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A search for dark matter in events with a displaced nonresonant muon pair and missing transverse momentum is presented. The analysis is performed using an integrated luminosity of 138 fb$^{-1}$ of proton-proton (pp) collision data at a center-of-mass energy of 13 TeV produced by the LHC in 2016-2018. No significant excess over the predicted backgrounds is observed. Upper limits are set on the product of the inelastic dark matter production cross section $\sigma$(pp $\to$ A' $\to$$\chi_1$$\chi_2$) and the decay branching fraction $\mathcal{B}$($\chi_2$$\to$$\chi_1 \mu^+ \mu^-$), where A' is a dark photon and $\chi_1$ and $\chi_2$ are states in the dark sector with near mass degeneracy. This is the first dedicated collider search for inelastic dark matter.
Definition of ABCD bins and yields in data, per match category. The predicted yield in the bin with the smallest backgrounds (bin D) is extracted from the simultaneous four-bin fit by assuming zero signal, which corresponds to $(\text{Obs. B} \times \text{Obs. C}) / (\text{Obs. A})$ in this limit.
Systematic uncertainties in the analysis. The jet uncertainties are larger in 2017 because of noise issues with the ECAL endcap. The tracking inefficiency in 2016 is caused by the unexpected saturation of photodiode signals in the tracker.
Simulated muon reconstruction efficiency of standard (blue squares) and displaced (red circles) reconstruction algorithms as a function of transverse vertex displacement $v_{xy}$. The two dashed vertical gray lines denote the ends of the fiducial tracker and muon detector regions, respectively.
Measured min-$d_{xy}$ distribution in the 2-match category, after requiring the $d_{xy}$ muon to pass the isolation requirement $I_{\mathrm{rel}}^{\mathrm{PF}} <0.25$ (i. e., the B and D bins of the ABCD plane). Overlaid with a red histogram is the background predicted from the region of the ABCD plane failing the same requirement (the A and C bins), as well as three signal benchmark hypotheses (as defined in the legends), assuming $\alpha_D = \alpha_{\mathrm{EM}}$ (the fine-structure constant). The red hatched bands correspond to the background prediction uncertainty. The last bin includes the overflow.
Two-dimensional exclusion surfaces for $\Delta = 0.1 \, m_1$ as a function of the DM mass $m_1$ and the signal strength $y$, with $m_{A'} = 3 \, m_1$. Filled histograms denote observed limits on $\sigma(\mathrm{pp} \to A' \to \chi_2 \chi_1) \, \mathcal{B}(\chi_2 \to \chi_1 \mu^+ \mu^-)$. Solid (dashed) curves denote the observed (expected) exclusion limits at 95% CL, with 68% CL uncertainty bands around the expectation. Regions above the curves are excluded, depending on the $\alpha_D$ hypothesis: $\alpha_{\mathrm{D}} = \alpha_{\mathrm{EM}}$ (dark blue) or 0.1 (light magenta).
Two-dimensional exclusion surfaces for $\Delta = 0.4 \, m_1$ as a function of the DM mass $m_1$ and the signal strength $y$, with $m_{A'} = 3 \, m_1$. Filled histograms denote observed limits on $\sigma(\mathrm{pp} \to A' \to \chi_2 \chi_1) \, \mathcal{B}(\chi_2 \to \chi_1 \mu^+ \mu^-)$. Solid (dashed) curves denote the observed (expected) exclusion limits at 95% CL, with 68% CL uncertainty bands around the expectation. Regions above the curves are excluded, depending on the $\alpha_D$ hypothesis: $\alpha_{\mathrm{D}} = \alpha_{\mathrm{EM}}$ (dark blue) or 0.1 (light magenta).
A search for the rare $\eta$$\to$$\mu^+\mu^-\mu^+\mu^-$ double-Dalitz decay is performed using a sample of proton-proton collisions, collected by the CMS experiment at the CERN LHC with high-rate muon triggers in 2017-2018 and corresponding to an integrated luminosity of 101 fb$^{-1}$. A signal having a statistical significance well in excess of 5 standard deviations is observed. Using the $\eta$$\to$$\mu^+ \mu^-$ decay as normalization, the branching fraction $\mathcal{B}(\eta$$\to$$\mu^+\mu^-\mu^+\mu^-)$ = [5.0 $\pm$ 0.8 (stat) $\pm$ 0.7 (syst) $\pm$ 0.7 ($\mathcal{B}_{2\mu}$)] $\times$ 10$^{-9}$ is measured, where the last term is the uncertainty in the normalization channel branching fraction. This work achieves an improved precision of over five orders of magnitude compared to previous results, leading to the first measurement of this branching fraction, which is found to agree with theoretical predictions.
The total efficiencies for the four-muon ($A_{4\mu}^{i,j}$, red and blue points) and two-muon ($A_{2\mu}^{i,j}$, orange and green points) decay channels, as functions of the generated meson's $p_{\mathrm{T}}$ and $y$, evaluated through MC simulation.
The total efficiencies for the four-muon ($A_{4\mu}^{i,j}$, red and blue points) and two-muon ($A_{2\mu}^{i,j}$, orange and green points) decay channels, as functions of the generated meson's $p_{\mathrm{T}}$ and $y$, evaluated through MC simulation.
Measured ratio of $\mathcal{B}_{4\mu}/\mathcal{B}_{2\mu}$
Measured ratio of $\mathcal{B}_{4\mu}/\mathcal{B}_{2\mu}$
Measured branching fraction $\mathcal{B}_{4\mu}$
Measured branching fraction $\mathcal{B}_{4\mu}$
A generic search is presented for the associated production of a Z boson or a photon with an additional unspecified massive particle X, pp $\to$ pp + Z/$\gamma$ + X, in proton-tagged events from proton-proton collisions at $\sqrt{s}$ = 13 TeV, recorded in 2017 with the CMS detector and the CMS-TOTEM precision proton spectrometer. The missing mass spectrum is analysed in the 600-1600 GeV range and a fit is performed to search for possible deviations from the background expectation. No significant excess in data with respect to the background predictions has been observed. Model-independent upper limits on the visible production cross section of pp $\to$ pp + Z/$\gamma$ + X are set.
Comparison of the $m_{miss}$ shapes for the simulated signal events within the fiducial region and those outside it, after including the effect of PU protons as describe in the text, for a generated $m_{X}$ mass of 1000 GeV. The distributions are shown for multi(+z)-multi(−z) proton reconstruction categories.
Comparison of the $m_{miss}$ shapes for the simulated signal events within the fiducial region and those outside it, after including the effect of PU protons as describe in the text, for a generated $m_{X}$ mass of 1000 GeV. The distributions are shown for multi(+z)-single(−z) proton reconstruction categories.
Comparison of the $m_{miss}$ shapes for the simulated signal events within the fiducial region and those outside it, after including the effect of PU protons as describe in the text, for a generated $m_{X}$ mass of 1000 GeV. The distributions are shown for single(+z)-multi(−z) proton reconstruction categories.
Comparison of the $m_{miss}$ shapes for the simulated signal events within the fiducial region and those outside it, after including the effect of PU protons as describe in the text, for a generated $m_{X}$ mass of 1000 GeV. The distributions are shown for single(+z)-single(−z) proton reconstruction categories.
Product of the acceptance times the combined reconstruction and identification efficiency, as a function of $m_{X}$ , for events generated inside the fiducial volume defined in Table 1. The curves shown panel display the different final states. The definition of the fiducial region and signal model used to estimate the acceptance is provided in the text.
Product of the acceptance times the combined reconstruction and identification efficiency, as a function of $m_{X}$ , for different proton reconstruction categories in the $Z \rightarrow \mu\mu $ analysis, and for events generated inside the fiducial volume defined in Table 1. The curves shown panel display the different final states. The definition of the fiducial region and signal model used to estimate the acceptance is provided in the text.
Distributions of the reconstructed proton $\xi$ in the negative arm from the proton mixing procedure with simulated MC events, are compared to data. The ee final states are shown.The ee events are displayed without the Z boson $p_T$ requirement.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.
Distributions of the reconstructed proton $\xi$ in the positive arm from the proton mixing procedure with simulated MC events, are compared to data. The ee final states are shown.The ee events are displayed without the Z boson $p_T$ requirement.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.
Distributions of the reconstructed di-proton rapidity from the proton mixing procedure with simulated MC events, are compared to data. The ee final states are shown.The ee events are displayed without the Z boson $p_T$ requirement.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.
Distributions of the reconstructed proton $\xi$ in the negative arm from the proton mixing procedure with simulated MC events, are compared to data. The $\mu\mu$ final states are shown.The $\mu\mu$ events are displayed without the Z boson $p_T$ requirement.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.
Distributions of the reconstructed proton $\xi$ in the positive arm from the proton mixing procedure with simulated MC events, are compared to data. The $\mu\mu$ final states are shown.The $\mu\mu$ events are displayed without the Z boson $p_T$ requirement.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.
Distributions of the reconstructed di-proton rapidity from the proton mixing procedure with simulated MC events, are compared to data. The $\mu\mu$ final states are shown.The $\mu\mu$ events are displayed without the Z boson $p_T$ requirement.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.
Distributions of the reconstructed proton $\xi$ in the negative arm from the proton mixing procedure with simulated MC events, are compared to data. The $\gamma$ final states are shown.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.
Distributions of the reconstructed proton $\xi$ in the positive arm from the proton mixing procedure with simulated MC events, are compared to data. The $\gamma$ final states are shown.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.
Distributions of the reconstructed di-proton rapidity from the proton mixing procedure with simulated MC events, are compared to data. The $\gamma$ final states are shown.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.
Validation of the background modelling method, using the $e\mu$ control sample. Selected $e\mu$ events are mixed with protons from $Z\rightarrow \mu \mu$ events with $p_{T}(Z)<10$ GeV to simulate the combinatorial background shape, while the data points are unaltered $e\mu$ events. The proton $\xi$ distribution for the positive CT-PPS arm is shown.
Validation of the background modelling method, using the $e\mu$ control sample. Selected $e\mu$ events are mixed with protons from $Z\rightarrow \mu \mu$ events with $p_{T}(Z)<10$ GeV to simulate the combinatorial background shape, while the data points are unaltered $e\mu$ events. The proton $\xi$ distribution for the negative CT-PPS arm is shown.
Validation of the background modelling method, using the $e\mu$ control sample. Selected $e\mu$ events are mixed with protons from $Z\rightarrow \mu \mu$ events with $p_{T}(Z)<10$ GeV to simulate the combinatorial background shape, while the data points are unaltered $e\mu$ events. The di-proton invariant mass is shown.
Validation of the background modelling method, using the $e\mu$ control sample. Selected $e\mu$ events are mixed with protons from $Z\rightarrow \mu \mu$ events with $p_{T}(Z)<10$ GeV to simulate the combinatorial background shape, while the data points are unaltered $e\mu$ events. The $m_{miss}$ is shown.
$m_{miss}$ distributions in the $pp\rightarrow ppZeeX$, with the protons reconstructed with the multi(+z)-multi(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.
$m_{miss}$ distributions in the $pp\rightarrow ppZeeX$, with the protons reconstructed with the multi(+z)-single(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.
$m_{miss}$ distributions in the $pp\rightarrow ppZeeX$, with the protons reconstructed with the single(+z)-multi(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.
$m_{miss}$ distributions in the $pp\rightarrow ppZeeX$, with the protons reconstructed with the single(+z)-single(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.
$m_{miss}$ distributions in the $pp\rightarrow ppZ\mu\mu X$, with the protons reconstructed with the multi(+z)-multi(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.
$m_{miss}$ distributions in the $pp\rightarrow ppZ\mu\mu X$, with the protons reconstructed with the multi(+z)-single(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.
$m_{miss}$ distributions in the $pp\rightarrow ppZ\mu\mu X$, with the protons reconstructed with the single(+z)-multi(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.
$m_{miss}$ distributions in the $pp\rightarrow ppZ\mu\mu X$, with the protons reconstructed with the single(+z)-single(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.
$m_{miss}$ distributions in the $pp\rightarrow pp\gamma X$, with the protons reconstructed with the multi(+z)-multi(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 10 pb.
$m_{miss}$ distributions in the $pp\rightarrow pp\gamma X$, with the protons reconstructed with the multi(+z)-single(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 10 pb.
$m_{miss}$ distributions in the $pp\rightarrow pp\gamma X$, with the protons reconstructed with the single(+z)-multi(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 10 pb.
$m_{miss}$ distributions in the $pp\rightarrow pp\gamma X$, with the protons reconstructed with the single(+z)-single(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 10 pb.
Upper limits on the $pp\rightarrow ppZ/\gamma X$ cross section at 95% CL, as a function of $m_X$. The 68 and 95% central intervals of the expected limits are represented by the green and yellow bands, respectively, while the observed limit is superimposed as a curve. The plot corresponds to the $Z\rightarrow ee$ analysis.
Upper limits on the $pp\rightarrow ppZ/\gamma X$ cross section at 95% CL, as a function of $m_X$. The 68 and 95% central intervals of the expected limits are represented by the green and yellow bands, respectively, while the observed limit is superimposed as a curve. The plot corresponds to the $Z\rightarrow \mu\mu$ analysis.
Upper limits on the $pp\rightarrow ppZ/\gamma X$ cross section at 95% CL, as a function of $m_X$. The 68 and 95% central intervals of the expected limits are represented by the green and yellow bands, respectively, while the observed limit is superimposed as a curve. The plot corresponds to the $Z$ analysis.
Upper limits on the $pp\rightarrow ppZ/\gamma X$ cross section at 95% CL, as a function of $m_X$. The 68 and 95% central intervals of the expected limits are represented by the green and yellow bands, respectively, while the observed limit is superimposed as a curve. The plot corresponds to the $\gamma$ analysis.
A search for physics beyond the standard model (SM) in final states with an electron or muon and missing transverse momentum is presented. The analysis uses data from proton-proton collisions at a centre-of-mass energy of 13 TeV, collected with the CMS detector at the LHC in 2016–2018 and corresponding to an integrated luminosity of 138 fb−1. No significant deviation from the SM prediction is observed. Model-independent limits are set on the production cross section of W’ bosons decaying into lepton-plus-neutrino final states. Within the framework of the sequential standard model, with the combined results from the electron and muon decay channels a W’ boson with mass less than 5.7 TeV is excluded at 95% confidence level. Results on a SM precision test, the determination of the oblique electroweak W parameter, are presented using LHC data for the first time. These results together with those from the direct W’ resonance search are used to extend existing constraints on composite Higgs scenarios. This is the first experimental exclusion on compositeness parameters using results from LHC data other than Higgs boson measurements.
Product of signal selection efficiency and acceptance as a function of resonance mass for a SSM WPRIME decaying to electron or muon plus neutrino.It is calculated as the number of WPRIME signal events passing the selection process over the number of generated events. In the selection process there is no requirement on a minimum $M_T$ applied. The SSM WPRIME signal samples have been generated with PYTHIA 8.2. More details in paper
Observed and expected number of events in the electron and muon channels, collected during three years (2016, 2017, and 2018), for selected values of $M_T$ thresholds. The statistical and systematic uncertainties are added in quadrature providing the total uncertainty.
Observed and expected-from-SM number of events in the electron and muon channels, collected during three years (2016, 2017, and 2018), for two steps in the selection procedure: 1) one high-quality high-$p_T$ lepton with $p_T$ > 240(53) GeV for E(MU), and no other lepton in the event, with $M_T$ > 400(120) GeV for events with E(MU). 2) additionally the ratio of the lepton $p_T$ and $p_T^{miss}$ must be 0.4 < $p_T$/$p_T^{miss}$ < 1.5 and the azimuthal angular difference between them, ${\Delta\phi}$> 2.5. The signal yield for an SSM WPRIME of mass 5.6 TeV is also included.
Electron $p_{T}$ distribution using 2016-2018 data sets. The complete set of selection criteria were applied. Two examples of SSM WPRIME boson signal samples with masses of 3.8 and 5.6 TeV are shown. The lower panel shows the ratio of data to SM prediction, and the shaded band represents the systematic uncertainties.
$p_{T}^{miss}$ distribution in the electron channel using 2016-2018 data sets. The complete set of selection criteria were applied. Two examples of SSM WPRIME boson signal samples with masses of 3.8 and 5.6 TeV are shown. The lower panel shows the ratio of data to SM prediction, and the shaded band represents the systematic uncertainties.
Muon $p_T$ distribution using 2016-2018 data sets. The complete set of selection criteria were applied. Two examples of SSM WPRIME boson signal samples with masses of 3.8 and 5.6 TeV are shown. The lower panel shows the ratio of data to SM prediction, and the shaded band represents the systematic uncertainties.
$p_T^{miss}$ distribution in the muon channel using 2016-2018 data sets. The complete set of selection criteria were applied. Two examples of SSM WPRIME boson signal samples with masses of 3.8 and 5.6 TeV are shown. The lower panel shows the ratio of data to SM prediction, and the shaded band represents the systematic uncertainties.
$M_T$ distribution for the E+INVISIBLE system using 2016-2018 data sets. The complete set of selection criteria were applied. Two examples of SSM WPRIME boson signal samples with masses of 3.8 and 5.6 TeV are shown. The lower panel shows the ratio of data to SM prediction, and the shaded band represents the systematic uncertainties.
$M_T$ distribution for the MU+INVISIBLE system using 2016-2018 data sets. The complete set of selection criteria were applied. Two examples of SSM WPRIME boson signal samples with masses of 3.8 and 5.6 TeV are shown. The lower panel shows the ratio of data to SM prediction, and the shaded band represents the systematic uncertainties.
Theoretical prediction for the production and decay cross-section of SSM WPRIME bosons (W --> LEPTON + NU) as a function of the WPRIME mass, for the range 200-6400 GeV and inclusive in phase-space (no cuts). The uncertainty shown covers PDF and ALPHAS uncertainties. These theoretical predictions are obtained with PYTHIA (LO) and corrected to NNLO in QCD using FEWZ program.
Observed (solid line) and expected (dashed line) upper limits at 95% CL on the product of WPRIME cross-section production and BF(WPRIME --> LEPTON + NU) for an SSM WPRIME boson, as a function of the boson mass, for the electron decay channel. The shaded bands represent the one (green) and two (yellow) standard deviation uncertainty bands for the expected limits. The theoretical predictions for the SSM at NNLO precision in QCD are shown with narrow gray bands corresponding to the PDF and ALPHAS uncertainties.
Observed (solid line) and expected (dashed line) upper limits at 95% CL on the product of WPRIME cross-section production and BF(WPRIME --> LEPTON + NU) for an SSM WPRIME boson, as a function of the boson mass, for the muon decay channel. The shaded bands represent the one (green) and two (yellow) standard deviation uncertainty bands for the expected limits. The theoretical predictions for the SSM at NNLO precision in QCD are shown with narrow gray bands corresponding to the PDF and ALPHAS uncertainties.
Observed (solid line) and expected (dashed line) upper limits at 95% CL on the product of WPRIME cross-section production and BF(WPRIME --> LEPTON + NU) for an SSM WPRIME boson, as a function of the boson mass, for the combined electron and muon decay channels. The shaded bands represent the one (green) and two (yellow) standard deviation uncertainty bands for the expected limits. The theoretical predictions for the SSM at NNLO precision in QCD are shown with narrow gray bands corresponding to the PDF and ALPHAS uncertainties.
The 95% CL observed (solid line) and expected (dashed line) model independent cross section upper limits as function of the $MT_{min}$ threshold, for the electron decay channel. The shaded bands represent the one (green) and two (yellow) standard deviation uncertainty bands for the expected limits.
The 95% CL observed (solid line) and expected (dashed line) model independent cross section upper limits as function of the $MT_{min}$ threshold, for the muon decay channel. The shaded bands represent the one (green) and two (yellow) standard deviation uncertainty bands for the expected limits.
The 95% CL observed (solid line) and expected (dashed line) model independent cross section upper limits as function of the $MT_{min}$ threshold, for the combined electron and muon decay channels. The shaded bands represent the one (green) and two (yellow) standard deviation uncertainty bands for the expected limits.
Observed (solid line) and expected (dashed line) upper limits at 95% CL on the coupling strength ratio, gWprime/gW as a function of the mass of the WPRIME boson, for the electron channel. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The area above the limit curve is excluded. The dotted line represents the case of SSM coupling, gWprime, being equal to gW, the SM coupling.
Observed (solid line) and expected (dashed line) upper limits at 95% CL on the coupling strength ratio, gWprime/gW, as a function of the mass of the WPRIME boson, for the muon channel. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The area above the limit curve is excluded. The dotted line represents the case of SSM coupling, gWprime , being equal to gW, the SM coupling.
Exclusion limits in the 2D plane (1/R, $\mu$) for the split-UED interpretation for the n = 2 case, for the electron channel for the 2016-2018 data sets. R is the radius of the additional spatial dimension and $\mu$ the bulk mass for the fermion field in five dimensions. The expected limit is depicted as a black dashed line. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The experimentally excluded region is the entire area to the left of the solid black line.
Exclusion limits in the 2D plane (1/R, $\mu$) for the split-UED interpretation for the n = 2 case, for the muon channel for the 2016-2018 data sets. R is the radius of the additional spatial dimension and $\mu$ the bulk mass for the fermion field in five dimensions. The expected limit is depicted as a black dashed line. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The experimentally excluded region is the entire area to the left of the solid black line.
