Showing 10 of 30 results
Measurements of the yield and nuclear modification factor, $R_\mathrm{ AA}$, for inclusive jet production are performed using 0.49 nb$^{-1}$ of Pb+Pb data at $\sqrt{s_\mathrm{NN}} = 5.02$ TeV and 25 pb$^{-1}$ of $pp$ data at $\sqrt{s}=5.02$ TeV with the ATLAS detector at the LHC. Jets are reconstructed with the anti-$k_t$ algorithm with radius parameter $R=0.4$ and are measured over the transverse momentum range of 40-1000 GeV in six rapidity intervals covering $|y|<2.8$. The magnitude of $R_\mathrm{ AA}$ increases with increasing jet transverse momentum, reaching a value of approximately 0.6 at 1 TeV in the most central collisions. The magnitude of $R_\mathrm{ AA}$ also increases towards peripheral collisions. The value of $R_\mathrm{ AA}$ is independent of rapidity at low jet transverse momenta, but it is observed to decrease with increasing rapidity at high transverse momenta.
The ⟨TAA⟩ and ⟨Npart⟩ values and their uncertainties in each centrality bin.
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This Letter presents a search for the production of a long-lived neutral particle ($Z_d$) decaying within the ATLAS hadronic calorimeter, in association with a Standard Model (SM) $Z$ boson produced via an intermediate scalar boson, where $Z\to l^+l^-$ ($l=e,\mu$). The data used were collected by the ATLAS detector during 2015 and 2016 $pp$ collisions with a center-of-mass energy of $\sqrt{s} = 13$ TeV at the Large Hadron Collider and corresponds to an integrated luminosity of $36.1\pm0.8$ fb$^{-1}$. No significant excess of events is observed above the expected background. Limits on the production cross section of the scalar boson times its decay branching fraction into the long-lived neutral particle are derived as a function of the mass of the intermediate scalar boson, the mass of the long-lived neutral particle, and its $c\tau$ from a few centimeters to one hundred meters. In the case that the intermediate scalar boson is the SM Higgs boson, its decay branching fraction to a long-lived neutral particle with a $c\tau$ approximately between 0.1 m and 7 m is excluded with a 95% confidence level up to 10% for $m_{Z_d}$ between 5 and 15 GeV.
The product of acceptance and efficiency for all signal MC samples.
A search for supersymmetric partners of top quarks decaying as $\tilde{t}_1\to c\tilde\chi^0_1$ and supersymmetric partners of charm quarks decaying as $\tilde{c}_1\to c\tilde\chi^0_1$, where $\tilde\chi^0_1$ is the lightest neutralino, is presented. The search uses 36.1 ${\rm fb}^{-1}$ $pp$ collision data at a centre-of-mass energy of 13 TeV collected by the ATLAS experiment at the Large Hadron Collider and is performed in final states with jets identified as containing charm hadrons. Assuming a 100% branching ratio to $c\tilde\chi^0_1$, top and charm squarks with masses up to 850 GeV are excluded at 95% confidence level for a massless lightest neutralino. For $m_{\tilde{t}_1,\tilde{c}_1}-m_{\tilde\chi^0_1}
Acceptance for best expected CLS SR in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Acceptance for SR1 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Acceptance for SR1 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Acceptance for SR1 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Acceptance for SR2 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Acceptance for SR2 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Acceptance for SR2 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Acceptance for SR3 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Acceptance for SR3 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Acceptance for SR3 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Acceptance for SR4 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Acceptance for SR4 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Acceptance for SR4 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Acceptance for SR5 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Acceptance for SR5 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Acceptance for SR5 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Acceptance for best expected CLS SR in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Acceptance for best expected CLS SR in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Detector efficiency for best expected CLS SR in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Detector efficiency for SR1 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Detector efficiency for SR1 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Detector efficiency for SR1 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Detector efficiency for SR2 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Detector efficiency for SR2 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Detector efficiency for SR2 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Detector efficiency for SR3 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Detector efficiency for SR3 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Detector efficiency for SR3 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Detector efficiency for SR4 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Detector efficiency for SR4 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Detector efficiency for SR4 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Detector efficiency for SR5 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Detector efficiency for SR5 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Detector efficiency for SR5 in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Detector efficiency for best expected CLS SR in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Detector efficiency for best expected CLS SR in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
Expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
Expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
Observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
Observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
Observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
SR1 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
SR1 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
SR1 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
SR1 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
SR1 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
SR1 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
SR2 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
SR2 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
SR2 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
SR2 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
SR2 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
SR2 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
SR3 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
SR3 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
SR3 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
SR3 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
SR3 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
SR3 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
SR4 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
