number of SM Higgs boson events with a mass mH= 125.09 GeV in the mass range 118 < m4l < 129 GeV for an integrated luminosity of 36.1/fb and sqrt(s)= 13 TeV in each reconstructed event category, shown separately for each Stage-0 production bin. The ggF and bbH contributions are shown separately but both contribute to the same (ggF) production bin. Statistical and systematic uncertainties are added in quadrature.
The observed and expected numbers of signal and background events in the four-lepton decay channels for an integrated luminosity of 36.1/fb and at sqrt(s)= 13 TeV, assuming the SM Higgs boson signal with a mass m_{H} = 125.09 GeV . The second column shows the expected number of signal events for the full mass range while the subsequent columns correspond to the mass range of 118 < m4l < 129 GeV. In addition to the ZZ* background, the contribution of other backgrounds is shown, comprising the data-driven estimate from Table 4 and the simulation-based estimate of contributions from rare triboson and tbar{t}V processes. Statistical and systematic uncertainties are added in quadrature.
The expected and observed numbers of signal events in reconstructed event categories for an integrated luminosity of 36.1/fb at sqrt(s)= 13 TeV, together with signal acceptances for each Stage-0 production mode. Results are obtained in bins of BDT discriminants using coarse binning with several bins merged into one. Signal acceptances less than 0.0001 are set to 0.
The observed values of Sigma*BR(H->ZZ*), the SM expected cross section sBRsm and their ratio Sigma*BR/(Sigma*BR)_SM for the inclusive production and in each Stage-0 and reduced Stage-1 production bin for an integrated luminosity of 36.1/fb and at sqrt(s)=13 TeV. The bbH contribution is considered as a part of the ggF production bins. The upper limits correspond to the 95% CL obtained with pseudo-experiments using the CL_s method. The uncertainties are given as (stat.)+(exp.)+(th.) for Stage 0 and as (stat.)+(syst.) for reduced Stage 1. Values without uncertainity are 95% CL upper limits.
Signal acceptance obtained as the ratio of the number of simulated signal events satisfying the event selection criteria in each reconstructed event category over the total number of events generated in the phase space specified by a given reduced Stage-1 ggF production bin. Results are obtained in bins of BDT discriminants using coarse binning with several bins merged into one. Values less than 0.0001 are set to 0.
Signal acceptance obtained as the ratio of the number of simulated signal events satisfying the event selection criteria in each reconstructed event category over the total number of events generated in the phase space specified by the given reduced Stage-1 VBF and VH production bins. Results are obtained in bins of BDT discriminants using coarse binning with several bins merged into one. Values less than 0.0001 are set to 0.
The signal strengths mu for the inclusive production and in each Stage-0 and reduced Stage-1 production bin for an integrated luminosity of 36.1/fb and at sqrt(s)=13 TeV. The bbH contribution is considered as a part of the ggF production bins. The upper limits correspond to the 95% CL obtained with pseudo-experiments using the CL_s method. The uncertainties are given as (stat.)+(exp.)+(th.) for Stage 0 and as (stat.)+(syst.) for reduced Stage 1. Values without uncertainity are 95% CL upper limits.
Signal acceptance (in percent) obtained as the ratio of the number of simulated signal events satisfying the event selection criteria in each reconstructed event category to the total number of generated events, as predicted by the MadGraph5_aMC@NLO generator assuming the SM coupling tensor structure or the BSM tensor structure with ($\kappa_{SM}$ = 1, | $\kappa_{AVV}$ | $\neq$ 0).
Number of expected ggF Higgs boson events for an integrated luminosity of $\mathcal L=36.1 \text{fb}^{-1}$ and at $\sqrt{\mathrm{s}}=13$ TeV, as predicted by the MadGraph5_aMC@NLO generator assuming the SM coupling tensor structure or the BSM tensor structure with ($\kappa_{SM}=1$, $|\kappa_{Avv}|=6$). The highest-order SM predicition for the sum of the ggF, ttH and bbH contributions is also shown for comparison.
Number of expected VBF and VH Higgs boson events for an integrated luminosity of $\mathcal L=36.1 \text{fb}^{-1}$ and at $\sqrt{\mathrm{s}}=13$ TeV, as predicted by the MadGraph5_aMC@NLO generator assuming the SM coupling tensor structure or the BSM tensor structure with ($\kappa_{SM}=1$, $|\kappa_{Avv}|=5$). The highest-order SM predicition for the sum of the VBF and VH contributions is also shown for comparison.