Exclusion limits in the 2D plane (1/R, $\mu$) for the split-UED interpretation for the n = 2 case, for the combined electron and muon channels for the 2016-2018 data sets. R is the radius of the additional spatial dimension and $\mu$ the bulk mass for the fermion field in five dimensions. The expected limit is depicted as a black dashed line. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The experimentally excluded region is the entire area to the left of the solid black line.
Observed (solid line) and expected (dashed line) upper limits at 95% CL on the ${\lambda}_{231}$ coupling in the RPV SUSY model with a STAU mediator, as a function of the mass of STAU, for the electron channel and for the production coupling, ${\lambda}^{'}_{3ij}$=0.5 . The couplings ${\lambda}^{'}_{3ij}$, ${\lambda}_{231}$, and ${\lambda}_{132}$ are defined in Fig. 1. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The area above the limit curve is excluded. Limits for other values of ${\lambda}^{'}_{3ij}$ are obtained multiplying the ones shown by the ratio ${\lambda}^{'}_{3ij}$/0.5
Observed (solid line) and expected (dashed line) upper limits at 95% CL on the ${\lambda}_{132}$ coupling in the RPV SUSY model with a stau mediator, as a function of the mass of the stau, for the muon channel and for the production coupling, ${\lambda}^{'}_{3ij}$ = 0.5 . The couplings ${\lambda}^{'}_{3ij}$, ${\lambda}_{231}$, and ${\lambda}_{132}$ are defined in Fig. 1. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The area above the limit curve is excluded. Limits for other values of ${\lambda}^{'}_{3ij}$ are obtained multiplying these ones by the ratio ${\lambda}^{'}_{3ij}$/0.5
Region in the oblique (W,Y) parameter phase space allowed by the current analysis at 95% CL. The combination of the electron and muon channel distributions from the 2017 and 2018 data sets at sqrt(s) = 13 TeV is used, having 101 fb-1 of luminosity.
Negative Log-Likelihood for the determination of the oblique W parameter, for the combination of the electron and muon channel and for 2017 and 2018 data sets (L=101 fb-1) at sqrt(s) = 13 TeV.
Total background estimate and observed data in all bins used in the limit calculation for the SSM WPRIME limits. The total event sample is split into the three years of data taking and the two lepton flavors.The distributions being shown are $M_T$ ones. The associated integrated luminosities for each year are of 35.9, 41.5, and 59.4 fb$̣^{-1}. The mass bins are numbered in ascending order.
A search for new heavy resonances decaying to WW, WZ, ZZ, WH, or ZH boson pairs in the all-jets final state is presented. The analysis is based on proton-proton collision data recorded by the CMS detector in 2016-2018 at a centre-of-mass energy of 13 TeV at the CERN LHC, corresponding to an integrated luminosity of 138 fb$^{-1}$. The search is sensitive to resonances with masses between 1.3 and 6 TeV, decaying to bosons that are highly Lorentz-boosted such that each of the bosons forms a single large-radius jet. Machine learning techniques are employed to identify such jets. No significant excess over the estimated standard model background is observed. A maximum local significance of 3.6 standard deviations, corresponding to a global significance of 2.3 standard deviations, is observed at masses of 2.1 and 2.9 TeV. In a heavy vector triplet model, spin-1 Z' and W' resonances with masses below 4.8 TeV are excluded at the 95% confidence level (CL). These limits are the most stringent to date. In a bulk graviton model, spin-2 gravitons and spin-0 radions with masses below 1.4 and 2.7 TeV, respectively, are excluded at 95% CL. Production of heavy resonances through vector boson fusion is constrained with upper cross section limits at 95% CL as low as 0.1 fb.
Observed and expected 95% CL upper limits on the product of the production cross section ($\sigma$) and the branching fraction, obtained after combining all categories with 138 $\mathrm{fb}^{−1}$ of data at $\sqrt{s}$ = 13 TeV for R to VV signal.
Observed and expected 95% CL upper limits on the product of the production cross section ($\sigma$) and the branching fraction, obtained after combining all categories with 138 $\mathrm{fb}^{−1}$ of data at $\sqrt{s}$ = 13 TeV for $\mathrm{G}_\mathrm{bulk}$ to $VV$ signal.
Observed and expected 95% CL upper limits on the product of the production cross section ($\sigma$) and the branching fraction, obtained after combining all categories with 138 $\mathrm{fb}^{−1}$ of data at $\sqrt{s}$ = 13 TeV for $\mathrm{V'}$ to $VV$ + $VH$ signal in HVT model B.
Observed and expected 95% CL upper limits on the product of the production cross section ($\sigma$) and the branching fraction, obtained after combining all categories with 138 $\mathrm{fb}^{−1}$ of data at $\sqrt{s}$ = 13 TeV for $\mathrm{V'}$ to $VV$ + $VH$ signal in HVT model C.
Total signal efficiency including all event categories as a function of the resonance mass $M_X$ for all DY/ggF signal models under consideration. The estimates from MC simulation (markers) are interpolated with a functional form (lines).
Total signal efficiency including all event categories as a function of the resonance mass $M_X$ for all VBF signal models under consideration. The estimates from MC simulation (markers) are interpolated with a functional form (lines).
A search is reported for pairs of light Higgs bosons (H$_1$) produced in supersymmetric cascade decays in final states with small missing transverse momentum. A data set of LHC pp collisions collected with the CMS detector at $\sqrt{s}$ = 13 TeV and corresponding to an integrated luminosity of 138 fb$^{-1}$ is used. The search targets events where both H$_1$ bosons decay into $\mathrm{b\bar{b}}$ pairs that are reconstructed as large-radius jets using substructure techniques. No evidence is found for an excess of events beyond the background expectations of the standard model (SM). Results from the search are interpreted in the next-to-minimal supersymmetric extension of the SM, where a "singlino" of small mass leads to squark and gluino cascade decays that can predominantly end in a highly Lorentz-boosted singlet-like H$_1$ and a singlino-like neutralino of small transverse momentum. Upper limits are set on the product of the squark or gluino pair production cross section and the square of the $\mathrm{b\bar{b}}$ branching fraction of the H$_1$ in a benchmark model containing almost mass-degenerate gluinos and light-flavour squarks. Under the assumption of an SM-like H$_1$$\to$$\mathrm{b\bar{b}}$ branching fraction, H$_1$ bosons with masses in the range 40-120 GeV arising from the decays of squarks or gluinos with a mass of 1200 to 2500 GeV are excluded at 95% confidence level.
Reference acceptance times efficiency values for the kinematic selection and $H_T>3500\;\mathrm{GeV}$ requirements ($A_{\mathrm{kin}}$) for the benchmark signal model with different values of $m_{\mathrm{SUSY}}$. These values are independent of $m_{\mathrm{H_1}}$ within 2% in the range $30 \le m_{\mathrm{H_1}} \le 125\;\mathrm{GeV}$.
Upper limits at 95% CL on $\sigma\times\mathcal{B}^2(\mathrm{H}_1\rightarrow b\bar{b}) \times A_{\mathrm{kin}}$ as a function of $m_{\mathrm{H_1}}$. The results are independent of $m_{\mathrm{SUSY}}$ within 10% in the range $1600<m_{\mathrm{SUSY}}<2800\;\mathrm{GeV}$.
Upper limits at 95% CL on $\sigma\times\mathcal{B}^2(\mathrm{H}_1\rightarrow b\bar{b})$ as a function of $m_{\mathrm{H_1}}$ for $m_{\mathrm{SUSY}}=1200\;\mathrm{GeV}$.
Upper limits at 95% CL on $\sigma\times\mathcal{B}^2(\mathrm{H}_1\rightarrow b\bar{b})$ as a function of $m_{\mathrm{H_1}}$ for $m_{\mathrm{SUSY}}=1600\;\mathrm{GeV}$.
Upper limits at 95% CL on $\sigma\times\mathcal{B}^2(\mathrm{H}_1\rightarrow b\bar{b})$ as a function of $m_{\mathrm{H_1}}$ for $m_{\mathrm{SUSY}}=2000\;\mathrm{GeV}$.
Upper limits at 95% CL on $\sigma\times\mathcal{B}^2(\mathrm{H}_1\rightarrow b\bar{b})$ as a function of $m_{\mathrm{H_1}}$ for $m_{\mathrm{SUSY}}=2200\;\mathrm{GeV}$.
Upper limits at 95% CL on $\sigma\times\mathcal{B}^2(\mathrm{H}_1\rightarrow b\bar{b})$ as a function of $m_{\mathrm{H_1}}$ for $m_{\mathrm{SUSY}}=2400\;\mathrm{GeV}$.
Upper limits at 95% CL on $\sigma\times\mathcal{B}^2(\mathrm{H}_1\rightarrow b\bar{b})$ as a function of $m_{\mathrm{H_1}}$ for $m_{\mathrm{SUSY}}=2600\;\mathrm{GeV}$.
Upper limits at 95% CL on $\sigma\times\mathcal{B}^2(\mathrm{H}_1\rightarrow b\bar{b})$ as a function of $m_{\mathrm{H_1}}$ for $m_{\mathrm{SUSY}}=2800\;\mathrm{GeV}$.
A search is presented for single production of a vector-like T quark with charge 2/3 $e$, in the decay channel featuring a top quark and a Z boson, with the top quark decaying hadronically and the Z boson decaying to neutrinos. The search uses data collected by the CMS experiment in proton-proton collisions at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 137 fb$^{-1}$ recorded at the CERN LHC in 2016-2018. The search is sensitive to a T quark mass between 0.6 and 1.8 TeV with decay widths ranging from negligibly small up to 30% of the T quark mass. Reconstruction strategies for the top quark are based on the degree of Lorentz boosting of its final state. At 95% confidence level, the upper limit on the product of the cross section and branching fraction for a T quark of small decay width varies between 15 and 602 fb, depending on its mass. For a T quark with decay widths between 10 and 30% of its mass, this upper limit ranges between 16 and 836 fb. For most of the studied range, the results provide the best limits to date. This is the first search for single T quark production based on the full Run 2 data set of the LHC.
Product of efficiency and acceptance of the event selection for T signal events as a function of the particle mass $m_\mathrm{T}$ and width $\Gamma$ for the different hypotheses considered.
Product of efficiency and acceptance of the event selection for T signal events as a function of the particle mass $m_\mathrm{T}$ and width $\Gamma$ for the different hypotheses considered.
Product of efficiency and acceptance of the event selection for T signal events as a function of the particle mass $m_\mathrm{T}$ and width $\Gamma$ for the different hypotheses considered.
Product of efficiency and acceptance of the event selection for T signal events as a function of the particle mass $m_\mathrm{T}$ and width $\Gamma$ for the different hypotheses considered.
Product of efficiency and acceptance of the event selection for T signal events as a function of the particle mass $m_\mathrm{T}$ and width $\Gamma$ for the different hypotheses considered.
Product of efficiency and acceptance of the event selection for T signal events as a function of the particle mass $m_\mathrm{T}$ and width $\Gamma$ for the different hypotheses considered.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the merged validation region with 0 forward jets. Data are compared to backgrounds are after the data-driven extraction is performed.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the merged validation region with at least 1 forward jet. Data are compared to backgrounds are after the data-driven extraction is performed.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the merged validation region with 0 forward jets. Data are compared to backgrounds are after the data-driven extraction is performed.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the merged validation region with at least 1 forward jet. Data are compared to backgrounds are after the data-driven extraction is performed.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the merged validation region with 0 forward jets. Data are compared to backgrounds are after the data-driven extraction is performed.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the merged validation region with at least 1 forward jet. Data are compared to backgrounds are after the data-driven extraction is performed.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the resolved validation region with 0 forward jets. Data are compared to backgrounds are after the data-driven extraction is performed.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the resolved validation region with at least 1 forward jet. Data are compared to backgrounds are after the data-driven extraction is performed.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the resolved validation region with 0 forward jets. Data are compared to backgrounds are after the data-driven extraction is performed.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the resolved validation region with at least 1 forward jet. Data are compared to backgrounds are after the data-driven extraction is performed.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the resolved validation region with 0 forward jets. Data are compared to backgrounds are after the data-driven extraction is performed.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the resolved validation region with at least 1 forward jet. Data are compared to backgrounds are after the data-driven extraction is performed.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the merged region with 0 forward jets. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the merged region with at least 1 forward jet. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the merged region with 0 forward jets. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the merged region with at least 1 forward jet. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the merged region with 0 forward jets. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the merged region with at least 1 forward jet. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the partially merged region with 0 forward jets. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the partially merged region with at least 1 forward jet. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the partially merged region with 0 forward jets. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the partially merged region with at least 1 forward jet. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the partially merged region with 0 forward jets. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the partially merged region with at least 1 forward jet. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the resolved region with 0 forward jets. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the resolved region with at least 1 forward jet. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the resolved region with 0 forward jets. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the resolved region with at least 1 forward jet. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the resolved region with 0 forward jets. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the resolved region with at least 1 forward jet. Data are compared to backgrounds obtained post-fit.
Observed and expected 95% CL upper limits on the product of the cross section and branching fraction of a T decaying to a hadronic top quark and a Z boson to neutrinos as a function of the T mass, for a T with a width of 0.01 $ imes$ its mass.
Observed and expected 95% CL upper limits on the product of the cross section and branching fraction of a T decaying to a hadronic top quark and a Z boson to neutrinos as a function of the T mass, for a T with a width of 0.1 $ imes$ its mass.
Observed and expected 95% CL upper limits on the product of the cross section and branching fraction of a T decaying to a hadronic top quark and a Z boson to neutrinos as a function of the T mass, for a T with a width of 0.2 $ imes$ its mass.
Observed and expected 95% CL upper limits on the product of the cross section and branching fraction of a T decaying to a hadronic top quark and a Z boson to neutrinos as a function of the T mass, for a T with a width of 0.3 $ imes$ its mass.
Model independent observed 95% CL upper limits on the product of the cross section and branching fraction of a T decaying to a top quark and a Z boson as a function of the T mass and width.
Singlet model 95% CL excluded values of the product of the cross section and branching fraction for a T decaying to a top quark and a Z boson.
The first collider search for dark matter arising from a strongly coupled hidden sector is presented and uses a data sample corresponding to 138 fb$^{-1}$, collected with the CMS detector at the CERN LHC, at $\sqrt{s} =$ 13 TeV. The hidden sector is hypothesized to couple to the standard model (SM) via a heavy leptophobic Z' mediator produced as a resonance in proton-proton collisions. The mediator decay results in two "semivisible" jets, containing both visible matter and invisible dark matter. The final state therefore includes moderate missing energy aligned with one of the jets, a signature ignored by most dark matter searches. No structure in the dijet transverse mass spectra compatible with the signal is observed. Assuming the Z' has a universal coupling of 0.25 to the SM quarks, an inclusive search, relevant to any model that exhibits this kinematic behavior, excludes mediator masses of 1.5-4.0 TeV at 95% confidence level, depending on the other signal model parameters. To enhance the sensitivity of the search for this particular class of hidden sector models, a boosted decision tree (BDT) is trained using jet substructure variables to distinguish between semivisible jets and SM jets from background processes. When the BDT is employed to identify each jet in the dijet system as semivisible, the mediator mass exclusion increases to 5.1 TeV, for wider ranges of the other signal model parameters. These limits exclude a wide range of strongly coupled hidden sector models for the first time.
The normalized distribution of the characteristic variable $R_{\text{T}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the characteristic variable $R_{\text{T}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the characteristic variable $R_{\text{T}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the characteristic variable $\Delta\phi_{\text{min}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the characteristic variable $\Delta\phi_{\text{min}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the characteristic variable $\Delta\phi_{\text{min}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $m_{\text{SD}}$ for the two highest $p_{\text{T}}$ jets from the simulated SM backgrounds and several signal models. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $m_{\text{SD}}$ for the two highest $p_{\text{T}}$ jets from the simulated SM backgrounds and several signal models. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $m_{\text{SD}}$ for the two highest $p_{\text{T}}$ jets from the simulated SM backgrounds and several signal models. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $D_{p_{\text{T}}}$ for the two highest $p_{\text{T}}$ jets from the simulated SM backgrounds and several signal models. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $D_{p_{\text{T}}}$ for the two highest $p_{\text{T}}$ jets from the simulated SM backgrounds and several signal models. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $D_{p_{\text{T}}}$ for the two highest $p_{\text{T}}$ jets from the simulated SM backgrounds and several signal models. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized BDT discriminator distribution for the two highest $p_{\text{T}}$ jets from the simulated SM backgrounds and several signal models.
The normalized BDT discriminator distribution for the two highest $p_{\text{T}}$ jets from the simulated SM backgrounds and several signal models.
The normalized BDT discriminator distribution for the two highest $p_{\text{T}}$ jets from the simulated SM backgrounds and several signal models.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The $m_{\text{T}}$ distribution for the high-$R_{\text{T}}$ signal region, comparing the observed data to the background prediction from the analytic fit ($g_{3}(x) = \exp(p_{1}x)x^{p_{2}(1+p_{3}\ln(x))}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the high-$R_{\text{T}}$ signal region, comparing the observed data to the background prediction from the analytic fit ($g_{3}(x) = \exp(p_{1}x)x^{p_{2}(1+p_{3}\ln(x))}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the high-$R_{\text{T}}$ signal region, comparing the observed data to the background prediction from the analytic fit ($g_{3}(x) = \exp(p_{1}x)x^{p_{2}(1+p_{3}\ln(x))}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the low-$R_{\text{T}}$ signal region, comparing the observed data to the background prediction from the analytic fit ($g_{2}(x) = \exp(p_{1}x)x^{p_{2}}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the low-$R_{\text{T}}$ signal region, comparing the observed data to the background prediction from the analytic fit ($g_{2}(x) = \exp(p_{1}x)x^{p_{2}}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the low-$R_{\text{T}}$ signal region, comparing the observed data to the background prediction from the analytic fit ($g_{2}(x) = \exp(p_{1}x)x^{p_{2}}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the high-SVJ2 signal region, comparing the observed data to the background prediction from the analytic fit ($g_{2}(x) = \exp(p_{1}x)x^{p_{2}}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the high-SVJ2 signal region, comparing the observed data to the background prediction from the analytic fit ($g_{2}(x) = \exp(p_{1}x)x^{p_{2}}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the high-SVJ2 signal region, comparing the observed data to the background prediction from the analytic fit ($g_{2}(x) = \exp(p_{1}x)x^{p_{2}}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the low-SVJ2 signal region, comparing the observed data to the background prediction from the analytic fit ($g_{2}(x) = \exp(p_{1}x)x^{p_{2}}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the low-SVJ2 signal region, comparing the observed data to the background prediction from the analytic fit ($g_{2}(x) = \exp(p_{1}x)x^{p_{2}}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the low-SVJ2 signal region, comparing the observed data to the background prediction from the analytic fit ($g_{2}(x) = \exp(p_{1}x)x^{p_{2}}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the dark hadron mass.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the dark hadron mass.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the dark hadron mass.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the invisible fraction.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the invisible fraction.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the invisible fraction.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the dark hadron mass.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the dark hadron mass.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the dark hadron mass.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the invisible fraction.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the invisible fraction.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the invisible fraction.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The 95% CL upper limits on the product of the cross section and branching fraction from the inclusive search for the $\alpha_{\text{dark}}$ variations.
The 95% CL upper limits on the product of the cross section and branching fraction from the inclusive search for the $\alpha_{\text{dark}}$ variations.
The 95% CL upper limits on the product of the cross section and branching fraction from the inclusive search for the $\alpha_{\text{dark}}$ variations.
The 95% CL upper limits on the product of the cross section and branching fraction from the BDT-based search for the $\alpha_{\text{dark}}$ variations.
The 95% CL upper limits on the product of the cross section and branching fraction from the BDT-based search for the $\alpha_{\text{dark}}$ variations.
The 95% CL upper limits on the product of the cross section and branching fraction from the BDT-based search for the $\alpha_{\text{dark}}$ variations.
The three two-dimensional signal model parameter scans.
The three two-dimensional signal model parameter scans.
The three two-dimensional signal model parameter scans.
Metrics representing the performance of the BDT for the benchmark signal model ($m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$), compared to each of the major SM background processes.
Metrics representing the performance of the BDT for the benchmark signal model ($m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$), compared to each of the major SM background processes.
Metrics representing the performance of the BDT for the benchmark signal model ($m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$), compared to each of the major SM background processes.
The range of effects on the signal yield for each systematic uncertainty and the total. Values less than 0.01% are rounded to 0.0%.
The range of effects on the signal yield for each systematic uncertainty and the total. Values less than 0.01% are rounded to 0.0%.
The range of effects on the signal yield for each systematic uncertainty and the total. Values less than 0.01% are rounded to 0.0%.
The normalized distribution of the variable $m_{\text{T}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $m_{\text{T}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $m_{\text{T}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $\Delta\eta(\text{J}_{1},\text{J}_{2})$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $\Delta\eta(\text{J}_{1},\text{J}_{2})$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $\Delta\eta(\text{J}_{1},\text{J}_{2})$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $p_{\text{T}}^{\text{miss}}$ for the simulated SM backgrounds and several signal models. The $R_{\text{T}}$ requirement is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $p_{\text{T}}^{\text{miss}}$ for the simulated SM backgrounds and several signal models. The $R_{\text{T}}$ requirement is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $p_{\text{T}}^{\text{miss}}$ for the simulated SM backgrounds and several signal models. The $R_{\text{T}}$ requirement is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $N_{\text{e}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $N_{\text{e}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $N_{\text{e}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $N_{\mu}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $N_{\mu}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $N_{\mu}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of $\Delta\eta(\text{J}_{1},\text{J}_{2})$ vs. $R_{\text{T}}$ for the simulated QCD background. The preselection requirements on both variables are omitted, but all other preselection requirements are applied.