SR4 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
SR4 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
SR4 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
SR4 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
SR4 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
SR5 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
SR5 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
SR5 expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
SR5 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
SR5 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
SR5 observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
Upper limits on signal cross sections and exclusion limits at 95% CL for the best expected SR in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
Upper limits on signal cross sections and exclusion limits at 95% CL for SR1 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
Upper limits on signal cross sections and exclusion limits at 95% CL for SR1 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
Upper limits on signal cross sections and exclusion limits at 95% CL for SR1 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
Upper limits on signal cross sections and exclusion limits at 95% CL for SR2 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
Upper limits on signal cross sections and exclusion limits at 95% CL for SR2 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
Upper limits on signal cross sections and exclusion limits at 95% CL for SR2 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
Upper limits on signal cross sections and exclusion limits at 95% CL for SR3 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
Upper limits on signal cross sections and exclusion limits at 95% CL for SR3 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
Upper limits on signal cross sections and exclusion limits at 95% CL for SR3 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
Upper limits on signal cross sections and exclusion limits at 95% CL for SR4 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
Upper limits on signal cross sections and exclusion limits at 95% CL for SR4 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
Upper limits on signal cross sections and exclusion limits at 95% CL for SR4 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
Upper limits on signal cross sections and exclusion limits at 95% CL for SR5 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
Upper limits on signal cross sections and exclusion limits at 95% CL for SR5 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
Upper limits on signal cross sections and exclusion limits at 95% CL for SR5 in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
Upper limits on signal cross sections and exclusion limits at 95% CL for the best expected SR in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
Upper limits on signal cross sections and exclusion limits at 95% CL for the best expected SR in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
Minimum branching ratio excluded at 95% CL, assuming no sensitivity for other decay possibilities, in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
Minimum branching ratio excluded at 95% CL, assuming no sensitivity for other decay possibilities, in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
Minimum branching ratio excluded at 95% CL, assuming no sensitivity for other decay possibilities, in the $m(\tilde t_1/\tilde c_1)$-$m(\tilde\chi^0_1)$ plane for the stop/scharm pair production scenario.
The signal region with the best expected CLS value for each signal in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
The signal region with the best expected CLS value for each signal in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
The signal region with the best expected CLS value for each signal in the $\tilde{t}_1/\tilde{c}_1-\tilde{\chi}_1^0$ mass plane.
Expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$\Delta m$ plane for the stop/scharm pair production scenario.
Expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$\Delta m$ plane for the stop/scharm pair production scenario.
Expected exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$\Delta m$ plane for the stop/scharm pair production scenario.
Observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$\Delta m$ plane for the stop/scharm pair production scenario.
Observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$\Delta m$ plane for the stop/scharm pair production scenario.
Observed exclusion limit at 95% CL in the $m(\tilde t_1/\tilde c_1)$-$\Delta m$ plane for the stop/scharm pair production scenario.
Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR1. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.
Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR1. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.
Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR1. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.
Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR2. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.
Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR2. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.
Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR2. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.
Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR3. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.
Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR3. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.
Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR3. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.
Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR4. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.
Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR4. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.
Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR4. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.
Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR5. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.
Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR5. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.
Comparison between data and expectation after the background-only fit for the $E_{T}^{miss}$ distribution in SR5. The shaded band indicates detector-related systematic uncertainties and the statistical uncertainties of the MC samples, while the error bars on the data points indicate the data's statistical uncertainty. The final bin in each histogram includes the overflow. The lower panel shows the ratio of the data to the SM prediction after the background-only fit. The distribution is also shown for a representative signal point.
Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (450,425)$ GeV signal point for signal region SR1.
Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (450,425)$ GeV signal point for signal region SR1.
Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (450,425)$ GeV signal point for signal region SR1.
Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (500,420)$ GeV signal point for signal region SR2.
Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (500,420)$ GeV signal point for signal region SR2.
Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (500,420)$ GeV signal point for signal region SR2.
Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (500,350)$ GeV signal point for signal region SR3.
Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (500,350)$ GeV signal point for signal region SR3.
Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (500,350)$ GeV signal point for signal region SR3.
Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (600,350)$ GeV signal point for signal region SR4.
Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (600,350)$ GeV signal point for signal region SR4.
Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (600,350)$ GeV signal point for signal region SR4.
Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (900,1)$ GeV signal point for signal region SR5.
Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (900,1)$ GeV signal point for signal region SR5.
Cutflow for the $(m_{\tilde{t}}, m_{\tilde{\chi}}) = (900,1)$ GeV signal point for signal region SR5.
A search for new phenomena in final states containing an $e^+e^-$ or $\mu^+\mu^-$ pair, jets, and large missing transverse momentum is presented. This analysis makes use of proton--proton collision data with an integrated luminosity of $36.1 \; \mathrm{fb}^{-1}$, collected during 2015 and 2016 at a centre-of-mass energy $\sqrt{s}$ = 13 TeV with the ATLAS detector at the Large Hadron Collider. The search targets the pair production of supersymmetric coloured particles (squarks or gluinos) and their decays into final states containing an $e^+e^-$ or $\mu^+\mu^-$ pair and the lightest neutralino ($\tilde{\chi}_1^0$) via one of two next-to-lightest neutralino ($\tilde{\chi}_2^0$) decay mechanisms: $\tilde{\chi}_2^0 \rightarrow Z \tilde{\chi}_1^0$, where the $Z$ boson decays leptonically leading to a peak in the dilepton invariant mass distribution around the $Z$ boson mass; and $\tilde{\chi}_2^0 \rightarrow \ell^+\ell^- \tilde{\chi}_1^0$ with no intermediate $\ell^+\ell^-$ resonance, 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 using simplified models, and exclude gluinos and squarks with masses as large as 1.85 TeV and 1.3 TeV at 95% confidence level, respectively.
Observed and expected dilepton mass distributions, with the bin boundaries considered for the interpretation, in SR-low. All statistical and systematic uncertainties of the expected background are included in the hatched band. An example signal from the slepton model with m(gluino) = 1200 GeV and m(neutralino1) = 900 GeV is overlaid.
Observed and expected dilepton mass distributions, with the bin boundaries considered for the interpretation, in SR-med. All statistical and systematic uncertainties of the expected background are included in the hatched band. An example signal from the slepton model with m(gluino) = 1600 GeV and m(neutralino1) = 900 GeV, and from an on-$Z$ model with m(gluino) = 1640 GeV and m(neutralino1) = 1160 GeV, is overlaid.
Observed and expected dilepton mass distributions, with the bin boundaries considered for the interpretation, in SR-high. All statistical and systematic uncertainties of the expected background are included in the hatched band. An example signal from the slepton model with m(gluino) = 1800 GeV and m(neutralino1) = 500 GeV, and from an on-$Z$ model with m(gluino) = 1650 GeV and m(neutralino1) = 550 GeV, is overlaid.
Observed and expected dilepton mass distributions, with the bin boundaries considered for the interpretation, in SRC of the low-pT edge search. All statistical and systematic uncertainties of the expected background are included in the hatched band. An example signal from the $Z^{*}$ model with m(gluino) = 1000 GeV and m(neutralino1) = 900 GeV is overlaid.
Observed and expected dilepton mass distributions, with the bin boundaries considered for the interpretation, in SRC-MET of the low-pT edge search. All statistical and systematic uncertainties of the expected background are included in the hatched band. An example signal from the $Z^{*}$ model with m(gluino) = 1000 GeV and m(neutralino1) = 900 GeV is overlaid.
Observed 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
Expected 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
Observed 95% CL exclusion contours from the low-p$_{T}$ signal regions on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
Expected 95% CL exclusion contours from the low-p$_{T}$ signal regions on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
Observed 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson and the lightest neutralino.
Expected 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson and the lightest neutralino.
Observed 95% CL exclusion contours from the low-p$_{T}$ signal regions on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson and the lightest neutralino.
Expected 95% CL exclusion contours from the low-p$_{T}$ signal regions on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson and the lightest neutralino.