Expected Correlation Matrix for Stage 0
Observed Correlation Matrix for Stage 0. As upper limits are derived for ttH and VH POIs using the observed data, the corresponding terms inside the matrix are set to zero.
Expected Correlation Matrix for Reduced Stage 1
Observed Correlation Matrix for Reduced Stage 1. As upper limits are derived for ttH and VH POIs using the observed data, the corresponding terms inside the matrix are set to zero.
Expected Covariance Matrix for Stage 0
Observed Covariance Matrix for Stage 0. As upper limits are derived for ttH and VH POIs using the observed data, the corresponding terms inside the matrix are set to zero.
Expected Covariance Matrix for Reduced Stage 1
Observed Covariance Matrix for Reduced Stage 1. As upper limits are derived for ttH and VH POIs using the observed data, the corresponding terms inside the matrix are set to zero.
Likelihood contours at 68% CL in the (Sigma_ggF*B , Sigma_VBF*B ) plane
Likelihood contours at 95% CL in the (Sigma_ggF*B , Sigma_VBF*B ) plane
Expected two-dimensional negative log-likelihood scans for $\kappa_{HVV}$ versus $\kappa_{AVV}$ coupling parameters using $\mathcal L=36.1 \text{fb}^{-1}$ of data and at $\sqrt{\mathrm{s}}=13$ TeV. The couplings $\kappa_{Hgg}$ and $\kappa_{SM}$ are fixed to the SM value of one in the fit. The 95% CL exclusion limits are shown.
Observed two-dimensional negative log-likelihood scans for $\kappa_{HVV}$ versus $\kappa_{AVV}$ coupling parameters using $\mathcal L=36.1 \text{fb}^{-1}$ of data and at $\sqrt{\mathrm{s}}=13$ TeV. The couplings $\kappa_{Hgg}$ and $\kappa_{SM}$ are fixed to the SM value of one in the fit. The 95% CL exclusion limits are shown.
Expected two-dimensional negative log-likelihood scans for $\kappa_{HVV}$ versus $\kappa_{AVV}$ coupling parameters using $\mathcal L=36.1 \text{fb}^{-1}$ of data and at $\sqrt{\mathrm{s}}=13$ TeV. The coupling $\kappa_{Hgg}$ is fixed to the SM value of one in the fit. The coupling $\kappa_{SM}$ is left as a free parameter of the fit. The 95% CL exclusion limits are shown.
Observed two-dimensional negative log-likelihood scans for $\kappa_{HVV}$ versus $\kappa_{AVV}$ coupling parameters using $\mathcal L=36.1 \text{fb}^{-1}$ of data and at $\sqrt{\mathrm{s}}=13$ TeV. The coupling $\kappa_{Hgg}$ is fixed to the SM value of one in the fit. The coupling $\kappa_{SM}$ is left as a free parameter of the fit. The 95% CL exclusion limits are shown.
Expected two-dimensional negative log-likelihood scans for $\kappa_{HVV}$ versus $\kappa_{SM}$ coupling parameters using $\mathcal L=36.1 \text{fb}^{-1}$ of data and at $\sqrt{\mathrm{s}}=13$ TeV. The 95% CL exclusion limits are shown.
Observed two-dimensional negative log-likelihood scans for $\kappa_{HVV}$ versus $\kappa_{SM}$ coupling parameters using $\mathcal L=36.1 \text{fb}^{-1}$ of data and at $\sqrt{\mathrm{s}}=13$ TeV. The 95% CL exclusion limits are shown.
Expected two-dimensional negative log-likelihood scans for $\kappa_{AVV}$ versus $\kappa_{SM}$ coupling parameters using $\mathcal L=36.1 \text{fb}^{-1}$ of data and at $\sqrt{\mathrm{s}}=13$ TeV. The 95% CL exclusion limits are shown.
Observed two-dimensional negative log-likelihood scans for $\kappa_{AVV}$ versus $\kappa_{SM}$ coupling parameters using $\mathcal L=36.1 \text{fb}^{-1}$ of data and at $\sqrt{\mathrm{s}}=13$ TeV. The 95% CL exclusion limits are shown.