The normalized distribution of $\Delta\eta(\text{J}_{1},\text{J}_{2})$ vs. $R_{\text{T}}$ for the simulated QCD background. The preselection requirements on both variables are omitted, but all other preselection requirements are applied.
The normalized distribution of $\Delta\eta(\text{J}_{1},\text{J}_{2})$ vs. $R_{\text{T}}$ for the simulated QCD background. The preselection requirements on both variables are omitted, but all other preselection requirements are applied.
The normalized distribution of $p_{\text{T}}^{\text{miss}}$ vs. $m_{\text{T}}$ for the simulated QCD background. All selection requirements are omitted, except for the requirement of two high-$p_{\text{T}}$ wide jets.
The normalized distribution of $p_{\text{T}}^{\text{miss}}$ vs. $m_{\text{T}}$ for the simulated QCD background. All selection requirements are omitted, except for the requirement of two high-$p_{\text{T}}$ wide jets.
The normalized distribution of $p_{\text{T}}^{\text{miss}}$ vs. $m_{\text{T}}$ for the simulated QCD background. All selection requirements are omitted, except for the requirement of two high-$p_{\text{T}}$ wide jets.
The normalized distribution of $R_{\text{T}}$ vs. $m_{\text{T}}$ for the simulated QCD background. All selection requirements are omitted, except for the requirement of two high-$p_{\text{T}}$ wide jets.
The normalized distribution of $R_{\text{T}}$ vs. $m_{\text{T}}$ for the simulated QCD background. All selection requirements are omitted, except for the requirement of two high-$p_{\text{T}}$ wide jets.
The normalized distribution of $R_{\text{T}}$ vs. $m_{\text{T}}$ for the simulated QCD background. All selection requirements are omitted, except for the requirement of two high-$p_{\text{T}}$ wide jets.
The normalized distributions of the BDT input variable $\tau_{21}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\tau_{21}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\tau_{21}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\tau_{32}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\tau_{32}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\tau_{32}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $N_{2}^{(1)}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $N_{2}^{(1)}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $N_{2}^{(1)}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $N_{3}^{(1)}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $N_{3}^{(1)}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $N_{3}^{(1)}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $g_{\text{jet}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $g_{\text{jet}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $g_{\text{jet}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\sigma_{\text{major}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\sigma_{\text{major}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\sigma_{\text{major}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\sigma_{\text{minor}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\sigma_{\text{minor}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\sigma_{\text{minor}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\Delta\phi(\vec{J},\vec{p}_{\text{T}}^{\text{miss}})$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\Delta\phi(\vec{J},\vec{p}_{\text{T}}^{\text{miss}})$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\Delta\phi(\vec{J},\vec{p}_{\text{T}}^{\text{miss}})$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\text{h}^{\pm}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\text{h}^{\pm}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\text{h}^{\pm}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\text{e}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\text{e}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\text{e}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\mu}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\mu}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\mu}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\text{h}^{0}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\text{h}^{0}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\text{h}^{0}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\gamma}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\gamma}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\gamma}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The product of signal acceptance and efficiency in the high-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the high-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the high-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the high-$R_{\text{T}}$ signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the high-$R_{\text{T}}$ signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the high-$R_{\text{T}}$ signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the high-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the high-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the high-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the low-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the low-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the low-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the low-$R_{\text{T}}$ signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the low-$R_{\text{T}}$ signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the low-$R_{\text{T}}$ signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the low-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the low-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the low-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the high-SVJ2 signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the high-SVJ2 signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the high-SVJ2 signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the high-SVJ2 signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the high-SVJ2 signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the high-SVJ2 signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the high-SVJ2 signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the high-SVJ2 signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the high-SVJ2 signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the low-SVJ2 signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the low-SVJ2 signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the low-SVJ2 signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the low-SVJ2 signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the low-SVJ2 signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the low-SVJ2 signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the low-SVJ2 signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the low-SVJ2 signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the low-SVJ2 signal region, for variations of the mediator mass and the dark coupling strength.
Comparison of different the dijet mass $m_{\text{J}\text{J}}$, the transverse mass $m_{\text{T}}$, and the Monte Carlo (MC) mass $m_{\text{MC}}$ for a signal model with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. No selection is applied, except that there must be at least two jets. $m_{\text{MC}}$ is computed by adding the generator-level four-vectors for invisible particles to the dijet system, to represent the achievable resolution if the invisible component were fully measured. The last bin of each histogram includes the overflow events.
Comparison of different the dijet mass $m_{\text{J}\text{J}}$, the transverse mass $m_{\text{T}}$, and the Monte Carlo (MC) mass $m_{\text{MC}}$ for a signal model with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. No selection is applied, except that there must be at least two jets. $m_{\text{MC}}$ is computed by adding the generator-level four-vectors for invisible particles to the dijet system, to represent the achievable resolution if the invisible component were fully measured. The last bin of each histogram includes the overflow events.
Comparison of different the dijet mass $m_{\text{J}\text{J}}$, the transverse mass $m_{\text{T}}$, and the Monte Carlo (MC) mass $m_{\text{MC}}$ for a signal model with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. No selection is applied, except that there must be at least two jets. $m_{\text{MC}}$ is computed by adding the generator-level four-vectors for invisible particles to the dijet system, to represent the achievable resolution if the invisible component were fully measured. The last bin of each histogram includes the overflow events.
$m_{\text{T}}$ distributions for signal models with different $m_{\text{dark}}$ values for the high-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $m_{\text{dark}}$ values for the high-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $m_{\text{dark}}$ values for the high-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $m_{\text{dark}}$ values for the low-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $m_{\text{dark}}$ values for the low-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $m_{\text{dark}}$ values for the low-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $r_{\text{inv}}$ values for the high-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $r_{\text{inv}}$ values for the high-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $r_{\text{inv}}$ values for the high-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $r_{\text{inv}}$ values for the low-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $r_{\text{inv}}$ values for the low-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $r_{\text{inv}}$ values for the low-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $\alpha_{\text{dark}}$ values for the high-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $\alpha_{\text{dark}}$ values for the high-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $\alpha_{\text{dark}}$ values for the high-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $\alpha_{\text{dark}}$ values for the low-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $\alpha_{\text{dark}}$ values for the low-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $\alpha_{\text{dark}}$ values for the low-$R_{\text{T}}$ inclusive signal region.
The proportions of each SM background process in the high-$R_{\text{T}}$ signal region.
The proportions of each SM background process in the high-$R_{\text{T}}$ signal region.
The proportions of each SM background process in the high-$R_{\text{T}}$ signal region.
The proportions of each SM background process in the low-$R_{\text{T}}$ signal region.
The proportions of each SM background process in the low-$R_{\text{T}}$ signal region.
The proportions of each SM background process in the low-$R_{\text{T}}$ signal region.
The proportions of each SM background process in the high-SVJ2 signal region.
The proportions of each SM background process in the high-SVJ2 signal region.
The proportions of each SM background process in the high-SVJ2 signal region.
The proportions of each SM background process in the low-SVJ2 signal region.
The proportions of each SM background process in the low-SVJ2 signal region.
The proportions of each SM background process in the low-SVJ2 signal region.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the dark hadron mass.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the dark hadron mass.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the dark hadron mass.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the invisible fraction.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the invisible fraction.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the invisible fraction.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the dark hadron mass.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the dark hadron mass.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the dark hadron mass.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the invisible fraction.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the invisible fraction.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the invisible fraction.
Relative efficiencies in % for each step of the event selection process for the major background processes. Statistical uncertainties, at most 1.8%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for the major background processes. Statistical uncertainties, at most 1.8%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for the major background processes. Statistical uncertainties, at most 1.8%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, varying $m_{\text{dark}}$ values, $r_{\text{inv}} = 0.3$, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.5%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, varying $m_{\text{dark}}$ values, $r_{\text{inv}} = 0.3$, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.5%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, varying $m_{\text{dark}}$ values, $r_{\text{inv}} = 0.3$, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.5%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, varying $m_{\text{dark}}$ values, $r_{\text{inv}} = 0.3$, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, varying $m_{\text{dark}}$ values, $r_{\text{inv}} = 0.3$, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, varying $m_{\text{dark}}$ values, $r_{\text{inv}} = 0.3$, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 4.1\,\text{TeV}$, varying $m_{\text{dark}}$ values, $r_{\text{inv}} = 0.3$, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 4.1\,\text{TeV}$, varying $m_{\text{dark}}$ values, $r_{\text{inv}} = 0.3$, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 4.1\,\text{TeV}$, varying $m_{\text{dark}}$ values, $r_{\text{inv}} = 0.3$, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, varying $r_{\text{inv}}$ values, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 2.6%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, varying $r_{\text{inv}}$ values, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 2.6%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, varying $r_{\text{inv}}$ values, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 2.6%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, varying $r_{\text{inv}}$ values, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 1.2%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, varying $r_{\text{inv}}$ values, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 1.2%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, varying $r_{\text{inv}}$ values, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 1.2%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 4.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, varying $r_{\text{inv}}$ values, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.9%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 4.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, varying $r_{\text{inv}}$ values, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.9%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 4.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, varying $r_{\text{inv}}$ values, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.9%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, and varying $\alpha_{\text{dark}}$ values. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, and varying $\alpha_{\text{dark}}$ values. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, and varying $\alpha_{\text{dark}}$ values. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, and varying $\alpha_{\text{dark}}$ values. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, and varying $\alpha_{\text{dark}}$ values. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, and varying $\alpha_{\text{dark}}$ values. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 4.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, and varying $\alpha_{\text{dark}}$ values. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 4.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, and varying $\alpha_{\text{dark}}$ values. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 4.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, and varying $\alpha_{\text{dark}}$ values. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
The associated production of a W and a Z boson is studied in final states with multiple leptons produced in proton-proton (pp) collisions at a centre-of-mass energy of 13 TeV using 137 fb$^{-1}$ of data collected with the CMS detector at the LHC. A measurement of the total inclusive production cross section yields $\sigma_{\text{tot}}$(pp $\to$ WZ) = 50.6 $\pm$ 0.8 (stat) $\pm$ 1.5 (syst) $\pm$ 1.1 (lumi) $\pm$ 0.5 (theo) pb. Measurements of the fiducial and differential cross sections for several key observables are also performed in all the final-state lepton flavour and charge compositions with a total of three charged leptons, which can be electrons or muons. All results are compared with theoretical predictions computed up to next-to-next-to-leading order in quantum chromodynamics plus next-to-leading order in electroweak theory and for various sets of parton distribution functions. The results include direct measurements of the charge asymmetry and the W and Z vector boson polarization. The first observation of longitudinally polarized W bosons in WZ production is reported. Anomalous gauge couplings are searched for, leading to new constraints on beyond-the-standard-model contributions to the WZ triple gauge coupling.
Distribution of the three leading leptons flavour in the CR-ZZ with uncertainties evaluated after the inclusive cross section fit
Distribution of the jet multiplicity in the CR-ttZ with uncertainties evaluated after the inclusive cross section fit
Distribution of the three leading leptons flavour in the CR-conv with uncertainties evaluated after the inclusive cross section fit
Distribution of the three leading leptons flavour in the SR-WZ with uncertainties evaluated after the inclusive cross section fit
Efficiency, acceptance, and proportion of events with leptonic tau decays in WZ production
WZ fiducial cross section in the four flavour exclusive and the flavour inclusive channels
WZ total cross section extrapolated from the four flavour exclusive and the flavour inclusive channels
Distribution of the total lepton charge in the SR-WZ with uncertainties evaluated after the inclusive cross section fit
W$^{+}$Z fiducial cross section in the four flavour exclusive and the flavour inclusive channels
W$^{-}$Z fiducial cross section in the four flavour exclusive and the flavour inclusive channels
WZ charge asymmetry ratio measured on each of the four flavour exclusive and the flavour inclusive channels
Distribution of the cosine of the W polarization angle times total lepton charge in the SR-WZ with uncertainties evaluated after the W polarization fit
Distribution of the cosine of the Z polarization angle in the SR-WZ with uncertainties evaluated after the Z polarization fit
Best fits to the W and Z polarization fractions
2D confidence regions at the 68, 95, and 99% CL in the $f_O^W$-$f_{L}^W-f_R^W$ plane
2D confidence regions at the 68, 95, and 99% CL in the $f_O^Z$-$f_{L}^Z-f_R^Z$ plane
Distribution of the invariant mass of the WZ system in the SR-WZ with uncertainties evaluated after the inclusive cross section fit
Best fit values and one dimensional confidence regions in several EFT coefficients obtained from the EFT fit considering both the SM interferences and purely BSM (order $\Lambda^{-2}$ and $\Lambda^{-4}$) terms
2D confidence regions at the 68, 95, and 99% CL in the $c_{www}$-$c_{w}$ plane
2D confidence regions at the 68, 95, and 99% CL in the $c_{w}$-$c_{b}$ plane
2D confidence regions at the 68, 95, and 99% CL in the $c_{www}$-$c_{w}$ plane
Best fit values and one dimensional confidence regions in several EFT coefficients obtained from the EFT fit considering only the SM-EFT interference (order $\Lambda^{-2}$) terms
Evolution of the best fit and expected and observed 95% CI for the $c_{w}$ parameter as a function of the cutoff scale
Evolution of the best fit and expected and observed 95% CI for the $c_{b}$ parameter as a function of the cutoff scale
Evolution of the best fit and expected and observed 95% CI for the $c_{www}$ parameter as a function of the cutoff scale
Evolution of the best fit and expected and observed 95% CI for the $\tilde{c}_{www}$ parameter as a function of the cutoff scale
Evolution of the best fit and expected and observed 95% CI for the $\tilde{c}_{w}$ parameter as a function of the cutoff scale
Differential cross section with respect to the transverse momentum of the Z boson
Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the $p_{T}$ of the Z boson
Response matrix for the $p_{T}$ of the Z boson obtained with POWHEG
Differential cross section with respect to the transverse momentum of the leading jet
Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the $p_{T}$ of the leading jet
Response matrix for the $p_{T}$ of the leading jet obtained with POWHEG
Differential cross section with respect to the jet multiplicity
Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the jet multiplicity
Response matrix for the jet multiplicity obtained with POWHEG
Differential cross section with respect to the invariant mass of the WZ system
Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the invariant mass of the WZ system
Response matrix for the invariant mass of the WZ system obtained with POWHEG
Differential cross section with respect to the transverse momentum of the lepton associated to the W boson
Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the $p_{T}$ of the lepton associated to the W boson
Response matrix for the $p_{T}$ of the lepton associated to the W boson obtained with POWHEG
Differential cross section with respect to the transverse momentum of the lepton associated to the W boson, W$^{+}$Z only
Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the $p_{T}$ of the lepton associated to the W boson, W$^{+}$Z only
Differential cross section with respect to the transverse momentum of the lepton associated to the W boson, W$^{-}$Z only
Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the $p_{T}$ of the lepton associated to the W boson, W$^{-}$Z only
Differential cross section with respect to the cosine of the W polarization angle times total lepton charge
Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the cosine of the W polarization angle times total lepton charge
Response matrix for the cosine of the W polarization angle times total lepton charge obtained with POWHEG
Differential cross section with respect to the cosine of the W polarization angle times total lepton charge, W$^{+}$Z only
Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the cosine of the W polarization angle times total lepton charge, W$^{+}$Z only
Differential cross section with respect to the cosine of the W polarization angle times total lepton charge, W$^{-}$Z only
Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the cosine of the W polarization angle times total lepton charge, W$^{-}$Z only
Differential cross section with respect to the cosine of the Z polarization angle
Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the cosine of the Z polarization angle
Response matrix for the cosine of the Z polarization angle obtained with POWHEG
Differential cross section with respect to the cosine of the Z polarization angle, W$^{+}$Z only
Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the cosine of the Z polarization angle, W$^{+}$Z only
Differential cross section with respect to the cosine of the Z polarization angle, W$^{-}$Z only
Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the cosine of the Z polarization angle, W$^{-}$Z only
A search is presented for new particles produced at the LHC in proton-proton collisions at $\sqrt{s} =$ 13 TeV, using events with energetic jets and large missing transverse momentum. The analysis is based on a data sample corresponding to an integrated luminosity of 101 fb$^{-1}$, collected in 2017-2018 with the CMS detector. Machine learning techniques are used to define separate categories for events with narrow jets from initial-state radiation and events with large-radius jets consistent with a hadronic decay of a W or Z boson. A statistical combination is made with an earlier search based on a data sample of 36 fb$^{-1}$, collected in 2016. No significant excess of events is observed with respect to the standard model background expectation determined from control samples in data. The results are interpreted in terms of limits on the branching fraction of an invisible decay of the Higgs boson, as well as constraints on simplified models of dark matter, on first-generation scalar leptoquarks decaying to quarks and neutrinos, and on models with large extra dimensions. Several of the new limits, specifically for spin-1 dark matter mediators, pseudoscalar mediators, colored mediators, and leptoquarks, are the most restrictive to date.
Differential signal yields for various signal hypotheses.
Differential signal yields for various signal hypotheses.
Differential signal yields for various signal hypotheses.
Differential signal yields for various signal hypotheses.
Differential signal yields for various signal hypotheses.
Differential signal yields for various signal hypotheses.
Differential signal yields for various signal hypotheses.
Differential signal yields for various signal hypotheses.
Differential signal yields for various signal hypotheses.
Differential signal yields for various signal hypotheses.
Differential signal yields for various signal hypotheses.
Differential signal yields for various signal hypotheses.
Differential signal yields for various signal hypotheses.
Differential signal yields for various signal hypotheses.
Differential signal yields for various signal hypotheses.
Differential signal yields for various signal hypotheses.
Background and data yields in the control and signal region bins. The prediction before ("prefit") and after the background only fit ("b-only") are given separately.
Background and data yields in the control and signal region bins. The prediction before ("prefit") and after the background only fit ("b-only") are given separately.
Background and data yields in the control and signal region bins. The prediction before ("prefit") and after the background only fit ("b-only") are given separately.
Background and data yields in the control and signal region bins. The prediction before ("prefit") and after the background only fit ("b-only") are given separately.
Background and data yields in the control and signal region bins. The prediction before ("prefit") and after the background only fit ("b-only") are given separately.
Background and data yields in the control and signal region bins. The prediction before ("prefit") and after the background only fit ("b-only") are given separately.
Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit to the control regions, and serve as input to the simplified likelihood reinterpretation scheme.
Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit to the control regions, and serve as input to the simplified likelihood reinterpretation scheme.
Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit to the corresponding control regions, and serve as input to the simplified likelihood reinterpretation scheme.
Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit to the corresponding control regions, and serve as input to the simplified likelihood reinterpretation scheme.
Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit to the control regions, and serve as input to the simplified likelihood reinterpretation scheme.
Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit to the control regions, and serve as input to the simplified likelihood reinterpretation scheme.
Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit to the corresponding control regions, and serve as input to the simplified likelihood reinterpretation scheme.
Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit to the corresponding control regions, and serve as input to the simplified likelihood reinterpretation scheme.
Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit to the control regions, and serve as input to the simplified likelihood reinterpretation scheme.
Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit to the control regions, and serve as input to the simplified likelihood reinterpretation scheme.
Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit to the corresponding control regions, and serve as input to the simplified likelihood reinterpretation scheme.
Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit to the corresponding control regions, and serve as input to the simplified likelihood reinterpretation scheme.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Median Expected exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.
Median Expected exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.
Observed exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.
Observed exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.
Expected plus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.
Expected plus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.
Expected minus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.
Expected minus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.
Median Expected exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.
Median Expected exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.
Observed exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.
Observed exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.
Expected plus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.
Expected plus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.
Expected minus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.
Expected minus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.
Upper limits on the coupling $g_{\chi}$ in the simplified model with a axial mediator.
Upper limits on the coupling $g_{\chi}$ in the simplified model with a axial mediator.
Upper limits on the coupling $g_{q}$ in the simplified model with a axial mediator.
Upper limits on the coupling $g_{q}$ in the simplified model with a axial mediator.
Upper limits on the coupling $g_{\chi}$ in the simplified model with a vector mediator.
Upper limits on the coupling $g_{\chi}$ in the simplified model with a vector mediator.
Upper limits on the coupling $g_{q}$ in the simplified model with a vector mediator.
Upper limits on the coupling $g_{q}$ in the simplified model with a vector mediator.
Exclusion limits on the signal strength in the simplified model with scalar couplings.
Exclusion limits on the signal strength in the simplified model with scalar couplings.
Exclusion limits on the signal strength in the simplified model with pseudoscalar couplings.
Exclusion limits on the signal strength in the simplified model with pseudoscalar couplings.
Exclusion limits on the fundamental Planck scale $M_{D}$ as a function of the number of extra dimensions $d$.
Exclusion limits on the fundamental Planck scale $M_{D}$ as a function of the number of extra dimensions $d$.
Median Expected exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.
Median Expected exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.
Observed exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.
Observed exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.
Expected plus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.
Expected plus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.
Expected minus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.
Expected minus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.