Observed 95% CL exclusion contours from the on-Z signal regions on the gluino and next-to-lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.
Expected 95% CL exclusion contours from the on-Z signal regions on the gluino and next-to-lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.
Observed 95% CL exclusion contours from the on-Z signal regions on the squark and next-to-lightest neutralino masses in a SUSY scenario where squarks are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.
Expected 95% CL exclusion contours from the on-Z signal regions on the squark and next-to-lightest neutralino masses in a SUSY scenario where squarks are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.
Observed 95% CL exclusion contours from the on-Z signal regions on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson the lightest neutralino.
Expected 95% CL exclusion contours from the on-Z signal regions on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and the lightest neutralino.
Acceptance and efficiency in the on-Z bin for SR-medium for the SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.
Acceptance and efficiency in the on-Z bin for SR-high for the SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.
Acceptance and efficiency over the full $m_{ll}$ range for SR-low for a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
Acceptance and efficiency over the full $m_{ll}$ range for SR-medium for a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
Acceptance and efficiency over the full $m_{ll}$ range for SR-high for a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
Acceptance and efficiency over the full $m_{ll}$ range for SRC for a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
Acceptance and efficiency over the full $m_{ll}$ range for SRC-MET for a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the on-Z $m_{ll}$ windows of SR-medium and SR-high, SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.
The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the on-Z $m_{ll}$ windows of SR-medium and SR-high, SUSY scenario where squarks are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.
The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the on-Z $m_{ll}$ windows of SR-medium and SR-high, in a SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson the lightest neutralino.
The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the signal regions, in a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the low-p$_{T}$ signal regions, in a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the signal regions, in a SUSYscenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson.
The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the low-p$_{T}$ signal regions, in a SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson.
Cutflow table for three benchmark signal points from the SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino, with m(gluino) = 1395 GeV and m(neutralino2) = 505 GeV, m(gluino) = 920 GeV and m(neutralino2) = 230 GeV and m(gluino) = 940 GeV and m(neutralino2) = 660 GeV, in the on-$Z$ $m_{ll}$ bins of SR-medium and SR-high for the electron and muon channels separately. The numbers are normalized to a luminosity of 36.1 fb$^{-1}$.
Cutflow table for a signal point from the SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino, with m(gluino) = 1000 GeV and m(neutralino1) = 800 GeV, m(gluino) = 1200 GeV and m(neutralino1) = 500 GeV and m(gluino) = 1400 GeV and m(neutralino1) = 100 GeV, in all m_{ll}$ bins of SR-low, SR-medium and SR-high for the electron and muon channels separately. The numbers are normalized to a luminosity of 36.1 fb$^{-1}$.
Cutflow table for a signal point from the SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson, with m(gluino) = 600 GeV and m(neutralino1) = 560 GeV and m(gluino) = 1000 GeV and m(neutralino1) = 960 GeV, in all $m_{ll}$ bins of SRC and SRC-MET for the electron and muon channels separately. The numbers are normalized to a luminosity of 36.1 fb$^{-1}$.
Signal region used to derive the exclusion limit for the SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino, corresponding to the SR determined to give the best expected limit for a given signal point.
Signal region used to derive the exclusion limit for the SUSY scenario where squarks are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino, corresponding to the SR determined to give the best expected limit for a given signal point.
Signal region used to derive the exclusion limit for the SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson the lightest neutralino, corresponding to the SR determined to give the best expected limit for a given signal point.
Signal region used to derive the exclusion limit for the SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson, corresponding to the SR determined to give the best expected limit for a given signal point.
Low-$p_{T}$ signal region used to derive the exclusion limit in the compressed region for the SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson, corresponding to the SR determined to give the best expected limit for a given signal point.
Signal region used to derive the exclusion limit for the SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino, corresponding to the SR determined to give the best expected limit for a given signal point.
Low-$p_{T}$ signal region used to derive the exclusion limit for the SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino, corresponding to the SR determined to give the best expected limit for a given signal point.