This paper presents a search for direct electroweak gaugino or gluino pair production with a chargino nearly mass-degenerate with a stable neutralino. It is based on an integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ of $pp$ collisions at $\sqrt{s} = 13$ TeV collected by the ATLAS experiment at the LHC. The final state of interest is a disappearing track accompanied by at least one jet with high transverse momentum from initial-state radiation or by four jets from the gluino decay chain. The use of short track segments reconstructed from the innermost tracking layers significantly improves the sensitivity to short chargino lifetimes. The results are found to be consistent with Standard Model predictions. Exclusion limits are set at 95% confidence level on the mass of charginos and gluinos for different chargino lifetimes. For a pure wino with a lifetime of about 0.2 ns, chargino masses up to 460 GeV are excluded. For the strong production channel, gluino masses up to 1.65 TeV are excluded assuming a chargino mass of 460 GeV and lifetime of 0.2 ns.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the high-Emiss region.
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Model dependent upper limits on cross-section (fb) for the electroweak production are shown by grey numbers in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Model dependent upper limits on cross-section (pb) for the electroweak production are shown by grey numbers in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Model dependent upper limits on cross-section (pb) for the electroweak production are shown by grey numbers in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Model dependent upper limits on cross-section (pb) for the electroweak production are shown by grey numbers in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Model dependent upper limits on cross-section (pb) for the electroweak production are shown by grey numbers in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Total acceptance $\times$ efficiency of the electroweak channel. The total signal acceptance $\times$ efficiency is defined as the probability of an event passing the signal region selection when an electroweak gaugino pair is produced in a pp collision.
Total acceptance $\times$ efficiency of the electroweak channel. The total signal acceptance $\times$ efficiency is defined as the probability of an event passing the signal region selection when an electroweak gaugino pair is produced in a pp collision.
Total acceptance $\times$ efficiency of the electroweak channel. The total signal acceptance $\times$ efficiency is defined as the probability of an event passing the signal region selection when an electroweak gaugino pair is produced in a pp collision.
Total acceptance $\times$ efficiency of the electroweak channel. The total signal acceptance $\times$ efficiency is defined as the probability of an event passing the signal region selection when an electroweak gaugino pair is produced in a pp collision.
Total acceptance $\times$ efficiency of the electroweak channel. The total signal acceptance $\times$ efficiency is defined as the probability of an event passing the signal region selection when an electroweak gaugino pair is produced in a pp collision.
Total acceptance $\times$ efficiency of the strong channel. In white regions, no simulation sample is available. The left-upper triangle region is not allowed kinematically in wino-LSP scenarios. The total signal acceptance $\times$ efficiency is calculated relative to events in which the gluinos decay into electroweak gaugino pairs.
Total acceptance $\times$ efficiency of the strong channel. In white regions, no simulation sample is available. The left-upper triangle region is not allowed kinematically in wino-LSP scenarios. The total signal acceptance $\times$ efficiency is calculated relative to events in which the gluinos decay into electroweak gaugino pairs.
Total acceptance $\times$ efficiency of the strong channel. In white regions, no simulation sample is available. The left-upper triangle region is not allowed kinematically in wino-LSP scenarios. The total signal acceptance $\times$ efficiency is calculated relative to events in which the gluinos decay into electroweak gaugino pairs.
Total acceptance $\times$ efficiency of the strong channel. In white regions, no simulation sample is available. The left-upper triangle region is not allowed kinematically in wino-LSP scenarios. The total signal acceptance $\times$ efficiency is calculated relative to events in which the gluinos decay into electroweak gaugino pairs.
Total acceptance $\times$ efficiency of the strong channel. In white regions, no simulation sample is available. The left-upper triangle region is not allowed kinematically in wino-LSP scenarios. The total signal acceptance $\times$ efficiency is calculated relative to events in which the gluinos decay into electroweak gaugino pairs.
The generator-level acceptance after reconstruction, for selecting and reconstructing charginos as a function of the chargino $eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the electroweak channel as a function of the chargino $eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the electroweak channel as a function of the chargino $eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the electroweak channel as a function of the chargino $eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the electroweak channel as a function of the chargino $eta$ and chargino decay radius (at generator level).
The generator-level acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the electroweak channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the electroweak channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the electroweak channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the electroweak channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The generator-level acceptance after reconstruction, for selecting and reconstructing charginos as a function of the chargino $\eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level).