Tagging efficiency for AK8 jets. The efficiency includes the effect of the machine-learning based DeepAK8 tagger, as well as the application of the mass window requirement on the jet. The efficiency is split depending on the matching generator-level object. For reinterpretation purposes, this efficiency can directly be applied to any AK8 jet that is matched to a given type of generator-level object, with no prior selection on the jet mass. Other acceptance requirements on jet $\p_{T}$ and $\eta$ should still be applied.
Tagging efficiency for AK8 jets. The efficiency includes the effect of the machine-learning based DeepAK8 tagger, as well as the application of the mass window requirement on the jet. The efficiency is split depending on the matching generator-level object. For reinterpretation purposes, this efficiency can directly be applied to any AK8 jet that is matched to a given type of generator-level object, with no prior selection on the jet mass. Other acceptance requirements on jet $\p_{T}$ and $\eta$ should still be applied.
A search for long-lived particles (LLPs) produced in decays of standard model (SM) Higgs bosons is presented. The data sample consists of 137 fb$^{-1}$ of proton-proton collisions at $\sqrt{s} =$ 13 TeV, recorded at the LHC in 2016-2018. A novel technique is employed to reconstruct decays of LLPs in the endcap muon detectors. The search is sensitive to a broad range of LLP decay modes and to masses as low as a few GeV. No excess of events above the SM background is observed. The most stringent limits to date on the branching fraction of the Higgs boson to LLPs subsequently decaying to quarks and $\tau^+\tau^-$ are found for proper decay lengths greater than 6, 20, and 40 m, for LLP masses of 7, 15, and 40 GeV, respectively.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 7 GeV mass and $ S \rightarrow d\bar{d}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 7 GeV mass and $ S \rightarrow d\bar{d}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 15 GeV mass and $ S \rightarrow d\bar{d}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 15 GeV mass and $ S \rightarrow d\bar{d}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 40 GeV mass and $ S \rightarrow d\bar{d}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 40 GeV mass and $ S \rightarrow d\bar{d}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 55 GeV mass and $ S \rightarrow d\bar{d}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 55 GeV mass and $ S \rightarrow d\bar{d}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 7 GeV mass and $ S \rightarrow \tau^{+} \tau^{-}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 7 GeV mass and $ S \rightarrow \tau^{+} \tau^{-}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 15 GeV mass and $ S \rightarrow \tau^{+} \tau^{-}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 15 GeV mass and $ S \rightarrow \tau^{+} \tau^{-}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 40 GeV mass and $ S \rightarrow \tau^{+} \tau^{-}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 40 GeV mass and $ S \rightarrow \tau^{+} \tau^{-}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 55 GeV mass and $ S \rightarrow \tau^{+} \tau^{-}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 55 GeV mass and $ S \rightarrow \tau^{+} \tau^{-}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 15 GeV mass and $ S \rightarrow b\bar{b}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 15 GeV mass and $ S \rightarrow b\bar{b}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 40 GeV mass and $ S \rightarrow b\bar{b}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 40 GeV mass and $ S \rightarrow b\bar{b}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 55 GeV mass and $ S \rightarrow b\bar{b}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 55 GeV mass and $ S \rightarrow b\bar{b}$ decay mode.
The cluster efficiency in bins of hadronic and EM energy in region A. Region A is defined as 391 cm $< r <$ 695.5 cm and 400 cm $< |z| <$ 671 cm. The cluster efficiency is estimated with LLPs decaying to $\tau^{+} \tau^{-}$. The sample contains equal fractions of events with LLP mass of 7, 15, 40, and 55 GeV and LLP lifetime of 0.1, 1, 10, and 100m. The first hadronic energy bins correspond to LLPs that decayed leptonically with 0 hadronic energy. The cluster efficiency includes all cluster-level selections described in the paper, except for the jet veto, time cut, and $\Delta\phi$ cut. The full simulation signal yield prediction for samples with various LLP mass between 7 - 55 GeV, lifetime between 0.1 - 100 m, and decay mode to $d\bar{d}$ and $\tau^{+} \tau^{-}$ can be reproduced using this parameterization to within 35% and 20% for region A and B, respectively.
The cluster efficiency in bins of hadronic and EM energy in region A. Region A is defined as 391 cm $< r <$ 695.5 cm and 400 cm $< |z| <$ 671 cm. The cluster efficiency is estimated with LLPs decaying to $\tau^{+} \tau^{-}$. The sample contains equal fractions of events with LLP mass of 7, 15, 40, and 55 GeV and LLP lifetime of 0.1, 1, 10, and 100m. The first hadronic energy bins correspond to LLPs that decayed leptonically with 0 hadronic energy. The cluster efficiency includes all cluster-level selections described in the paper, except for the jet veto, time cut, and $\Delta\phi$ cut. The full simulation signal yield prediction for samples with various LLP mass between 7 - 55 GeV, lifetime between 0.1 - 100 m, and decay mode to $d\bar{d}$ and $\tau^{+} \tau^{-}$ can be reproduced using this parameterization to within 35% and 20% for region A and B, respectively.
The cluster efficiency in bins of hadronic and EM energy in region B. Region B is defined as 671 cm $< |z| <$ 1100 cm, $r <$ 695.5 cm, and $|\eta| <$ 2. The cluster efficiency is estimated with LLPs decaying to $\tau^{+} \tau^{-}$. The sample contains equal fractions of events with LLP mass of 7, 15, 40, and 55 GeV and LLP lifetime of 0.1, 1, 10, and 100m. The first hadronic energy bins correspond to LLPs that decayed leptonically with 0 hadronic energy. The cluster efficiency includes all cluster-level selections described in the paper, except for the jet veto, time cut, and $\Delta\phi$ cut. The full simulation signal yield prediction for samples with various LLP mass between 7 - 55 GeV, lifetime between 0.1 - 100 m, and decay mode to $d\bar{d}$ and $\tau^{+} \tau^{-}$ can be reproduced using this parameterization to within 35% and 20% for region A and B, respectively.
The cluster efficiency in bins of hadronic and EM energy in region B. Region B is defined as 671 cm $< |z| <$ 1100 cm, $r <$ 695.5 cm, and $|\eta| <$ 2. The cluster efficiency is estimated with LLPs decaying to $\tau^{+} \tau^{-}$. The sample contains equal fractions of events with LLP mass of 7, 15, 40, and 55 GeV and LLP lifetime of 0.1, 1, 10, and 100m. The first hadronic energy bins correspond to LLPs that decayed leptonically with 0 hadronic energy. The cluster efficiency includes all cluster-level selections described in the paper, except for the jet veto, time cut, and $\Delta\phi$ cut. The full simulation signal yield prediction for samples with various LLP mass between 7 - 55 GeV, lifetime between 0.1 - 100 m, and decay mode to $d\bar{d}$ and $\tau^{+} \tau^{-}$ can be reproduced using this parameterization to within 35% and 20% for region A and B, respectively.
The efficiency of $N_{station} > 1$ requirement in bins of hadronic energy in region B. Region B is defined as 671 cm $< |z| <$ 1100 cm, $r <$ 695.5 cm, and $|\eta| <$ 2. The cluster efficiency is estimated with LLPs decaying to $\tau^{+} \tau^{-}$. The sample contains equal fractions of events with LLP mass of 7, 15, 40, and 55 GeV and LLP lifetime of 0.1, 1, 10, and 100m. The first hadronic energy bin corresponds to LLPs that decayed leptonically with 0 hadronic energy. The efficiency is calculated with respect to clusters that pass all cluster-level cuts described in the paper, except for the jet veto, time cut, and $\Delta\phi$ cut. The full simulation signal yield prediction for samples with various LLP mass between 7 - 55 GeV, lifetime between 0.1 - 100 m, and decay mode to $d\bar{d}$ and $\tau^{+} \tau^{-}$ can be reproduced using this parameterization to within 10%.
The efficiency of $N_{station} > 1$ requirement in bins of hadronic energy in region B. Region B is defined as 671 cm $< |z| <$ 1100 cm, $r <$ 695.5 cm, and $|\eta| <$ 2. The cluster efficiency is estimated with LLPs decaying to $\tau^{+} \tau^{-}$. The sample contains equal fractions of events with LLP mass of 7, 15, 40, and 55 GeV and LLP lifetime of 0.1, 1, 10, and 100m. The first hadronic energy bin corresponds to LLPs that decayed leptonically with 0 hadronic energy. The efficiency is calculated with respect to clusters that pass all cluster-level cuts described in the paper, except for the jet veto, time cut, and $\Delta\phi$ cut. The full simulation signal yield prediction for samples with various LLP mass between 7 - 55 GeV, lifetime between 0.1 - 100 m, and decay mode to $d\bar{d}$ and $\tau^{+} \tau^{-}$ can be reproduced using this parameterization to within 10%.
The geometric signal acceptance as a function of $c\tau$. The acceptance is shown for four different LLP mass hypotheses: 7, 15, 40, and 55 GeV. The acceptance is defined by requiring at least 1 LLP to decay in the region defined as 400 cm $< |z| <$ 1100 cm, $r < $ 695.5 cm, and $|\eta| <$ 2.4.
A search is presented for a heavy vector resonance decaying into a Z boson and the standard model Higgs boson, where the Z boson is identified through its leptonic decays to electrons, muons, or neutrinos, and the Higgs boson is identified through its hadronic decays. The search is performed in a Lorentz-boosted regime and is based on data collected from 2016 to 2018 at the CERN LHC, corresponding to an integrated luminosity of 137 fb$^{-1}$. Upper limits are derived on the production of a narrow heavy resonance Z', and a mass below 3.5 and 3.7 TeV is excluded at 95% confidence level in models where the heavy vector boson couples exclusively to fermions and to bosons, respectively. These are the most stringent limits placed on the Heavy Vector Triplet Z' model to date. If the heavy vector boson couples exclusively to standard model bosons, upper limits on the product of the cross section and branching fraction are set between 23 and 0.3 fb for a Z' mass between 0.8 and 4.6 TeV, respectively. This is the first limit set on a heavy vector boson coupling exclusively to standard model bosons in its production and decay.
The product of signal acceptance and efficiency in the 0l categories for the signal produced via qqbar annihilation.
The product of signal acceptance and efficiency in the 2l categories for the signal produced via qqbar annihilation.
The product of signal acceptance and efficiency in the 0l categories for the signal produced via vector boson fusion.
The product of signal acceptance and efficiency in the 2l categories for the signal produced via vector boson fusion.
$m_{X}^{T}$ distribution in data in the 0l 2b non-VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}^{T}$ observed in the SR.
$m_{X}^{T}$ distribution in data in the 0l $\leq$1b non-VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}^{T}$ observed in the SR.
$m_{X}$ distribution in data in the 2e 2b non-VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}$ observed in the SR.
$m_{X}$ distribution in data in the 2e $\leq$1b non-VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}$ observed in the SR.
$m_{X}$ distribution in data in the 2$\mu$ 2b non-VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}$ observed in the SR.
$m_{X}$ distribution in data in the 2$\mu$ $\leq$1b non-VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}$ observed in the SR.
$m_{X}^{T}$ distribution in data in the 0l 2b VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}^{T}$ observed in the SR.
$m_{X}^{T}$ distribution in data in the 0l $\leq$1b VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}^{T}$ observed in the SR.
$m_{X}$ distribution in data in the 2e 2b VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}$ observed in the SR.
$m_{X}$ distribution in data in the 2e $\leq$1b VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}$ observed in the SR.
$m_{X}$ distribution in data in the 2$\mu$ 2b VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}$ observed in the SR.
$m_{X}$ distribution in data in the 2$\mu$ $\leq$1b VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}$ observed in the SR.
Observed and expected 95% CL upper limit on $\sigma \mathcal{B}$(Z'-> ZH) with all categories combined for the non-VBF signal, including all statistical and systematic uncertainties. The inner green band and the outer yellow band indicate the regions containing 68 and 95%, respectively, of the distribution of expected limits under the background-only hypothesis. The CMS search for a heavy resonance using 2016 data and the same final state [JHEP 11 (2018) 172] is shown as a comparison.
Observed and expected 95% CL upper limit on $\sigma \mathcal{B}$(Z'-> ZH) with all categories combined for the VBF signal, including all statistical and systematic uncertainties. The inner green band and the outer yellow band indicate the regions containing 68 and 95%, respectively, of the distribution of expected limits under the background-only hypothesis.
Observed exclusion limit in the space of the HVT model parameters [$g_{V}c_{H}$, $g^{2}c_{F}/g_{V}$] for mass hypotheses of 2 TeV for the non-VBF signal.
Observed exclusion limit in the space of the HVT model parameters [$g_{V}c_{H}$, $g^{2}c_{F}/g_{V}$] for mass hypotheses of 3 TeV for the non-VBF signal.
Observed exclusion limit in the space of the HVT model parameters [$g_{V}c_{H}$, $g^{2}c_{F}/g_{V}$] for mass hypotheses of 4 TeV for the non-VBF signal.
A search is performed for the rare decay W$^\pm\to\pi^\pm\gamma$ in proton-proton collisions at $\sqrt{s} =$ 13 TeV. Data corresponding to an on W integrated luminosity of 137 fb$^{-1}$ were collected during 2016 to 2018 with the CMS detector. This analysis exploits a novel search strategy based on W boson production in top quark pair events. An inclusive search for the W$^\pm\to\pi^\pm\gamma$ decay is not optimal at the LHC because of the high trigger thresholds. Instead, a trigger selection is exploited in which the W boson originating from one of the top quarks is used to tag the event in a leptonic decay. The W boson emerging from the other top quark is used to search for the W$^\pm\to\pi^\pm\gamma$ signature. Such decays are characterized by an isolated track pointing to a large energy deposit, and by an isolated photon of large transverse momentum. The presence of b quark jets reduces the background from the hadronization of light-flavor quarks and gluons. The W$^\pm\to\pi^\pm\gamma$ decay is not observed. An upper exclusion limit is set to this branching fraction, corresponding to 1.50 $\times$ 10$^{-5}$ at 95% confidence level, whereas the expected upper limit exclusion limit is 0.85 $^{+0.52}_{-0.29}$ $\times$ 10$^{-5}$.
The product of signal efficiency and acceptance per year and per lepton channel (muon or electron).
Expected and observed upper exclusion limits on the branching fraction of the decay of a W boson into a pion and a photon, using 2016 to 2018 data.
A search for physics beyond the standard model in events with at least three charged leptons (electrons or muons) is presented. The data sample corresponds to an integrated luminosity of 137 fb$^{-1}$ of proton-proton collisions at $\sqrt{s} =$ 13 TeV, collected with the CMS detector at the LHC in 2016-2018. The two targeted signal processes are pair production of type-III seesaw heavy fermions and production of a light scalar or pseudoscalar boson in association with a pair of top quarks. The heavy fermions may be manifested as an excess of events with large values of leptonic transverse momenta or missing transverse momentum. The light scalars or pseudoscalars may create a localized excess in the dilepton mass spectra. The results exclude heavy fermions of the type-III seesaw model for masses below 880 GeV at 95% confidence level in the scenario of equal branching fractions to each lepton flavor. This is the most restrictive limit on the flavor-democratic scenario of the type-III seesaw model to date. Assuming a Yukawa coupling of unit strength to top quarks, branching fractions of new scalar (pseudoscalar) bosons to dielectrons or dimuons above 0.004 (0.03) and 0.04 (0.03) are excluded at 95% confidence level for masses in the range 15-75 and 108-340 GeV, respectively. These are the first limits in these channels on an extension of the standard model with scalar or pseudoscalar particles.
The $M_{T}$ distribution in the WZ-enriched region. The last bin contains the overflow events.
The $L_{T}$ distribution in the ttZ-enriched region. The last bin contains the overflow events.
The $S_{T}$ distribution in the ZZ-enriched region. The last bin contains the overflow events.
The $L_{T}$ distribution in the MisID-enriched region. The last bin contains the overflow events.
The $L_{T}+p^{miss}_{T}$ distribution in the 3L below-Z signal region. The last bin contains the overflow events.
The $M_{T}$ distribution in the 3L on-Z signal region. The last bin contains the overflow events.
The $L_{T}+p^{miss}_{T}$ distribution in the 3L above-Z signal region. The last bin contains the overflow events.
The $L_{T}+p^{miss}_{T}$ distribution in the 3L OSSF0 signal region. The last bin contains the overflow events.
The $L_{T}+p^{miss}_{T}$ distribution in the 4L OSSF0 signal region. The last bin contains the overflow events.
The $L_{T}+p^{miss}_{T}$ distribution in the 4L OSSF1 signal region. The last bin contains the overflow events.
The $L_{T}+p^{miss}_{T}$ distribution in the 4L OSSF2 signal region. The last bin contains the overflow events.
The dielectron $M_{OSSF}^{20}$ distribution in the 3L(ee) 0B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{300}$ distribution in the 3L(ee) 0B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{20}$ distribution in the 3L(ee) 0B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{300}$ distribution in the 3L(ee) 0B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{20}$ distribution in the 3L(ee) 0B, $S_{T}$>800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{300}$ distribution in the 3L(ee) 0B, $S_{T}$>800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{20}$ distribution in the 3L(ee) 1B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{300}$ distribution in the 3L(ee) 1B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{20}$ distribution in the 3L(ee) 1B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{300}$ distribution in the 3L(ee) 1B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{20}$ distribution in the 3L(ee) 1B, $S_{T}$>800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{300}$ distribution in the 3L(ee) 1B, $S_{T}$>800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{20}$ distribution in the 4L(ee) 0B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{300}$ distribution in the 4L(ee) 0B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{20}$ distribution in the 4L(ee) 0B, $S_{T}$>400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{300}$ distribution in the 4L(ee) 0B, $S_{T}$>400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{20}$ distribution in the 4L(ee) 1B signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{300}$ distribution in the 4L(ee) 1B signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dimuon $M_{OSSF}^{20}$ distribution in the 3L($\mu\mu$) 0B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{300}$ distribution in the 3L($\mu\mu$) 0B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{20}$ distribution in the 3L($\mu\mu$) 0B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{300}$ distribution in the 3L($\mu\mu$) 0B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{20}$ distribution in the 3L($\mu\mu$) 0B, $S_{T}$>800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{300}$ distribution in the 3L($\mu\mu$) 0B, $S_{T}$>800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{20}$ distribution in the 3L($\mu\mu$) 1B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{300}$ distribution in the 3L($\mu\mu$) 1B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{20}$ distribution in the 3L($\mu\mu$) 1B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{300}$ distribution in the 3L($\mu\mu$) 1B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{20}$ distribution in the 3L($\mu\mu$) 1B, $S_{T}$>800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{300}$ distribution in the 3L($\mu\mu$) 1B, $S_{T}$>800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{20}$ distribution in the 4L($\mu\mu$) 0B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{300}$ distribution in the 4L($\mu\mu$) 0B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{20}$ distribution in the 4L($\mu\mu$) 0B, $S_{T}$>400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{300}$ distribution in the 4L($\mu\mu$) 0B, $S_{T}$>400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{20}$ distribution in the 4L($\mu\mu$) 1B signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{300}$ distribution in the 4L($\mu\mu$) 1B signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The 95% confidence level exclusion limits for the flavor-democratic scenario on the total production cross section of heavy fermion pairs.
The 95% confidence level exclusion limits on the product of the total production cross section of tt$\phi$(S) and $\mathcal{B}(\phi - {ee})$.
The 95% confidence level exclusion limits on the product of the total production cross section of tt$\phi$(PS) and $\mathcal{B}(\phi - {ee})$.
The 95% confidence level exclusion limits on the product of the total production cross section of tt$\phi$(S) and $\mathcal{B}(\phi - {\mu\mu})$.
The 95% confidence level exclusion limits on the product of the total production cross section of tt$\phi$(PS) and $\mathcal{B}(\phi - {\mu\mu})$.
The 95% confidence level exclusion limits on $g_{t}^2\mathcal{B}(\phi - {ee})$ for tt$\phi$(S).
The 95% confidence level exclusion limits on $g_{t}^2\mathcal{B}(\phi - {ee})$ for tt$\phi$(PS).
The 95% confidence level exclusion limits on $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$ for tt$\phi$(S).
The 95% confidence level exclusion limits on $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$ for tt$\phi$(PS).
Product of the fiducial acceptance and the event selection efficiency for the type-III Seesaw signal model at various signal mass hypotheses calculated after all analysis selection requirements.
Product of the fiducial acceptance and the event selection efficiency for the tt$\phi$ signal models at various signal mass hypotheses calculated after all analysis selection requirements.
A search for long-lived particles decaying to displaced, nonprompt jets and missing transverse momentum is presented. The data sample corresponds to an integrated luminosity of 137 fb$^{-1}$ of proton-proton collisions at a center-of-mass energy of 13 TeV collected by the CMS experiment at the CERN LHC in 2016-2018. Candidate signal events containing nonprompt jets are identified using the timing capabilities of the CMS electromagnetic calorimeter. The results of the search are consistent with the background prediction and are interpreted using a gauge-mediated supersymmetry breaking reference model with a gluino next-to-lightest supersymmetric particle. In this model, gluino masses up to 2100, 2500, and 1900 GeV are excluded at 95% confidence level for proper decay lengths of 0.3, 1, and 100 m, respectively. These are the best limits to date for such massive gluinos with proper decay lengths greater than $\sim$0.5 m.
Summary of the estimated number of background events.
Summary of the estimated number of background events.
The timing distribution of the backgrounds predicted to contribute to the signal region, compared to those for a representative signal model. The time is defined by the jet in the event with the largest $t_{\mathrm{jet}}$ passing the relevant selection. The distributions for the major backgrounds are taken from control regions and normalized to the predictions. The observed data is shown by the black points.
The timing distribution of the background sources predicted to contribute to the signal region, compared to those for a representative signal model. The time is defined by the jet in the event with the largest $t_{\mathrm{jet}}$ passing the relevant selection. The distributions for the major backgrounds are taken from control regions and normalized to the predictions. The observed data is shown by the black points. No events are observed in data for $t_{\mathrm{jet}} > 3\,$ns (indicated with a vertical black line).
The product of the acceptance and efficiency in the $c\tau_{0}$ vs. $m_{\tilde{g}}$ plane for the GMSB model, after all requirements.
The product of the acceptance and efficiency in the $c\tau_{0}$ vs. $m_{\tilde{g}}$ plane for the GMSB model, after all requirements.
The observed upper limits at $95\%$ CL for the gluino pair production cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed.
The observed upper limits at $95\%$ CL for the gluino pair production cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
The observed upper limits at $95\%$ CL for the gluino pair production cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed.
The observed upper limits at $95\%$ CL for the gluino pair production cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
The observed and expected upper limits at $95\%$ CL on the gluino pair production cross section for a gluino GMSB model with $m_{\tilde{g}}=2400$ GeV. The one (two) standard deviation variation in the expected limit is shown in the inner green (outer yellow) band. The blue solid line shows the observed limit obtained by the CMS displaced jet search
The observed and expected upper limits at $95\%$ CL on the gluino pair production cross section for a gluino GMSB model with $m_{\tilde{g}}=2400$ GeV. The one (two) standard deviation variation in the expected limit is shown in the inner green (outer yellow) band. The blue solid line shows the observed limit obtained by the CMS displaced jet search
The distribution (normalized to unity) of number of ECAL cells hit in the jet for jets in a background enriched data sample (satisfying $|\eta| < 1.48$, $PV_{\rm track}^{\rm fraction} > 1/12$, $\mathrm{HEF} > 0.2$, $t_{\mathrm{jet}} < -3\,\mathrm{ns}$ and $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}} < 0.8$) and for signal jets satisfying signal region requirements (except those on $E_{\mathrm{ECAL}}$ and $N^{\mathrm{cell}}_{\mathrm{ECAL}}$).
The distribution (normalized to unity) of number of ECAL cells hit in the jet for jets in a background enriched data sample (satisfying $|\eta| < 1.48$, $p_\mathrm{T}tf > 0.08$, $\mathrm{HEF} > 0.2$, $t_{\mathrm{jet}} < -3\,\mathrm{ns}$ and $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}} < 0.8$) and for signal jets satisfying signal region requirements (except those on $E_{\mathrm{ECAL}}$ and $N^{\mathrm{cell}}_{\mathrm{ECAL}}$).
The distribution (normalized to unity) of $\mathrm{HEF}$ for a data sample enriched in beam halo and noise jets (satisfying $|\eta| < 1.48$, $p_\mathrm{T} > 30 \,\mathrm{GeV}$, $PV_{\rm track}^{\rm fraction} < 1/12$, $t_{\mathrm{jet}} < -3\,\mathrm{ns}$, $E_{\mathrm{ECAL}} > 20\,\mathrm{GeV}$ and $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}} < 0.4$) and for signal jets passing signal region selections (except on $\mathrm{HEF}$).
The distribution (normalized to unity) of $\mathrm{HEF}$ for a data sample enriched in beam halo and noise jets (satisfying $|\eta| < 1.48$, $p_\mathrm{T} > 30 \,\mathrm{GeV}$, $p_\mathrm{T}tf < 0.08$, $t_{\mathrm{jet}} < -3\,\mathrm{ns}$, $E_{\mathrm{ECAL}} > 20\,\mathrm{GeV}$ and $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}} < 0.4$) and for signal jets passing signal region selections (except on $\mathrm{HEF}$).
The distribution (normalized to unity) of $E_{\mathrm{HCAL}}$ for a data sample enriched in beam halo and noise jets (satisfying $|\eta| < 1.48$, $p_\mathrm{T} > 30 \,\mathrm{GeV}$, $PV_{\rm track}^{\rm fraction} < 1/12$, $t_{\mathrm{jet}} < -3\,\mathrm{ns}$, $E_{\mathrm{ECAL}} > 20\,\mathrm{GeV}$ and $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}} < 0.4$) and for signal jets passing signal region selections (except on $E_{\mathrm{HCAL}}$).
The distribution (normalized to unity) of $E_{\mathrm{HCAL}}$ for a data sample enriched in beam halo and noise jets (satisfying $|\eta| < 1.48$, $p_\mathrm{T} > 30 \,\mathrm{GeV}$, $p_\mathrm{T}tf < 0.08$, $t_{\mathrm{jet}} < -3\,\mathrm{ns}$, $E_{\mathrm{ECAL}} > 20\,\mathrm{GeV}$ and $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}} < 0.4$) and for signal jets passing signal region selections (except on $E_{\mathrm{HCAL}}$).
The distribution (normalized to unity) of $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}}$ for data sample enriched in jets from noise (satisfying $|\eta| < 1.48$, $p_\mathrm{T} > 30\,\mathrm{GeV}$, $PV_{\rm track}^{\rm fraction} > 1/12$, $\mathrm{HEF} > 0.2$, $t_{\mathrm{jet}} < -3\,\mathrm{ns}$, $E_{\mathrm{ECAL}} > 20 \,\mathrm{GeV}$ and $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}} < 0.8$) and for signal jets passing signal region selections (except on $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}}$ and $t^{\mathrm{RMS}}_\mathrm{jet}$)
The distribution (normalized to unity) of $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}}$ for data sample enriched in jets from noise (satisfying $|\eta| < 1.48$, $p_\mathrm{T} > 30\,\mathrm{GeV}$, $p_\mathrm{T}tf > 0.08$, $\mathrm{HEF} > 0.2$, $t_{\mathrm{jet}} < -3\,\mathrm{ns}$, $E_{\mathrm{ECAL}} > 20 \,\mathrm{GeV}$ and $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}} < 0.8$) and for signal jets passing signal region selections (except on $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}}$ and $t^{\mathrm{RMS}}_\mathrm{jet}$)
The distribution (normalized to unity) of $t^{\mathrm{RMS}}_\mathrm{jet}$ for data sample enriched in jets from noise (satisfying $|\eta| < 1.48$, $p_\mathrm{T} > 30\,\mathrm{GeV}$, $PV_{\rm track}^{\rm fraction} > 1/12$, $\mathrm{HEF} > 0.2$, $t_{\mathrm{jet}} < -3\,\mathrm{ns}$, $E_{\mathrm{ECAL}} > 20 \,\mathrm{GeV}$ and $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}} < 0.8$) and for signal jets passing signal region selections (except on $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}}$ and $t^{\mathrm{RMS}}_\mathrm{jet}$)
The distribution (normalized to unity) of $t^{\mathrm{RMS}}_\mathrm{jet}$ for data sample enriched in jets from noise (satisfying $|\eta| < 1.48$, $p_\mathrm{T} > 30\,\mathrm{GeV}$, $p_\mathrm{T}tf > 0.08$, $\mathrm{HEF} > 0.2$, $t_{\mathrm{jet}} < -3\,\mathrm{ns}$, $E_{\mathrm{ECAL}} > 20 \,\mathrm{GeV}$ and $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}} < 0.8$) and for signal jets passing signal region selections (except on $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}}$ and $t^{\mathrm{RMS}}_\mathrm{jet}$)
The distribution (normalized to unity) of $PV_{\rm track}^{\rm fraction}$ for a data sample enriched in main bunch backgrounds (satisfying $p_\mathrm{T} > 30\,\mathrm{GeV}$, $|\eta| < 1.48$, $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}} < 0.8$, $|t_{\mathrm{jet}}| < 3\,\mathrm{ns}$ and $E_{\mathrm{ECAL}} >20\,\mathrm{GeV}$) and for signal jets passing signal selections (except on $PV_{\rm track}^{\rm fraction}$).
The distribution (normalized to unity) of $p_\mathrm{T}tf$ for a data sample enriched in main bunch backgrounds (satisfying $p_\mathrm{T} > 30\,\mathrm{GeV}$, $|\eta| < 1.48$, $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}} < 0.8$, $|t_{\mathrm{jet}}| < 3\,\mathrm{ns}$ and $E_{\mathrm{ECAL}} >20\,\mathrm{GeV}$) and for signal jets passing signal selections (except on $p_\mathrm{T}tf$).
The distribution (normalized to unity) of $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}}$ for a data sample enriched in beam halo (satisfying $p_\mathrm{T} > 30\,\mathrm{GeV}$, $|\eta| < 1.48$, $PV_{\rm track}^{\rm fraction} < 1/12$, $\mathrm{HEF} < 0.2$, $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}} < 0.4$, $t_{\mathrm{jet}} < -3\,\mathrm{ns}$ and $E_{\mathrm{ECAL}} > 20\,\mathrm{GeV}$) and for signal jets passing signal selections (except on $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}}$)
The distribution (normalized to unity) of $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}}$ for a data sample enriched in beam halo (satisfying $p_\mathrm{T} > 30\,\mathrm{GeV}$, $|\eta| < 1.48$, $p_\mathrm{T}tf < 0.08$, $\mathrm{HEF} < 0.2$, $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}} < 0.4$, $t_{\mathrm{jet}} < -3\,\mathrm{ns}$ and $E_{\mathrm{ECAL}} > 20\,\mathrm{GeV}$) and for signal jets passing signal selections (except on $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}}$)
The distribution (normalized to unity) of $\mathrm{max}(\Delta \phi_{\mathrm{DT}})$ for a data sample enriched in cosmic muons (satisfying $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}} < 0.8$, $p_\mathrm{T} > 30\,\mathrm{GeV}$, $|\eta| < 1.48$, $PV_{\rm track}^{\rm fraction} < 1/12$, $\mathrm{HEF} > 0.2$, $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}} < 0.4$, $t_{\mathrm{jet}} > 3\,\mathrm{ns}$, $E_{\mathrm{ECAL}} > 20\,\mathrm{GeV}$ and failing the HCAL noise rejection quality filters) and for signal jets passing signal selections (except on $\mathrm{max}(\Delta \phi_{\mathrm{DT}})$).
The distribution (normalized to unity) of $\mathrm{max}(\Delta \phi_{\mathrm{DT}})$ for a data sample enriched in cosmic muons (satisfying $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}} < 0.8$, $p_\mathrm{T} > 30\,\mathrm{GeV}$, $|\eta| < 1.48$, $p_\mathrm{T}tf < 0.08$, $\mathrm{HEF} > 0.2$, $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}} < 0.4$, $t_{\mathrm{jet}} > 3\,\mathrm{ns}$, $E_{\mathrm{ECAL}} > 20\,\mathrm{GeV}$ and failing the HCAL noise rejection quality filters) and for signal jets passing signal selections (except on $\mathrm{max}(\Delta \phi_{\mathrm{DT}})$).
The distribution (normalized to unity) of $\mathrm{max}(\Delta \phi_{\mathrm{RPC}})$ for a data sample enriched in cosmic muons (satisfying $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}} < 0.8$, $p_\mathrm{T} > 30\,\mathrm{GeV}$, $|\eta| < 1.48$, $PV_{\rm track}^{\rm fraction} < 1/12$, $\mathrm{HEF} > 0.2$, $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}} < 0.4$, $t_{\mathrm{jet}} > 3\,\mathrm{ns}$, $E_{\mathrm{ECAL}} > 20\,\mathrm{GeV}$ and failing the HCAL noise rejection quality filters) and for signal jets passing signal selections (except on $\mathrm{max}(\Delta \phi_{\mathrm{RPC}})$).
The distribution (normalized to unity) of $\mathrm{max}(\Delta \phi_{\mathrm{RPC}})$ for a data sample enriched in cosmic muons (satisfying $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}} < 0.8$, $p_\mathrm{T} > 30\,\mathrm{GeV}$, $|\eta| < 1.48$, $p_\mathrm{T}tf < 0.08$, $\mathrm{HEF} > 0.2$, $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}} < 0.4$, $t_{\mathrm{jet}} > 3\,\mathrm{ns}$, $E_{\mathrm{ECAL}} > 20\,\mathrm{GeV}$ and failing the HCAL noise rejection quality filters) and for signal jets passing signal selections (except on $\mathrm{max}(\Delta \phi_{\mathrm{RPC}})$).
Distribution of $t_{\mathrm{jet}}$ for jets with the full Run 2 dataset with no cleaning selection applied (a) and after all jet cleaning selections are applied (b) in events satisfying the trigger requirements and satisfying $p_T^\mathrm{miss} > 300$. The jets are required to pass an inverted selection of $PV_{\rm track}^{\rm fraction} > 1/12$ to enrich the sample in those originating from main and satellite bunch backgrounds. The cleaning selections are shown to reduce the backgrounds by many orders of magnitude.
Distribution of $t_{\mathrm{jet}}$ for jets with the full Run 2 dataset with no cleaning selection applied (a) and after all jet cleaning selections are applied (b) in events satisfying the trigger requirements and satisfying $p_T^\mathrm{miss} > 300$. The jets are required to pass an inverted selection of $PV_{\rm track}^{\rm fraction} > 0.08$ to enrich the sample in those originating from main and satellite bunch backgrounds. The cleaning selections are shown to reduce the backgrounds by many orders of magnitude.
Distribution of $t_{\mathrm{jet}}$ for jets with the full Run 2 dataset in events satisfying the trigger requirements and satisfying $p_T^\mathrm{miss} < 300$. The jets are required to pass an inverted selection of $PV_{\rm track}^{\rm fraction} > 1/12$ to enrich the sample in those originating from main and satellite bunch backgrounds (all other jet cleaning selections are applied). Clear contributions from jets from satellite bunch collisions can be seen peaked around -5, 5 and 10 ns.
Distribution of $t_{\mathrm{jet}}$ for jets with the full Run 2 dataset in events satisfying the trigger requirements and satisfying $p_T^\mathrm{miss} < 300$. The jets are required to pass an inverted selection of $PV_{\rm track}^{\rm fraction} > 0.08$ to enrich the sample in those originating from main and satellite bunch backgrounds (all other jet cleaning selections are applied). Clear contributions from jets from satellite bunch collisions can be seen peaked around -5, 5 and 10 ns.
Contribution to the delayed time of jets from the $\beta$ of the gluino is plotted against the delay contribution from the difference (assuming straight line paths) between the path taken by the gluino and the particle forming the jet from the path length for a particle travelling directly to the same position on the ECAL barrel for gluino $c\tau_{0} = 10$ m and mass of 1000 Gev (top) and 3000 GeV (bottom). The dominant contribution is shown to be the gluino $\beta$.
Contribution to the delayed time of jets from the $\beta$ of the gluino is plotted against the delay contribution from the difference (assuming straight line paths) between the path taken by the gluino and the particle forming the jet from the path length for a particle travelling directly to the same position on the ECAL barrel for gluino $c\tau_{0} = 10$ m and mass of 1000 Gev (top) and 3000 GeV (bottom). The dominant contribution is shown to be the gluino $\beta$.
Selection efficiencies for the GMSB model with $m_{\tilde{g}}=1000$ and various proper decay lengths
Selection efficiencies for the GMSB model with $m_{\tilde{g}}=1000$ and various proper decay lengths
Selection efficiencies for the GMSB model with $m_{\tilde{g}}=2400$ and various proper decay lengths
Selection efficiencies for the GMSB model with $m_{\tilde{g}}=2400$ and various proper decay lengths
Selection efficiencies for the GMSB model with $m_{\tilde{g}}=3000$ and various proper decay lengths
Selection efficiencies for the GMSB model with $m_{\tilde{g}}=3000$ and various proper decay lengths
The observed upper limits at $95\%$ CL for the gluino pair production cross section relative to the theoretical cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
The observed upper limits at $95\%$ CL for the gluino pair production cross section relative to the theoretical cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
The expected upper limits at $95\%$ CL for the gluino pair production cross section relative to the theoretical cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
The expected upper limits at $95\%$ CL for the gluino pair production cross section relative to the theoretical cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
The expected plus 1 $\sigma_{\mathrm{experiment}}$ upper limits at $95\%$ CL for the gluino pair production cross section relative to the theoretical cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
The expected plus 1 $\sigma_{\mathrm{experiment}}$ upper limits at $95\%$ CL for the gluino pair production cross section relative to the theoretical cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
The expected minus 1 $\sigma_{\mathrm{experiment}}$ upper limits at $95\%$ CL for the gluino pair production cross section relative to the theoretical cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
The expected minus 1 $\sigma_{\mathrm{experiment}}$ upper limits at $95\%$ CL for the gluino pair production cross section relative to the theoretical cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
The expected upper limits at $95\%$ CL for the gluino pair production cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
The expected upper limits at $95\%$ CL for the gluino pair production cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
The expected plus 1 $\sigma_{\mathrm{experiment}}$ upper limits at $95\%$ CL for the gluino pair production cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
The expected plus 1 $\sigma_{\mathrm{experiment}}$ upper limits at $95\%$ CL for the gluino pair production cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
The expected minus 1 $\sigma_{\mathrm{experiment}}$ upper limits at $95\%$ CL for the gluino pair production cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
The expected minus 1 $\sigma_{\mathrm{experiment}}$ upper limits at $95\%$ CL for the gluino pair production cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
A general search is presented for a low-mass $\tau^-\tau^+$ resonance produced in association with a bottom quark. The search is based on proton-proton collision data at a center-of-mass energy of 13 TeV collected by the CMS experiment at the LHC, corresponding to an integrated luminosity of 35.9 fb$^{-1}$. The data are consistent with the standard model expectation. Upper limits at 95% confidence level on the cross section times branching fraction are determined for two signal models: a light pseudoscalar Higgs boson decaying to a pair of $\tau$ leptons produced in association with bottom quarks, and a low-mass boson X decaying to a $\tau$-lepton pair that is produced in the decay of a bottom-like quark B such that B $\to$ bX. Masses between 25 and 70 GeV are probed for the light pseudoscalar boson with upper limits ranging from 250 to 44 pb. Upper limits from 20 to 0.3 pb are set on B masses between 170 and 450 GeV for X boson masses between 20 and 70 GeV.
The product of acceptance, efficiency, and branching fraction of $\mathrm{b}\overline{\mathrm{b}}\mathrm{A}$ production with $\mathrm{A} \rightarrow \tau\tau$ in the $\mathrm{e}\tau_\mathrm{h}$ and $\mu\tau_\mathrm{h}$ channels of the 1 b tag event category, as a function of the pseudoscalar mass. The selections are as described in the paper. The uncertainty refers to the statistical uncertainty only.
Observed $m_{\tau\tau}$ distribution in the $\mathrm{e}\tau_\mathrm{h}$ channel of the 1 b tag category, compared to the expected SM background contributions. The signal distributions for $\mathrm{b}\overline{\mathrm{b}}\mathrm{A}$ production with pseudoscalar mass 40 and 60 GeV are overlaid to illustrate the sensitivity. They are normalized to the cross section times branching fraction of 800 pb. The uncertainty band represents the sum in quadrature of statistical and systematic uncertainties obtained from the fit. The lower panel shows the ratio between the observed and expected events in each bin.
Observed $m_{\tau\tau}$ distribution in the $\mu\tau_\mathrm{h}$ channel of the 1 b tag category, compared to the expected SM background contributions. The signal distributions for $\mathrm{b}\overline{\mathrm{b}}\mathrm{A}$ production with pseudoscalar mass 40 and 60 GeV are overlaid to illustrate the sensitivity. They are normalized to the cross section times branching fraction of 800 pb. The uncertainty band represents the sum in quadrature of statistical and systematic uncertainties obtained from the fit. The lower panel shows the ratio between the observed and expected events in each bin.
Observed (black solid) and expected (black dotted) limits at 95% confidence level on the product of the the cross section for bbA prodcution and the branching fraction $\mathrm{A} \rightarrow \tau\tau$, obtained from the combination of the $\mathrm{e}\tau_\mathrm{h}$ and $\mu\tau_\mathrm{h}$ channels in the 1 b tag category, as a function of the A boson mass. The green and yellow bands represent the one and two standard deviation uncertainties in the expected limits.
Observed (black solid) and expected (black dotted) limits at 95% confidence level on the product of the the cross section for bbA prodcution and the branching fraction $\mathrm{A} \rightarrow \tau\tau$, obtained in the $\mathrm{e}\tau_\mathrm{h}$ channel of the 1 b tag category, as a function of the A boson mass. The green and yellow bands represent the one and two standard deviation uncertainties in the expected limits.
Observed (black solid) and expected (black dotted) limits at 95% confidence level on the product of the the cross section for bbA prodcution and the branching fraction $\mathrm{A} \rightarrow \tau\tau$, obtained in the $\mu\tau_\mathrm{h}$ channel of the 1 b tag category, as a function of the A boson mass. The green and yellow bands represent the one and two standard deviation uncertainties in the expected limits.
The product of acceptance, efficiency, and branching fraction of the qbX signal with $\mathrm{X} \rightarrow \tau\tau$ and $m_{\mathrm{B}}=170~\mathrm{GeV}$ in $\mathrm{e}\tau_\mathrm{h}$ and $\mu\tau_\mathrm{h}$ channels of the 1b1f and 1b1c event categories, as a function of the X boson mass. The selections are as described in the paper. The uncertainty refers to the statistical uncertainty only.