The generator-level acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in direct electroweak production with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in direct electroweak production with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in direct electroweak production with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in direct electroweak production with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in direct electroweak production with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in the strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in the strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in the strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in the strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in the strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
The event and tracklet generator-level acceptance and selection efficiency for a few electroweak signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few electroweak signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few electroweak signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few electroweak signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few electroweak signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few strong signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few strong signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few strong signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few strong signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few strong signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
Systematic uncertainties in the signal event yields at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. The uncertainty in the cross-section of the strong production is large due to the large effect from the PDF uncertainty.
Systematic uncertainties in the signal event yields at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. The uncertainty in the cross-section of the strong production is large due to the large effect from the PDF uncertainty.
Systematic uncertainties in the signal event yields at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. The uncertainty in the cross-section of the strong production is large due to the large effect from the PDF uncertainty.
Systematic uncertainties in the signal event yields at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. The uncertainty in the cross-section of the strong production is large due to the large effect from the PDF uncertainty.
Systematic uncertainties in the signal event yields at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. The uncertainty in the cross-section of the strong production is large due to the large effect from the PDF uncertainty.
Observed events, expected background for null signal, and expected signal yields for two benchmark models: electroweak channel with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) and strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. Also shown are the probability of a background-only experiment being more signal-like than observed ($p_0$) and the upper limit on the model-independent visible cross-section at 95\% CL. The uncertainty in the total background yield is different from the sum of uncertainties in quadrature due to anticorrelation between different backgrounds.
Observed events, expected background for null signal, and expected signal yields for two benchmark models: electroweak channel with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) and strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. Also shown are the probability of a background-only experiment being more signal-like than observed ($p_0$) and the upper limit on the model-independent visible cross-section at 95\% CL. The uncertainty in the total background yield is different from the sum of uncertainties in quadrature due to anti-correlation between different backgrounds.
Observed events, expected background for null signal, and expected signal yields for two benchmark models: electroweak channel with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) and strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. Also shown are the probability of a background-only experiment being more signal-like than observed ($p_0$) and the upper limit on the model-independent visible cross-section at 95\% CL. The uncertainty in the total background yield is different from the sum of uncertainties in quadrature due to anti-correlation between different backgrounds.
Observed events, expected background for null signal, and expected signal yields for two benchmark models: electroweak channel with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) and strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. Also shown are the probability of a background-only experiment being more signal-like than observed ($p_0$) and the upper limit on the model-independent visible cross-section at 95\% CL. The uncertainty in the total background yield is different from the sum of uncertainties in quadrature due to anti-correlation between different backgrounds.
Observed events, expected background for null signal, and expected signal yields for two benchmark models: electroweak channel with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) and strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. Also shown are the probability of a background-only experiment being more signal-like than observed ($p_0$) and the upper limit on the model-independent visible cross-section at 95\% CL. The uncertainty in the total background yield is different from the sum of uncertainties in quadrature due to anti-correlation between different backgrounds.
Effects of systematic uncertainties on the signal exclusion significance at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. Effects of uncertainties on the fake-tracklet background is smaller in the strong channel analysis because the estimated number of the fake-tracket background events is small.
Effects of systematic uncertainties on the signal exclusion significance at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. Effects of uncertainties on the fake-tracklet background is smaller in the strong channel analysis because the estimated number of the fake-tracklet background events is small.
Effects of systematic uncertainties on the signal exclusion significance at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. Effects of uncertainties on the fake-tracklet background is smaller in the strong channel analysis because the estimated number of the fake-tracklet background events is small.
Effects of systematic uncertainties on the signal exclusion significance at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. Effects of uncertainties on the fake-tracklet background is smaller in the strong channel analysis because the estimated number of the fake-tracklet background events is small.
Effects of systematic uncertainties on the signal exclusion significance at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. Effects of uncertainties on the fake-tracklet background is smaller in the strong channel analysis because the estimated number of the fake-tracklet background events is small.
Cross-section upper limits for the strong production, presented in unit of fb. Left-upper triangle region is unphysical because the wino mass is larger than the gluino mass.
Cross-section upper limits for the strong production, presented in unit of fb. Left-upper triangle region is unphysical because the wino mass is larger than the gluino mass.
Cross-section upper limits for the strong production, presented in unit of fb. Left-upper triangle region is unphysical because the wino mass is larger than the gluino mass.
Cross-section upper limits for the strong production, presented in unit of fb. Left-upper triangle region is unphysical because the wino mass is larger than the gluino mass.
Cross-section upper limits for the strong production, presented in unit of fb. Left-upper triangle region is unphysical because the wino mass is larger than the gluino mass.
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