Observed $m_{\tau\tau}$ distribution in the $\mathrm{e}\tau_\mathrm{h}$ channel of the 1b1f category, compared to the expected SM background contributions. The distributions of the qbX signal with $m_{\mathrm{B}}=170~\mathrm{GeV}$, and X boson mass 40 and 60 GeV are overlaid to illustrate the sensitivity. They are normalized to the cross section times branching fraction of 20 pb. The uncertainty band represents the sum in quadrature of statistical and systematic uncertainties obtained from the fit. The lower panel shows the ratio between the observed and expected events in each bin.
Observed $m_{\tau\tau}$ distribution in the $\mathrm{e}\tau_\mathrm{h}$ channel of the 1b1c category, compared to the expected SM background contributions. The distributions of the qbX signal with $m_{\mathrm{B}}=170~\mathrm{GeV}$, and X boson mass 40 and 60 GeV are overlaid to illustrate the sensitivity. They are normalized to the cross section times branching fraction of 20 pb. The uncertainty band represents the sum in quadrature of statistical and systematic uncertainties obtained from the fit. The lower panel shows the ratio between the observed and expected events in each bin.
Observed $m_{\tau\tau}$ distribution in the $\mu\tau_\mathrm{h}$ channel of the 1b1f category, compared to the expected SM background contributions. The distributions of the qbX signal with $m_{\mathrm{B}}=170~\mathrm{GeV}$, and X boson mass 40 and 60 GeV are overlaid to illustrate the sensitivity. They are normalized to the cross section times branching fraction of 20 pb. The uncertainty band represents the sum in quadrature of statistical and systematic uncertainties obtained from the fit. The lower panel shows the ratio between the observed and expected events in each bin.
Observed $m_{\tau\tau}$ distribution in the $\mu\tau_\mathrm{h}$ channel of the 1b1c category, compared to the expected SM background contributions. The distributions of the qbX signal with $m_{\mathrm{B}}=170~\mathrm{GeV}$, and X boson mass 40 and 60 GeV are overlaid to illustrate the sensitivity. They are normalized to the cross section times branching fraction of 20 pb. The uncertainty band represents the sum in quadrature of statistical and systematic uncertainties obtained from the fit. The lower panel shows the ratio between the observed and expected events in each bin.
Observed (black solid) and expected (black dotted) limits at 95% confidence level on the product of the the cross section for the prodcution of the qbX signal with mB = 170 GeV and the branching fraction $\mathrm{X} \rightarrow \tau\tau$, obtained from the combination of the $\mathrm{e}\tau_\mathrm{h}$ and $\mu\tau_\mathrm{h}$ channels, and the 1b1f and 1b1c categories, as a function of the X boson mass. The green and yellow bands represent the one and two standard deviation uncertainties in the expected limits.
Observed (black solid) and expected (black dotted) limits at 95% confidence level on the product of the the cross section for the prodcution of the qbX signal with mB = 300 GeV and the branching fraction $\mathrm{X} \rightarrow \tau\tau$, obtained from the combination of the $\mathrm{e}\tau_\mathrm{h}$ and $\mu\tau_\mathrm{h}$ channels, and the 1b1f and 1b1c categories, as a function of the X boson mass. The green and yellow bands represent the one and two standard deviation uncertainties in the expected limits.
Observed (black solid) and expected (black dotted) limits at 95% confidence level on the product of the the cross section for the prodcution of the qbX signal with mB = 450 GeV and the branching fraction $\mathrm{X} \rightarrow \tau\tau$, obtained from the combination of the $\mathrm{e}\tau_\mathrm{h}$ and $\mu\tau_\mathrm{h}$ channels, and the 1b1f and 1b1c categories, as a function of the X boson mass. The green and yellow bands represent the one and two standard deviation uncertainties in the expected limits.
Observed (black solid) and expected (black dotted) limits at 95% confidence level on the product of the the cross section for the prodcution of the qbX signal with mB = 170 GeV and the branching fraction $\mathrm{X} \rightarrow \tau\tau$, obtained in the $\mathrm{e}\tau_\mathrm{h}$ channel of the 1b1f category, as a function of the X boson mass. The green and yellow bands represent the one and two standard deviation uncertainties in the expected limits.
Observed (black solid) and expected (black dotted) limits at 95% confidence level on the product of the the cross section for the prodcution of the qbX signal with mB = 170 GeV and the branching fraction $\mathrm{X} \rightarrow \tau\tau$, obtained in the $\mathrm{e}\tau_\mathrm{h}$ channel of the 1b1c category, as a function of the X boson mass. The green and yellow bands represent the one and two standard deviation uncertainties in the expected limits.
Observed (black solid) and expected (black dotted) limits at 95% confidence level on the product of the the cross section for the prodcution of the qbX signal with mB = 170 GeV and the branching fraction $\mathrm{X} \rightarrow \tau\tau$, obtained in the $\mu\tau_\mathrm{h}$ channel of the 1b1f category, as a function of the X boson mass. The green and yellow bands represent the one and two standard deviation uncertainties in the expected limits.
Observed (black solid) and expected (black dotted) limits at 95% confidence level on the product of the the cross section for the prodcution of the qbX signal with mB = 170 GeV and the branching fraction $\mathrm{X} \rightarrow \tau\tau$, obtained in the $\mu\tau_\mathrm{h}$ channel of the 1b1c category, as a function of the X boson mass. The green and yellow bands represent the one and two standard deviation uncertainties in the expected limits.
A search is performed for events consistent with the pair production of a new heavy particle that acts as a mediator between a dark sector and normal matter, and that decays to a light quark and a new fermion called a dark quark. The search is based on data corresponding to an integrated luminosity of 16.1 fb$^{-1}$ from proton-proton collisions at $\sqrt{s} =$ 13 TeV collected by the CMS experiment at the LHC in 2016. The dark quark is charged only under a new quantum-chromodynamics-like force, and forms an "emerging jet" via a parton shower, containing long-lived dark hadrons that give rise to displaced vertices when decaying to standard model hadrons. The data are consistent with the expectation from standard model processes. Limits are set at 95% confidence level excluding dark pion decay lengths between 5 and 225 mm for dark mediators with masses between 400 and 1250 GeV. Decay lengths smaller than 5 mm and greater than 225 mm are also excluded in the lower part of this mass range. The dependence of the limit on the dark pion mass is weak for masses between 1 and 10 GeV. This analysis is the first dedicated search for the pair production of a new particle that decays to a jet and an emerging jet.
Distributions of $\langle IP_{\mathrm{2D}}\rangle$ for background (black) and for signals with a mediator mass of 1 TeV and a dark pion proper decay length of 25 mm, for various dark pion masses.
Distributions of $\alpha_\mathrm{3D}$ for background (black) and for signals with a mediator mass of 1 TeV and a dark pion mass of 5 GeV for dark pion proper decay lengths ranging from 1 to 300 mm.
The signal acceptance A, defined as the fraction of simulated signal events passing the selection criteria, for models with a dark pion mass $m_{\pi_\mathrm{DK}}$ of 5 GeV as a function of the mediator mass $m_{\mathrm{X_{DK}}}$ and the dark pion proper decay length $c\tau_{\pi_\mathrm{DK}}$. The corresponding selection set number for each model is indicated as text on the plot.
Measured misidentification probability distribution as a function of track multiplicity for the EMJ-1 criteria group defined in Table 2. The red up-pointing triangles are for b jets while the blue down-pointing triangles are for light-flavor jets. The horizontal lines on the data points indicate the variable bin width.
The $H_\mathrm{T}$ distribution for the observed data events (black points) and the predicted background estimation (blue) for selection set 8 (SM QCD-enhanced), requiring at least two jets tagged by loose emerging jet criteria.
The number of associated tracks distribution for the observed data events (black points) and the predicted background estimation (blue) for selection set 8 (SM QCD-enhanced), requiring at least two jets tagged by loose emerging jet criteria.
The $H_\mathrm{T}$ distribution for the observed data events (black points) and the predicted background estimation (blue) for selection set 9 (SM QCD-enhanced), requiring at least one jet tagged by loose emerging jet criteria and large $p_\mathrm{T}^\mathrm{miss}$.
The number of associated tracks distribution for the observed data events (black points) and the predicted background estimation (blue) for selection set 9 (SM QCD-enhanced), requiring at least one jet tagged by loose emerging jet criteria and large $p_\mathrm{T}^\mathrm{miss}$.
Upper limits at 95% CL on the signal cross section for models with dark pion mass $(m_{\pi_\mathrm{DK}})$ of 5 GeV in the proper decay length $(c\tau_{\pi_\mathrm{DK}})$ versus dark mediator mass $(m_{\mathrm{X_{DK}}})$ plane.
Dark mediator mass exclusion limits at 95% CL derived from theoretical cross sections for models with dark pion mass $(m_{\pi_\mathrm{DK}})$ of 5 GeV in the proper decay length $(c\tau_{\pi_\mathrm{DK}})$ versus dark mediator mass $(m_{\mathrm{X_{DK}}})$ plane.
A search for a new heavy particle decaying to a pair of vector bosons (WW or WZ) is presented using data from the CMS detector corresponding to an integrated luminosity of 35.9 fb$^{-1}$ collected in proton-proton collisions at a centre-of-mass energy of 13 TeV in 2016. One of the bosons is required to be a W boson decaying to e$\nu$ or $\mu\nu$, while the other boson is required to be reconstructed as a single massive jet with substructure compatible with that of a highly-energetic quark pair from a W or Z boson decay. The search is performed in the resonance mass range between 1.0 and 4.5 TeV. The largest deviation from the background-only hypothesis is observed for a mass near 1.4 TeV and corresponds to a local significance of 2.5 standard deviations. The result is interpreted as an upper bound on the resonance production cross section. Comparing the excluded cross section values and the expectations from theoretical calculations in the bulk graviton and heavy vector triplet models, spin-2 WW resonances with mass smaller than 1.07 TeV and spin-1 WZ resonances lighter than 3.05 TeV, respectively, are excluded at 95% confidence level.
Exclusion limits on the product of the production cross section and the branching fraction for a new spin-2 resonance decaying to WW, as a function of the resonance mass hypothesis.
Exclusion limits on the product of the production cross section and the branching fraction for a new spin-1 resonance decaying to WZ, as a function of the resonance mass hypothesis.
Signal selection efficiency times acceptance as a function of resonance mass for a spin-2 bulk graviton decaying to WW and a spin-1 W' decaying to WZ.
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.
A search for heavy neutral Higgs bosons and $Z^{\prime}$ bosons is performed using a data sample corresponding to an integrated luminosity of 36.1 fb$^{-1}$ from proton-proton collisions at $\sqrt{s}$ = 13 TeV recorded by the ATLAS detector at the LHC during 2015 and 2016. The heavy resonance is assumed to decay to $\tau^+\tau^-$ with at least one tau lepton decaying to final states with hadrons and a neutrino. The search is performed in the mass range of 0.2-2.25 TeV for Higgs bosons and 0.2-4.0 TeV for $Z^{\prime}$ bosons. The data are in good agreement with the background predicted by the Standard Model. The results are interpreted in benchmark scenarios. In the context of the hMSSM scenario, the data exclude $\tan\beta > 1.0$ for $m_A$ = 0.25 TeV and $\tan\beta > 42$ for $m_A$ = 1.5 TeV at the 95% confidence level. For the Sequential Standard Model, $Z^{\prime}_\mathrm{SSM}$ with $m_{Z^{\prime}} < 2.42$ TeV is excluded at 95% confidence level, while $Z^{\prime}_\mathrm{NU}$ with $m_{Z^{\prime}} < 2.25$ TeV is excluded for the non-universal $G(221)$ model that exhibits enhanced couplings to third-generation fermions.
Observed and predicted mTtot distribution in the b-veto category of the 1l1tau_h channel. Despite listing this as an exclusive final state (as there must be no b-jets), there is no explicit selection on the presence of additional light-flavour jets. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. In the paper, the first bin is cut off at 60 GeV for aesthetics but contains underflows down to 50 GeV as in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 300, 500 and 800 GeV and $\tan\beta$ = 10 in the hMSSM scenario are also provided.
Observed and predicted mTtot distribution in the b-tag category of the 1l1tau_h channel. Despite listing this as an exclusive final state (as there must be at least one b-jets), there is no explicit selection on the presence of additional light-flavour jets. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. In the paper, the first bin is cut off at 60 GeV for aesthetics but contains underflows down to 50 GeV as in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 300, 500 and 800 GeV and $\tan\beta$ = 10 in the hMSSM scenario are also provided.
Observed and predicted mTtot distribution in the b-veto category of the 2tau_h channel. Despite listing this as an exclusive final state (as there must be no b-jets), there is no explicit selection on the presence of additional light-flavour jets. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 300, 500 and 800 GeV and $\tan\beta$ = 10 in the hMSSM scenario are also provided.
Observed and predicted mTtot distribution in the b-tag category of the 2tau_h channel. Despite listing this as an exclusive final state (as there must be at least one b-jets), there is no explicit selection on the presence of additional light-flavour jets. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 300, 500 and 800 GeV and $\tan\beta$ = 10 in the hMSSM scenario are also provided.
Observed and predicted mTtot distribution for the b-inclusive selection in the 1l1tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. In the paper, the first bin is cut off at 60 GeV for aesthetics but contains underflows down to 50 GeV as in the HepData table. The last bin includes overflows. The prediction for a SSM Zprime with masses of 1500, 2000 and 2500 GeV are also provided.
Observed and predicted mTtot distribution for the b-inclusive selection in the 2tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The prediction for a SSM Zprime with masses of 1500, 2000 and 2500 GeV are also provided.
Observed and expected 95% CL upper limits on the b-associated Higgs boson production cross section times ditau branching fraction as a function of the boson mass.
Observed and expected 95% CL upper limits on the Drell Yan production cross section times ditau branching fraction as a function of the Zprime boson mass.
Observed and expected 95% CL upper limits on the Higgs boson production cross section times ditau branching fraction as a function of the boson mass and the relative strength of the b-associated production.
Ratio of the 95% CL upper limits on the production cross section times branching fraction for alternate Zprime models with respect to the SSM, both observed and expected are shown.
Acceptance, acceptance times efficiency and b-tag category fraction for a scalar boson produced by gluon-gluon fusion as a function of the scalar boson mass.
Acceptance, acceptance times efficiency and b-tag category fraction for a scalar boson produced by b-associated production as a function of the scalar boson mass.
Acceptance and acceptance times efficiency for a heavy gauge boson produced by Drell Yan as a function of the gauge boson mass.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.
Observed and expected 95% CL upper limits on the gluon-gluon fusion Higgs boson production cross section times ditau branching fraction as a function of the boson mass.
A search for pair production of a scalar partner of the top quark in events with four or more jets plus missing transverse momentum is presented. An analysis of 36.1 fb$^{-1}$ of $\sqrt{s}$=13 TeV proton-proton collisions collected using the ATLAS detector at the LHC yields no significant excess over the expected Standard Model background. To interpret the results a simplified supersymmetric model is used where the top squark is assumed to decay via $\tilde{t}_1 \rightarrow t^{(*)} \tilde\chi^0_1$ and $\tilde{t}_1\rightarrow b\tilde\chi^\pm_1 \rightarrow b W^{(*)} \tilde\chi^0_1$, where $\tilde\chi^0_1$ ($\chi^\pm_1$) denotes the lightest neutralino (chargino). Exclusion limits are placed in terms of the top-squark and neutralino masses. Assuming a branching ratio of 100% to $t \tilde\chi^0_1$, top-squark masses in the range 450-950 GeV are excluded for $\tilde\chi^0_1$ masses below 160 GeV. In the case where $m_{\tilde{t}_1}\sim m_t+m_{\tilde\chi^0_1}$, top-squark masses in the range 235-590 GeV are excluded.
Distribution of $E_\text{T}^\text{miss}$ for SRA-TT after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $E_\text{T}^\text{miss}$ for SRA-TT after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $E_\text{T}^\text{miss}$ for SRA-TT after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $E_\text{T}^\text{miss}$ for SRA-TT after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $E_\text{T}^\text{miss}$ for SRA-TT after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $E_\text{T}^\text{miss}$ for SRA-TT after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $E_\text{T}^\text{miss}$ for SRA-TT after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T2}^{\chi^2}$ for SRA-T0 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T2}^{\chi^2}$ for SRA-T0 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T2}^{\chi^2}$ for SRA-T0 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T2}^{\chi^2}$ for SRA-T0 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T2}^{\chi^2}$ for SRA-T0 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T2}^{\chi^2}$ for SRA-T0 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T2}^{\chi^2}$ for SRA-T0 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T}^{b,\text{max}}$ for SRB-TW after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T}^{b,\text{max}}$ for SRB-TW after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T}^{b,\text{max}}$ for SRB-TW after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T}^{b,\text{max}}$ for SRB-TW after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T}^{b,\text{max}}$ for SRB-TW after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T}^{b,\text{max}}$ for SRB-TW after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T}^{b,\text{max}}$ for SRB-TW after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $R_\text{ISR}$ for SRC1-5 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $R_\text{ISR}$ for SRC1-5 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $R_\text{ISR}$ for SRC1-5 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $R_\text{ISR}$ for SRC1-5 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $R_\text{ISR}$ for SRC1-5 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $R_\text{ISR}$ for SRC1-5 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $R_\text{ISR}$ for SRC1-5 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T}^{b,\text{max}}$ for SRD-high after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T}^{b,\text{max}}$ for SRD-high after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T}^{b,\text{max}}$ for SRD-high after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T}^{b,\text{max}}$ for SRD-high after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T}^{b,\text{max}}$ for SRD-high after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T}^{b,\text{max}}$ for SRD-high after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T}^{b,\text{max}}$ for SRD-high after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $H_\text{T}$ for SRE after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $H_\text{T}$ for SRE after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $H_\text{T}$ for SRE after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $H_\text{T}$ for SRE after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $H_\text{T}$ for SRE after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $H_\text{T}$ for SRE after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $H_\text{T}$ for SRE after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Expected (blue solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Expected (blue solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Expected (blue solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Expected (blue solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Expected (blue solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Expected (blue solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Expected (blue solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Observed (red solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Observed (red solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Observed (red solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Observed (red solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Observed (red solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Observed (red solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Observed (red solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Expected exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Expected exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Expected exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Expected exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Expected exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Expected exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Expected exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Observed exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Observed exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Observed exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Observed exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Observed exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Observed exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Observed exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Results of the exclusion fits for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ from the combination of SRA, SRB, SRC, SRD and SRE, based on the best expected $CL_s$. The numbers centered on the grid points indicate which of the signal regions gave the best expected $CL_s$ (with 1, 2, 3, 4, 5, 6 corresponding to SRA, SRB, SRC, SRD-low,SR D-high, SRE respectively).
Results of the exclusion fits for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ from the combination of SRA, SRB, SRC, SRD and SRE, based on the best expected $CL_s$. The numbers centered on the grid points indicate which of the signal regions gave the best expected $CL_s$ (with 1, 2, 3, 4, 5, 6 corresponding to SRA, SRB, SRC, SRD-low,SR D-high, SRE respectively).
Results of the exclusion fits for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ from the combination of SRA, SRB, SRC, SRD and SRE, based on the best expected $CL_s$. The numbers centered on the grid points indicate which of the signal regions gave the best expected $CL_s$ (with 1, 2, 3, 4, 5, 6 corresponding to SRA, SRB, SRC, SRD-low,SR D-high, SRE respectively).
Results of the exclusion fits for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ from the combination of SRA, SRB, SRC, SRD and SRE, based on the best expected $CL_s$. The numbers centered on the grid points indicate which of the signal regions gave the best expected $CL_s$ (with 1, 2, 3, 4, 5, 6 corresponding to SRA, SRB, SRC, SRD-low,SR D-high, SRE respectively).
Results of the exclusion fits for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ from the combination of SRA, SRB, SRC, SRD and SRE, based on the best expected $CL_s$. The numbers centered on the grid points indicate which of the signal regions gave the best expected $CL_s$ (with 1, 2, 3, 4, 5, 6 corresponding to SRA, SRB, SRC, SRD-low,SR D-high, SRE respectively).
Results of the exclusion fits for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ from the combination of SRA, SRB, SRC, SRD and SRE, based on the best expected $CL_s$. The numbers centered on the grid points indicate which of the signal regions gave the best expected $CL_s$ (with 1, 2, 3, 4, 5, 6 corresponding to SRA, SRB, SRC, SRD-low,SR D-high, SRE respectively).
Results of the exclusion fits for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ from the combination of SRA, SRB, SRC, SRD and SRE, based on the best expected $CL_s$. The numbers centered on the grid points indicate which of the signal regions gave the best expected $CL_s$ (with 1, 2, 3, 4, 5, 6 corresponding to SRA, SRB, SRC, SRD-low,SR D-high, SRE respectively).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 25%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 25%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 25%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 25%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 25%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 25%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 25%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 50%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 50%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 50%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 50%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 50%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 50%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 50%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0 (top left), 25% (top right), 50% (middle left), 75% middle right) and 100% (bottom). The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0 (top left), 25% (top right), 50% (middle left), 75% middle right) and 100% (bottom). The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0 (top left), 25% (top right), 50% (middle left), 75% middle right) and 100% (bottom). The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0 (top left), 25% (top right), 50% (middle left), 75% middle right) and 100% (bottom). The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0 (top left), 25% (top right), 50% (middle left), 75% middle right) and 100% (bottom). The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0 (top left), 25% (top right), 50% (middle left), 75% middle right) and 100% (bottom). The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0 (top left), 25% (top right), 50% (middle left), 75% middle right) and 100% (bottom). The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the wino NLSP grid for negative values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the wino NLSP grid for negative values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the wino NLSP grid for negative values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the wino NLSP grid for negative values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the wino NLSP grid for negative values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the wino NLSP grid for negative values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the wino NLSP grid for negative values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the wino NLSP grid for positive values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the wino NLSP grid for positive values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the wino NLSP grid for positive values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the wino NLSP grid for positive values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the wino NLSP grid for positive values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the wino NLSP grid for positive values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the wino NLSP grid for positive values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the well-tempered neutralino grid for the $m_{q3L}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the well-tempered neutralino grid for the $m_{q3L}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the well-tempered neutralino grid for the $m_{q3L}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the well-tempered neutralino grid for the $m_{q3L}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the well-tempered neutralino grid for the $m_{q3L}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the well-tempered neutralino grid for the $m_{q3L}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the well-tempered neutralino grid for the $m_{q3L}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the well-tempered neutralino grid for the $m_{tR}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the well-tempered neutralino grid for the $m_{tR}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the well-tempered neutralino grid for the $m_{tR}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the well-tempered neutralino grid for the $m_{tR}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the well-tempered neutralino grid for the $m_{tR}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the well-tempered neutralino grid for the $m_{tR}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the well-tempered neutralino grid for the $m_{tR}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with large tan$\beta$ (top left) is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with large tan$\beta$ (top left) is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with large tan$\beta$ (top left) is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with large tan$\beta$ (top left) is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with large tan$\beta$ (top left) is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with large tan$\beta$ (top left) is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with large tan$\beta$ (top left) is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with small tan$\beta$ are shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with small tan$\beta$ are shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with small tan$\beta$ are shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with small tan$\beta$ are shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with small tan$\beta$ are shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with small tan$\beta$ are shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with small tan$\beta$ are shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenario with a mostly right-handed top squark partner is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenario with a mostly right-handed top squark partner is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenario with a mostly right-handed top squark partner is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenario with a mostly right-handed top squark partner is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenario with a mostly right-handed top squark partner is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenario with a mostly right-handed top squark partner is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenario with a mostly right-handed top squark partner is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Acceptance for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Acceptance for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Acceptance for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Acceptance for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Acceptance for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Acceptance for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Acceptance for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Acceptance for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Acceptance for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Acceptance for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Acceptance for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Acceptance for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Acceptance for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Acceptance for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Acceptance for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Acceptance for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Acceptance for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Acceptance for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Acceptance for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Acceptance for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Acceptance for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Efficiencies for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Efficiencies for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Efficiencies for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Efficiencies for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Efficiencies for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Efficiencies for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Efficiencies for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Efficiencies for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Efficiencies for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Efficiencies for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Efficiencies for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Efficiencies for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Efficiencies for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Efficiencies for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Efficiencies for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Efficiencies for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Efficiencies for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Efficiencies for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Efficiencies for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Efficiencies for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Efficiencies for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Upper limit cross-section, in femtobarn, for the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ grid.
Upper limit cross-section, in femtobarn, for the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ grid.
Upper limit cross-section, in femtobarn, for the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ grid.
Upper limit cross-section, in femtobarn, for the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ grid.
Upper limit cross-section, in femtobarn, for the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ grid.
Upper limit cross-section, in femtobarn, for the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ grid.
Upper limit cross-section, in femtobarn, for the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ grid.
Upper limit cross-section, in femtobarn, for the $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft grid.
Upper limit cross-section, in femtobarn, for the $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft grid.
Upper limit cross-section, in femtobarn, for the $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft grid.
Upper limit cross-section, in femtobarn, for the $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft grid.
Upper limit cross-section, in femtobarn, for the $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft grid.
Upper limit cross-section, in femtobarn, for the $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft grid.
Upper limit cross-section, in femtobarn, for the $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft grid.
Cutflow for SRA for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (800,1) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRA for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (800,1) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRA for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (800,1) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRA for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (800,1) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRA for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (800,1) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRA for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (800,1) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRA for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (800,1) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow SRB for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (600,300) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow SRB for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (600,300) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow SRB for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (600,300) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow SRB for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (600,300) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow SRB for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (600,300) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow SRB for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (600,300) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow SRB for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (600,300) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRC1 and SRC2 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (250,77) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRC1 and SRC2 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (250,77) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRC1 and SRC2 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (250,77) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRC1 and SRC2 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (250,77) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRC1 and SRC2 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (250,77) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRC1 and SRC2 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (250,77) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRC1 and SRC2 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (250,77) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRC3, SRC4, and SRC5 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (500,327) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRC3, SRC4, and SRC5 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (500,327) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRC3, SRC4, and SRC5 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (500,327) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRC3, SRC4, and SRC5 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (500,327) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRC3, SRC4, and SRC5 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (500,327) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRC3, SRC4, and SRC5 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (500,327) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRC3, SRC4, and SRC5 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (500,327) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRD-high for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV with $m(\tilde{t}_1,\tilde\chi^{\pm}_1)=$ (800,100) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRD-high for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV with $m(\tilde{b}_1,\tilde\chi^{\pm}_1)=$ (750,200) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRD-high for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV with $m(\tilde{b}_1,\tilde\chi^{\pm}_1)=$ (750,200) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRD-high for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV with $m(\tilde{b}_1,\tilde\chi^{\pm}_1)=$ (750,200) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRD-high for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV with $m(\tilde{b}_1,\tilde\chi^{\pm}_1)=$ (800,100) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRD-high for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV with $m(\tilde{b}_1,\tilde\chi^{\pm}_1)=$ (750,200) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRD-high for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV with $m(\tilde{b}_1,\tilde\chi^{\pm}_1)=$ (750,200) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRD-low for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV witht $m(\tilde{t}_1,\tilde\chi^{\pm}_1)=$ (600,200) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRD-low for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV witht $m(\tilde{b}_1,\tilde\chi^{\pm}_1)=$ (400,200) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRD-low for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV witht $m(\tilde{b}_1,\tilde\chi^{\pm}_1)=$ (400,200) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRD-low for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV witht $m(\tilde{b}_1,\tilde\chi^{\pm}_1)=$ (400,200) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRD-low for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV witht $m(\tilde{b}_1,\tilde\chi^{\pm}_1)=$ (600,200) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRD-low for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV witht $m(\tilde{b}_1,\tilde\chi^{\pm}_1)=$ (400,200) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRD-low for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV witht $m(\tilde{b}_1,\tilde\chi^{\pm}_1)=$ (400,200) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRE for a signal model with gluino pair production in the case where both gluinos decay via $\tilde{g}\to t\tilde{t}_1\to t\tilde\chi^0_1+$soft and $\Delta m(\tilde{t}_1, \tilde\chi^0_1)=5$ GeV with $m(\tilde{g},\tilde{t}_1)=$ (1700,400) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRE for a signal model with gluino pair production in the case where both gluinos decay via $\tilde{g}\to t\tilde{t}_1\to t\tilde\chi^0_1+$soft and $\Delta m(\tilde{t}_1, \tilde\chi^0_1)=5$ GeV with $m(\tilde{g},\tilde{t}_1)=$ (1700,400) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRE for a signal model with gluino pair production in the case where both gluinos decay via $\tilde{g}\to t\tilde{t}_1\to t\tilde\chi^0_1+$soft and $\Delta m(\tilde{t}_1, \tilde\chi^0_1)=5$ GeV with $m(\tilde{g},\tilde{t}_1)=$ (1700,400) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRE for a signal model with gluino pair production in the case where both gluinos decay via $\tilde{g}\to t\tilde{t}_1\to t\tilde\chi^0_1+$soft and $\Delta m(\tilde{t}_1, \tilde\chi^0_1)=5$ GeV with $m(\tilde{g},\tilde{t}_1)=$ (1700,400) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRE for a signal model with gluino pair production in the case where both gluinos decay via $\tilde{g}\to t\tilde{t}_1\to t\tilde\chi^0_1+$soft and $\Delta m(\tilde{t}_1, \tilde\chi^0_1)=5$ GeV with $m(\tilde{g},\tilde{t}_1)=$ (1700,400) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRE for a signal model with gluino pair production in the case where both gluinos decay via $\tilde{g}\to t\tilde{t}_1\to t\tilde\chi^0_1+$soft and $\Delta m(\tilde{t}_1, \tilde\chi^0_1)=5$ GeV with $m(\tilde{g},\tilde{t}_1)=$ (1700,400) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRE for a signal model with gluino pair production in the case where both gluinos decay via $\tilde{g}\to t\tilde{t}_1\to t\tilde\chi^0_1+$soft and $\Delta m(\tilde{t}_1, \tilde\chi^0_1)=5$ GeV with $m(\tilde{g},\tilde{t}_1)=$ (1700,400) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
The results of a search for new heavy $W^\prime$ bosons decaying to an electron or muon and a neutrino using proton-proton collision data at a centre-of-mass energy of $\sqrt{s} = 13$ TeV are presented. The dataset was collected in 2015 and 2016 by the ATLAS experiment at the Large Hadron Collider and corresponds to an integrated luminosity of 36.1 fb$^{-1}$. As no excess of events above the Standard Model prediction is observed, the results are used to set upper limits on the $W^\prime$ boson cross-section times branching ratio to an electron or muon and a neutrino as a function of the $W^\prime$ mass. Assuming a $W^\prime$ boson with the same couplings as the Standard Model $W$ boson, $W^\prime$ masses below 5.1 TeV are excluded at the 95% confidence level.
Transverse mass distribution for events satisfying all selection criteria in the electron channel.
Transverse mass distribution for events satisfying all selection criteria in the electron channel.
Transverse mass distribution for events satisfying all selection criteria in the muon channel.
Transverse mass distribution for events satisfying all selection criteria in the muon channel.
Upper limits at the 95% CL on the cross section for SSM W' production and decay to the electron+neutrino channel as a function of the W' pole mass.
Upper limits at the 95% CL on the cross section for SSM W' production and decay to the electron+neutrino channel as a function of the W' pole mass.
Upper limits at the 95% CL on the cross section for SSM W' production and decay to the muon+neutrino channel as a function of the W' pole mass.
Upper limits at the 95% CL on the cross section for SSM W' production and decay to the muon+neutrino channel as a function of the W' pole mass.
Combined (electron and muon channels) upper limits at the 95% CL on the cross section for SSM W' production and decay to a single lepton generation as a function of the W' pole mass.
Combined (electron and muon channels) upper limits at the 95% CL on the cross section for SSM W' production and decay to a single lepton generation as a function of the W' pole mass.
Product of acceptance and efficiency for the electron and muon selections as a function of the W' pole mass.
Product of acceptance and efficiency for the electron and muon selections as a function of the W' pole mass.
Detailed measurements of $t$-channel single top-quark production are presented. They use 20.2 fb$^{-1}$ of data collected by the ATLAS experiment in proton-proton collisions at a centre-of-mass energy of 8 TeV at the LHC. Total, fiducial and differential cross-sections are measured for both top-quark and top-antiquark production. The fiducial cross-section is measured with a precision of 5.8 % (top quark) and 7.8 % (top antiquark), respectively. The total cross-sections are measured to be $\sigma_{\mathrm{tot}}(tq) = 56.7^{+4.3}_{-3.8}\;$pb for top-quark production and $\sigma_{\mathrm{tot}}(\bar{t}q) = 32.9^{+3.0}_{-2.7}\;$pb for top-antiquark production, in agreement with the Standard Model prediction. In addition, the ratio of top-quark to top-antiquark production cross-sections is determined to be $R_t=1.72 \pm 0.09$, with an improved relative precision of 4.9 % since several systematic uncertainties cancel in the ratio. The differential cross-sections as a function of the transverse momentum and rapidity of both the top quark and the top antiquark are measured at both the parton and particle levels. The transverse momentum and rapidity differential cross-sections of the accompanying jet from the $t$-channel scattering are measured at particle level. All measurements are compared to various Monte Carlo predictions as well as to fixed-order QCD calculations where available.
Predicted and observed event yields for the signal region (SR). The multijet background prediction is obtained from a binned maximum-likelihood fit to the $E_{\mathrm{T}}^{\mathrm{miss}}$ distribution. All the other predictions are derived using theoretical cross-sections, given for the backgrounds in Sect. 6 and for the signal in Sect. 1. The quoted uncertainties are in the predicted cross-sections or in the number of multijet events, in case of the multijet process.
Predicted and observed event yields for the signal region (SR). The multijet background prediction is obtained from a binned maximum-likelihood fit to the $E_{\mathrm{T}}^{\mathrm{miss}}$ distribution. All the other predictions are derived using theoretical cross-sections, given for the backgrounds in Sect. 6 and for the signal in Sect. 1. The quoted uncertainties are in the predicted cross-sections or in the number of multijet events, in case of the multijet process.
Definition of the fiducial phase space.
Definition of the fiducial phase space.
The seven input variables to the NN ordered by their discriminating power. The jet that is not $b$-tagged is referred to as $\textit{untagged}~$jet.
The seven input variables to the NN ordered by their discriminating power. The jet that is not $b$-tagged is referred to as $\textit{untagged}~$jet.
Event yields for the different processes estimated with the fit to the $O_\mathrm{NN}$ distribution compared to the numbers of observed events. Only the statistical uncertainties are quoted. The $Z,VV+\mathrm{jets}$ contributions and the multijet background are fixed in the fit; therefore no uncertainty is quoted for these processes.
Event yields for the different processes estimated with the fit to the $O_\mathrm{NN}$ distribution compared to the numbers of observed events. Only the statistical uncertainties are quoted. The $Z,VV+\mathrm{jets}$ contributions and the multijet background are fixed in the fit; therefore no uncertainty is quoted for these processes.
Detailed list of the contribution from each source of uncertainty to the total uncertainty in the measured values of $\sigma_{\mathrm{fid}}(tq)$ and $\sigma_{\mathrm{fid}}(\bar tq)$. The estimation of the systematic uncertainties has a statistical uncertainty of $0.3\%$. Uncertainties contributing less than $0.5\%$ are marked with ‘<0.5’.
Detailed list of the contribution from each source of uncertainty to the total uncertainty in the measured values of $\sigma_{\mathrm{fid}}(tq)$ and $\sigma_{\mathrm{fid}}(\bar tq)$. The estimation of the systematic uncertainties has a statistical uncertainty of $0.3\%$. Uncertainties contributing less than $0.5\%$ are marked with ‘<0.5’.
Significant contributions to the total relative uncertainty in the measured value of $R_{t}$. The estimation of the systematic uncertainties has a statistical uncertainty of $0.3~\%$. Uncertainties contributing less than $0.5~\%$ are not shown.
Significant contributions to the total relative uncertainty in the measured value of $R_{t}$. The estimation of the systematic uncertainties has a statistical uncertainty of $0.3~\%$. Uncertainties contributing less than $0.5~\%$ are not shown.
Slopes $a$ of the mass dependence of the measured cross$-$sections.
Slopes $a$ of the mass dependence of the measured cross$-$sections.
Predicted (post-fit) and observed event yields for the signal region (SR), after the requirement on the neural network discriminant, $O_{\mathrm{NN}}~>~0.8$. The multijet background prediction is obtained from the fit to the $E_{\mathrm{T}}^{\mathrm{miss}}$ distribution described in Section 6, while all the other predictions and uncertainties are derived from the total cross$-$section measurement. In some cases there is no uncertainty quoted. In these cases the uncertainty is < 0.5.
Predicted (post-fit) and observed event yields for the signal region (SR), after the requirement on the neural network discriminant, $O_{\mathrm{NN}}~>~0.8$. The multijet background prediction is obtained from the fit to the $E_{\mathrm{T}}^{\mathrm{miss}}$ distribution described in Section 6, while all the other predictions and uncertainties are derived from the total cross$-$section measurement. In some cases there is no uncertainty quoted. In these cases the uncertainty is < 0.5.
Predicted (post-fit) and observed event yields for the signal region (SR), after the requirement on the second neural network discriminant, $O_{\mathrm{NN2}}~>~0.8$. The multijet background prediction is obtained from the fit to the $E_{\mathrm{T}}^{\mathrm{miss}}$ distribution described in Section 6, while all the other predictions and uncertainties are derived from the total cross$-$section measurement. In some cases there is no uncertainty quoted. In these cases the uncertainty is < 0.5.
Predicted (post-fit) and observed event yields for the signal region (SR), after the requirement on the second neural network discriminant, $O_{\mathrm{NN2}}~>~0.8$. The multijet background prediction is obtained from the fit to the $E_{\mathrm{T}}^{\mathrm{miss}}$ distribution described in Section 6, while all the other predictions and uncertainties are derived from the total cross$-$section measurement. In some cases there is no uncertainty quoted. In these cases the uncertainty is < 0.5.
Migration matrix for $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ at the particle level. The pseudo top quark is shown on the $y$-axis and the reconstructed variable is shown on the $x$-axis.
Migration matrix for $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ at the particle level. The pseudo top quark is shown on the $y$-axis and the reconstructed variable is shown on the $x$-axis.
Migration matrix for $p_{\mathrm{T}}(t)$ at the parton level. The parton-level quark is shown on the $y$-axis and the reconstructed variable is shown on the $x$-axis.
Migration matrix for $p_{\mathrm{T}}(t)$ at the parton level. The parton-level quark is shown on the $y$-axis and the reconstructed variable is shown on the $x$-axis.
Migration matrix for $|y(\hat{t\hspace{-0.2mm}})|$ at the particle level. The pseudo top quark is shown on the $y$-axis and the reconstructed variable is shown on the $x$-axis.
Migration matrix for $|y(\hat{t\hspace{-0.2mm}})|$ at the particle level. The pseudo top quark is shown on the $y$-axis and the reconstructed variable is shown on the $x$-axis.
Migration matrix for $|y(t)|$ at the parton level. The parton-level quark is shown on the $y$-axis and the reconstructed variable is shown on the $x$-axis.
Migration matrix for $|y(t)|$ at the parton level. The parton-level quark is shown on the $y$-axis and the reconstructed variable is shown on the $x$-axis.
Uncertainties in the normalisations of the different backgrounds for all processes, as derived from the total cross-section measurement.
Uncertainties in the normalisations of the different backgrounds for all processes, as derived from the total cross-section measurement.
Absolute and normalised unfolded differential $tq$ production cross$-$section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ at particle level.
Absolute and normalised unfolded differential $tq$ production cross$-$section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ at particle level.
Absolute and normalised unfolded differential $\bar tq$ production cross$-$section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ at particle level.
Absolute and normalised unfolded differential $\bar tq$ production cross$-$section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ at particle level.
Absolute and normalised unfolded differential $tq$ production cross$-$section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ at particle level.
Absolute and normalised unfolded differential $tq$ production cross$-$section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ at particle level.
Absolute and normalised unfolded differential $\bar tq$ production cross$-$section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ at particle level.
Absolute and normalised unfolded differential $\bar tq$ production cross$-$section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ at particle level.
Absolute and normalised unfolded differential $tq$ production cross$-$section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ at particle level.
Absolute and normalised unfolded differential $tq$ production cross$-$section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ at particle level.
Absolute and normalised unfolded differential $\bar tq$ production cross$-$section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ at particle level.
Absolute and normalised unfolded differential $\bar tq$ production cross$-$section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ at particle level.
Absolute and normalised unfolded differential $tq$ production cross$-$section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ at particle level.
Absolute and normalised unfolded differential $tq$ production cross$-$section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ at particle level.
Absolute and normalised unfolded differential $\bar tq$ production cross$-$section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ at particle level.
Absolute and normalised unfolded differential $\bar tq$ production cross$-$section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ at particle level.
Absolute and normalised unfolded differential $tq$ production cross$-$section as a function of $p_{\mathrm{T}}(t)$ at parton level.
Absolute and normalised unfolded differential $tq$ production cross$-$section as a function of $p_{\mathrm{T}}(t)$ at parton level.
Absolute and normalised unfolded differential $\bar tq$ production cross$-$section as a function of $p_{\mathrm{T}}(t)$ at parton level.
Absolute and normalised unfolded differential $\bar tq$ production cross$-$section as a function of $p_{\mathrm{T}}(t)$ at parton level.
Absolute and normalised unfolded differential $tq$ production cross$-$section as a function of $|y(t)|$ at parton level.
Absolute and normalised unfolded differential $tq$ production cross$-$section as a function of $|y(t)|$ at parton level.
Absolute and normalised unfolded differential $\bar tq$ production cross$-$section as a function of $|y(t)|$ at parton level.
Absolute and normalised unfolded differential $\bar tq$ production cross$-$section as a function of $|y(t)|$ at parton level.
Statistical correlation matrix for the absolute differential cross-section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ for $tq$ events(at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.
Statistical correlation matrix for the absolute differential cross-section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ for $ \bar tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.
Statistical correlation matrix for the normalised differential cross-section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ for $tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.
Statistical correlation matrix for the normalised differential cross-section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ for $\bar tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.
Statistical correlation matrix for the absolute differential cross-section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ for $tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.
Statistical correlation matrix for the absolute differential cross-section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ for $ \bar tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.
Statistical correlation matrix for the normalised differential cross-section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ for $tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.
Statistical correlation matrix for the normalised differential cross-section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ for $\bar tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.
Statistical correlation matrix for the absolute differential cross-section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ for $tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.
Statistical correlation matrix for the absolute differential cross-section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ for $\bar tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.
Statistical correlation matrix for the normalised differential cross-section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ for $tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.
Statistical correlation matrix for the normalised differential cross-section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ for $\bar tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.
Statistical correlation matrix for the absolute differential cross-section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ for $tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.
Statistical correlation matrix for the absolute differential cross-section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ for $\bar tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.
Statistical correlation matrix for the normalised differential cross-section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ for $tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.
Statistical correlation matrix for the normalised differential cross-section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ for $\bar tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.
Statistical correlation matrix for the absolute differential cross-section as a function of $p_{\mathrm{T}}(t)$ for $tq$ events (at the parton level). It includes the statistical uncertainty due to the number of data events and MC statistics.
Statistical correlation matrix for the absolute differential cross-section as a function of $p_{\mathrm{T}}(t)$ for $ \bar tq$ events (at the parton level). It includes the statistical uncertainty due to the number of data events and MC statistics.
Statistical correlation matrix for the normalised differential cross-section as a function of $p_{\mathrm{T}}(t)$ for $tq$ events (at the parton level). It includes the statistical uncertainty due to the number of data events and MC statistics.
Statistical correlation matrix for the normalised differential cross-section as a function of $p_{\mathrm{T}}(t)$ for $ \bar tq$ events (at the parton level). It includes the statistical uncertainty due to the number of data events and MC statistics.
Statistical correlation matrix for the absolute differential cross-section as a function of $|y(t)|$ for $tq$ events (at the parton level). It includes the statistical uncertainty due to the number of data events and MC statistics.
Statistical correlation matrix for the absolute differential cross-section as a function of $|y(t)|$ for $\bar tq$ events (at the parton level). It includes the statistical uncertainty due to the number of data events and MC statistics.
Statistical correlation matrix for the normalised differential cross-section as a function of $|y(t)|$ for $tq$ events (at the parton level). It includes the statistical uncertainty due to the number of data events and MC statistics.
Statistical correlation matrix for the normalised differential cross-section as a function of $|y(t)|$ for $\bar tq$ events (at the parton level). It includes the statistical uncertainty due to the number of data events and MC statistics.
Fiducial acceptance $A_{\mathrm{fid}}$ for different $t$-channel single top-quark MC samples. $^{\mathrm{(a)}}$ Calculation taken from AcerMC $+$ $\mathrm{P{\scriptsize YTHIA}6}$. $^{\mathrm{(b)}}$ Calculation taken from $\mathrm{P{\scriptsize OWHEG}}$-$\mathrm{B{\scriptsize OX}}$ $+$ $\mathrm{P{\scriptsize YTHIA}6}$.
Fiducial acceptance $A_{\mathrm{fid}}$ for different $t$-channel single top-antiquark MC samples. $^{\mathrm{(a)}}$ Calculation taken from AcerMC $+$ $\mathrm{P{\scriptsize YTHIA}6}$. $^{\mathrm{(b)}}$ Calculation taken from $\mathrm{P{\scriptsize OWHEG}}$-$\mathrm{B{\scriptsize OX}}$ $+$ $\mathrm{P{\scriptsize YTHIA}6}$.
Uncertainties for the absolute differential $tq$ cross-section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ at particle level per bin ([0,35,50,75,100,150,200,300] GeV) in percent of $\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.
Uncertainties for the normalised differential $tq$ cross-section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ at particle level per bin ([0,35,50,75,100,150,200,300] GeV) in percent of $\left( \dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.
Uncertainties for the absolute differential $\bar tq$ cross-section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ at particle level per bin ([0,35,50,75,100,150,300] GeV) in percent of $\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})}$.
Uncertainties for the normalised differential $\bar tq$ cross-section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ at particle level per bin ([0,35,50,75,100,150,300] GeV) in percent of $\left( \dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})}$.
Uncertainties for the absolute differential $tq$ cross-section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ at particle level per bin ([0,0.15,0.3,0.45,0.7,1.0,1.3,2.2]) in percent of $\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}|y(\hat{t\hspace{-0.2mm}})|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.
Uncertainties for the normalised differential $tq$ cross-section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ at particle level per bin ([0,0.15,0.3,0.45,0.7,1.0,1.3,2.2]) in percent of $\left(\dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}|y(\hat{t\hspace{-0.2mm}})|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.
Uncertainties for the absolute differential $\bar tq$ cross-section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ at particle level per bin ([0,0.15,0.3,0.45,0.7,1.0,1.3,2.2]) in percent of $\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}|y(\hat{t\hspace{-0.2mm}})|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.
Uncertainties for the normalised differential $\bar tq$ cross-section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ at particle level per bin ([0,0.15,0.3,0.45,0.7,1.0,1.3,2.2]) in percent of $\left(\dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}|y(\hat{t\hspace{-0.2mm}})|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.
Uncertainties for the absolute differential $tq$ cross-section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ at particle level per bin ([30,45,60,75,100,150,300] GeV) in percent of $\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.
Uncertainties for the normalised differential $tq$ cross-section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ at particle level per bin ([30,45,60,75,100,150,300] GeV) in percent of $\left(\dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.
Uncertainties for the absolute differential $\bar tq$ cross-section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ at particle level per bin ([30,45,60,75,100,150,300] GeV) in percent of $\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.
Uncertainties for the normalised differential $\bar tq$ cross-section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ at particle level per bin ([30,45,60,75,100,150,300] GeV) in percent of $\left(\dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.
Uncertainties for the absolute differential $tq$ cross-section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ at particle level per bin ([0.0, 1.2, 1.7, 2.2, 2.7, 3.3, 4.5]) in percent of $\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}|y(\hat{j\hspace{-0.2mm}})|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.
Uncertainties for the normalised differential $tq$ cross-section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ at particle level per bin ([0.0, 1.2, 1.7, 2.2, 2.7, 3.3, 4.5]) in percent of $\left(\dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}|y(\hat{j\hspace{-0.2mm}})|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.
Uncertainties for the absolute differential $\bar tq$ cross-section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ at particle level per bin ([0.0, 1.2, 1.7, 2.2, 2.7, 3.3, 4.5]) in percent of $\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}|y(\hat{j\hspace{-0.2mm}})|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.
Uncertainties for the normalised differential $\bar tq$ cross-section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ at particle level per bin ([0.0, 1.2, 1.7, 2.2, 2.7, 3.3, 4.5]) in percent of $\left(\dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}|y(\hat{j\hspace{-0.2mm}})|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.
Uncertainties for the absolute differential $tq$ cross-section as a function of $p_{\mathrm{T}}(t)$ at parton level per bin ([0,50,100,150,200,300] GeV) in percent of $\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}p_{\mathrm{T}}(t)}$.
Uncertainties for the normalised differential $tq$ cross-section as a function of $p_{\mathrm{T}}(t)$ at parton level per bin ([0,50,100,150,200,300] GeV) in percent of $\left(\dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}p_{\mathrm{T}}(t)}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.
Uncertainties for the absolute differential $\bar tq $ cross-section as a function of $p_{\mathrm{T}}(t)$ at parton level per bin ([0,50,100,150,300] GeV) in percent of $\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}p_{\mathrm{T}}(t)}$.
Uncertainties for the normalised differential $\bar tq $ cross-section as a function of $p_{\mathrm{T}}(t)$ at parton level per bin ([0,50,100,150,300] GeV) in percent of $\left(\dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}p_{\mathrm{T}}(t)}$.
Uncertainties for the absolute differential $ tq $ cross-section as a function of $|y(t)|$ at parton level per bin ([0,0.3,0.7,1.3,2.2]) in percent of $\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}|y(t)|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.
Uncertainties for the normalised differential $ tq $ cross-section as a function of $|y(t)|$ at parton level per bin ([0,0.3,0.7,1.3,2.2]) in percent of $\left(\dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}|y(t)|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.
Uncertainties for the absolute differential $ \bar tq $ cross-section as a function of $|y(t)|$ at parton level per bin ([0,0.3,0.7,1.3,2.2]) in percent of $\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}|y(t)|}$.
Uncertainties for the normalised differential $ \bar tq $ cross-section as a function of $|y(t)|$ at parton level per bin ([0,0.3,0.7,1.3,2.2]) in percent of $\left(\dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}|y(t)|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.
Two searches for new phenomena in final states containing a same-flavour opposite-lepton (electron or muon) pair, jets, and large missing transverse momentum are presented. These searches make use of proton--proton collision data, collected during 2015 and 2016 at a centre-of-mass energy $\sqrt{s}=13$ TeV by the ATLAS detector at the Large Hadron Collider, which correspond to an integrated luminosity of 14.7 fb$^{-1}$. Both searches target the pair production of supersymmetric particles, squarks or gluinos, which decay to final states containing a same-flavour opposite-sign lepton pair via one of two mechanisms: a leptonically decaying Z boson in the final state, leading to a peak in the dilepton invariant-mass distribution around the Z boson mass; and decays of neutralinos (e.g. $\tilde{\chi}_2^0 \rightarrow \ell^+\ell^- \tilde{\chi}_1^0$), yielding a kinematic endpoint in the dilepton invariant-mass spectrum. The data are found to be consistent with the Standard Model expectation. Results are interpreted in simplified models of gluino-pair (squark-pair) production, and provide sensitivity to gluinos (squarks) with masses as large as 1.70 TeV (980 GeV).
Dilepton invariant mass distribution in SRZ.
Dilepton transverse momentum distribution in SRZ.
Missing transverse momentum distribution in SRZ.
HT inclusive distribution in SRZ.
Jet multiplicity distribution in SRZ.
B-tagged jet multiplicity distribution in SRZ.
Dilepton invariant mass distribution in SRMedium.
Dilepton invariant mass distribution in SRMedium.
Dilepton invariant mass in SRHigh.
Expected 95% exclusion contour for the gluino simplified model with fixed N1 mass and decays to quarks and Z bosons in SRZ.
Observed 95% exclusion contour for the gluino simplified model with fixed N1 mass and decays to quarks and Z bosons in SRZ.
Expected 95% exclusion contour for the squark simplified model with fixed N1 mass and decays to quarks and Z bosons in SRZ.
Observed 95% exclusion contour for the squark simplified model with fixed N1 mass and decays to quarks and Z bosons in SRZ.
Expected 95% exclusion contour for the gluino simplified model with varying N1 mass and decays to quarks and Z bosons in SRZ.
Observed 95% exclusion contour for the gluino simplified model with varying N1 mass and decays to quarks and Z bosons in SRZ.
Expected 95% exclusion contour for the gluino simplified model with sleptons in the edge SRs.
Observed 95% exclusion contour for the gluino simplified model with sleptons in the edge SRs.
Expected 95% exclusion contour for the gluino simplified model with decays to on- or off-shell Z bosons in the edge SRs.
Observed 95% exclusion contour for the gluino simplified model with decays to on- or off-shell Z bosons in the edge SRs.
Expected 95% exclusion contour for the gluino simplified model with decays to on- or off-shell Z bosons in SRZ.
Observed 95% exclusion contour for the gluino simplified model with decays to on- or off-shell Z bosons in SRZ.
Cutflow table for three benchmark signal points from the $\tilde{g}$--$\chi_{2}^{0}$ on-shell grid in SRZ for the $ee$ and $\mu\mu$ channels separately. The number of generated events is N RAW, while N WEIGHTED corresponds to the number of events expected in 14.7/fb, after all MC simulation corrections have been applied.
Cutflow table for three benchmark signal points for the slepton model in SR-low, SR-medium and SR-high for the $ee$ and $\mu\mu$ channels separately. The number of generated events is N RAW, while N WEIGHTED corresponds to the number of events expected in 14.7/fb, after all MC simulation corrections have been applied. The event generation was filtered to require at least two leptons (electrons or muons) with $p_{T}>5$ GeV and $|\eta|<2.8$, with 20000 events required to pass the filter. The corresponding number of unfiltered events is provided in the ``Pre-filter events'' row of the table.
Signal acceptance for the gluino simplified model with decays to quarks and Z bosons in SRZ.
Signal efficiency for the gluino simplified model with decays to quarks and Z bosons in SRZ.
Signal acceptance for the gluino simplified model with decays via sleptons in SRLow.
Signal efficiency for the gluino simplified model with decays via sleptons in SRLow.
Signal acceptance for the gluino simplified model with decays via sleptons in SRMedium.
Signal efficiency for the gluino simplified model with decays via sleptons in SRMedium.
Signal acceptance for the gluino simplified model with decays via sleptons in SRHigh.
Signal efficiency for the gluino simplified model with decays via sleptons in SRHigh.
Upper limits on the signal cross-section at 95% CL for the gluino simplified model with fixed N1 mass and decays to quarks and Z bosons in SRZ.
Upper limits on the signal cross-section at 95% CL for the squark simplified model with fixed N1 mass and decays to quarks and Z bosons in SRZ.
Upper limits on the signal cross-section at 95% CL for the gluino simplified model with varying N1 mass and decays to quarks and Z bosons in SRZ.
Upper limits on the signal cross-section at 95% CL for the gluino simplified model with decays via sleptons.
Upper limits on the signal cross-section at 95% CL for the gluino simplified model with decays to on-shell or off-shell Z bosons.
A search for supersymmetry in events with large missing transverse momentum, jets, and at least one hadronically decaying tau lepton has been performed using 3.2 fb$^{-1}$ of proton-proton collision data at $\sqrt{s}=13$ TeV recorded by the ATLAS detector at the Large Hadron Collider in 2015. Two exclusive final states are considered, with either exactly one or at least two tau leptons. No excess over the Standard Model prediction is observed in the data. Results are interpreted in the context of gauge-mediated supersymmetry breaking and a simplified model of gluino pair production with tau-rich cascade decays, substantially improving on previous limits. In the GMSB model considered, supersymmetry-breaking scale ($\Lambda$) values below 92 TeV are excluded at the 95% confidence level, corresponding to gluino masses below 2000 GeV. For large values of $\tan\beta$, values of $\Lambda$ up to 107 TeV and gluino masses up to 2300 GeV are excluded. In the simplified model, gluino masses are excluded up to 1570 GeV for neutralino masses around 100 GeV. Neutralino masses up to 700 GeV are excluded for all gluino masses between 800 GeV and 1500 GeV, while the strongest exclusion of 750 GeV is achieved for gluino masses around 1400 GeV.
mTtau distributions for "extended SR selections" of the 1 tau channel, for the Compressed SR selection without the mTtau > 80 GeV requirement. The last bin includes overflow events. Uncertainties are statistical only. Signal predictions are overlaid for several benchmark models, normalised to their predicted cross sections. For the simplified model, "LM" refers to a low mass splitting, or compressed scenario, with m(gluino)=665 GeV and m(neutralino)=585 GeV; "MM" stands for a medium mass splitting, with m(gluino)=1145 GeV and m(neutralino)=265 GeV; "HM" denotes a high mass splitting scenario, with m(gluino)=1305 GeV and m(neutralino)=105 GeV.
mTtau distributions for "extended SR selections" of the 1 tau channel, for the Medium Mass SR selection without the mTtau > 200 GeV requirement. The last bin includes overflow events. Uncertainties are statistical only. Signal predictions are overlaid for several benchmark models, normalised to their predicted cross sections. For the simplified model, "LM" refers to a low mass splitting, or compressed scenario, with m(gluino)=665 GeV and m(neutralino)=585 GeV; "MM" stands for a medium mass splitting, with m(gluino)=1145 GeV and m(neutralino)=265 GeV; "HM" denotes a high mass splitting scenario, with m(gluino)=1305 GeV and m(neutralino)=105 GeV.
mTtau distributions for "extended SR selections" of the 1 tau channel, for the High Mass SR selection without the mTtau > 200 GeV requirement. The last bin includes overflow events. Uncertainties are statistical only. Signal predictions are overlaid for several benchmark models, normalised to their predicted cross sections. For the simplified model, "LM" refers to a low mass splitting, or compressed scenario, with m(gluino)=665 GeV and m(neutralino)=585 GeV; "MM" stands for a medium mass splitting, with m(gluino)=1145 GeV and m(neutralino)=265 GeV; "HM" denotes a high mass splitting scenario, with m(gluino)=1305 GeV and m(neutralino)=105 GeV.
Kinematic distributions for "extended SR selections" of the 2-tau channel, for mTsum in the Compressed SR selection without the mTsum>1400 GeV requirement. The last bin includes overflow events. Cited uncertainties are statistical uncertainties only. Signal predictions are overlaid for several benchmark models, normalised to their predicted cross sections. For the simplified model, "MM" refers to a medium mass splitting, with m(gluino)=1145 GeV and m(neutralino)=265 GeV; "HM" denotes a high mass splitting scenario, with m(gluino)=1305 GeV and m(neutralino)=105 GeV. The GMSB benchmark model corresponds to Lambda = 90 TeV and tanbeta = 40.
Kinematic distributions for "extended SR selections" of the 2-tau channel, for mTtau1+mTtau2 in the High-Mass SR selection without the mTtau1+mTtau2>350GeV requirement. The last bin includes overflow events. Cited uncertainties are statistical uncertainties only. Signal predictions are overlaid for several benchmark models, normalised to their predicted cross sections. For the simplified model, "MM" refers to a medium mass splitting, with m(gluino)=1145 GeV and m(neutralino)=265 GeV; "HM" denotes a high mass splitting scenario, with m(gluino)=1305 GeV and m(neutralino)=105 GeV. The GMSB benchmark model corresponds to Lambda = 90 TeV and tanbeta = 40.
Kinematic distributions for "extended SR selections" of the 2-tau channel, for HT in the GMSB SR selection without the HT > 1700 GeV requirement. The last bin includes overflow events. Cited uncertainties are statistical uncertainties only. Signal predictions are overlaid for several benchmark models, normalised to their predicted cross sections. For the simplified model, "MM" refers to a medium mass splitting, with m(gluino)=1145 GeV and m(neutralino)=265 GeV; "HM" denotes a high mass splitting scenario, with m(gluino)=1305 GeV and m(neutralino)=105 GeV. The GMSB benchmark model corresponds to Lambda = 90 TeV and tanbeta = 40.
Expected exclusion contour at the 95% confidence level for the simplified model of gluino pair production, based on the combined results from the 1tau and 2tau channel. The result is obtained using 3.2 fb-1 of sqrt(s) = 13 TeV ATLAS data.
Observed exclusion contour at the 95% confidence level for the simplified model of gluino pair production, based on the combined results from the 1tau and 2tau channel. The result is obtained using 3.2 fb-1 of sqrt(s) = 13 TeV ATLAS data.
Expected exclusion contour at the 95% confidence level for the simplified model of gluino pair production, based on results from the 2tau channel. The result is obtained using 3.2 fb-1 of sqrt(s) = 13 TeV ATLAS data.
Expected exclusion contour at the 95% confidence level for the simplified model of gluino pair production, based on results from the 1tau channel. The result is obtained using 3.2 fb-1 of sqrt(s) = 13 TeV ATLAS data.
Observed exclusion contours at the 95% confidence level for the gauge-mediated supersymmetry-breaking model, based on results from the 2 tau channel. The result is obtained using 3.2 fb-1 of sqrt(s) = 13 TeV ATLAS data. Additional model parameters are M(mess) = 250 TeV, N5 = 3, mu>0 and Cgrav =1.
Expected exclusion contours at the 95% confidence level for the gauge-mediated supersymmetry-breaking model, based on results from the 2 tau channel. The result is obtained using 3.2 fb-1 of sqrt(s) = 13 TeV ATLAS data. Additional model parameters are M(mess) = 250 TeV, N5 = 3, mu>0 and Cgrav =1.
Observed upper cross section limits in pb for the simplified model of gluino pair production for the combination of all SRs.
Best expected signal region for the simplified model of gluino pair production. The respective SR has been used in the combination of the results.
Acceptance for the gluino production simplified model grid in the Compressed 1tau signal region.
Efficiency for the gluino production simplified model grid in the Compressed 1tau signal region.
Acceptance times Efficiency for the gluino production simplified model grid in the Compressed 1tau signal region.
Acceptance for the gluino production simplified model grid in the medium mass 1tau signal region.
Efficiency for the gluino production simplified model grid in the medium mass 1tau signal region.
Acceptance times Efficiency for the gluino production simplified model grid in the medium mass 1tau signal region.
Acceptance for the gluino production simplified model grid in the high mass 1tau signal region.
Efficiency for the gluino production simplified model grid in the high mass 1tau signal region.
Acceptance times Efficiency for the gluino production simplified model grid in the high mass 1tau signal region.
Acceptance for the gluino production simplified model grid in the compressed 2tau signal region.
Efficiency for the gluino production simplified model grid in the compressed 2tau signal region.
Acceptance times Efficiency for the gluino production simplified model grid in the compressed 2tau signal region.
Acceptance for the gluino production simplified model grid in the high mass 2tau signal region.
Efficiency for the gluino production simplified model grid in the high mass 2tau signal region.
Acceptance times Efficiency for the gluino production simplified model grid in the high mass 2tau signal region.
Acceptance for the GMSB model grid in the 2tau signal region.
Efficiency for the GMSB model grid in the 2tau signal region.
Acceptance times Efficiency for the GMSB model grid in the 2tau signal region.
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