A search for high-mass resonances decaying to $\tau\nu$ using proton-proton collisions at $\sqrt{s}$ = 13 TeV produced by the Large Hadron Collider is presented. Only $\tau$-lepton decays with hadrons in the final state are considered. The data were recorded with the ATLAS detector and correspond to an integrated luminosity of 36.1 fb$^{-1}$. No statistically significant excess above the Standard Model expectation is observed; model-independent upper limits are set on the visible $\tau\nu$ production cross section. Heavy $W^{\prime}$ bosons with masses less than 3.7 TeV in the Sequential Standard Model and masses less than 2.2-3.8 TeV depending on the coupling in the non-universal G(221) model are excluded at the 95% credibility level.
Observed and predicted $m_{\rm T}$ distributions including SSM and NU (cot$\phi$ = 5.5) $W^{\prime}$ signals with masses of 3 TeV. Please note that in the paper figure the bin content is divided by the bin width, but this is not done in the HepData table.
Observed and predicted $m_{\rm T}$ distributions including SSM and NU (cot$\phi$ = 5.5) $W^{\prime}$ signals with masses of 3 TeV. Please note that in the paper figure the bin content is divided by the bin width, but this is not done in the HepData table.
Observed and predicted $m_{\rm T}$ distributions including SSM and NU (cot$\phi$ = 5.5) $W^{\prime}$ signals with masses of 3 TeV. Please note that in the paper figure the bin content is divided by the bin width, but this is not done in the HepData table. The table also contains each background contribution to the Standard Model expectation separately with their statistical uncertainties.
Number of expected Standard Model background events including total statistical and systematic uncertainty added in quadrature (calculated before applying the statistical fitting procedure), number of observed events, and the observed and expected 95% CL upper limits on the visible $\tau\nu$ production cross section, $\sigma_{\rm vis} = \sigma(pp \to \tau\nu +X) \cdot \mathcal{A} \cdot \varepsilon$, for $m_{\rm T}$ thresholds ranging from 250 to 1800 GeV. See HepData abstract for details on how to use this data for reinterpretation.
Number of expected Standard Model background events including total statistical and systematic uncertainty added in quadrature (calculated before applying the statistical fitting procedure), number of observed events, and the observed and expected 95% CL upper limits on the visible $\tau\nu$ production cross section, $\sigma_{\rm vis} = \sigma(pp \to \tau\nu +X) \cdot \mathcal{A} \cdot \varepsilon$, for $m_{\rm T}$ thresholds ranging from 250 to 1800 GeV. See HepData abstract for details on how to use this data for reinterpretation.
Number of expected Standard Model background events including total statistical and systematic uncertainty added in quadrature (calculated before applying the statistical fitting procedure), number of observed events, and the observed and expected 95% CL upper limits on the visible $\tau\nu$ production cross section, $\sigma_{\rm vis} = \sigma(pp \to \tau\nu +X) \cdot \mathcal{A} \cdot \varepsilon$, for $m_{\rm T}$ thresholds ranging from 250 to 1800 GeV. See HepData abstract for details on how to use this data for reinterpretation.
Observed and expected 95% CL upper limits on cross section times $\tau\nu$ branching fraction for $W^{\prime}_{\rm SSM}$.
Observed and expected 95% CL upper limits on cross section times $\tau\nu$ branching fraction for $W^{\prime}_{\rm SSM}$.
Observed and expected 95% CL upper limits on cross section times $\tau\nu$ branching fraction for $W^{\prime}_{\rm SSM}$.
Regions of the non-universal G(221) parameter space excluded at 95% CL.
Regions of the non-universal G(221) parameter space excluded at 95% CL.
Regions of the non-universal G(221) parameter space excluded at 95% CL.
Number of expected $W^{\prime}_{\rm SSM}$, $W^{\prime}_{\rm NU}$, Standard Model background and observed events passing the optimal $m_{\rm T}$ threshold for each considered signal mass hypothesis. The expectations include the total statistical and systematic uncertainty added in quadrature. The yields and uncertainties are calculated before applying the statistical fitting procedure.
Number of expected $W^{\prime}_{\rm SSM}$, $W^{\prime}_{\rm NU}$, Standard Model background and observed events passing the optimal $m_{\rm T}$ threshold for each considered signal mass hypothesis. The expectations include the total statistical and systematic uncertainty added in quadrature. The yields and uncertainties are calculated before applying the statistical fitting procedure.
Number of expected $W^{\prime}_{\rm SSM}$, $W^{\prime}_{\rm NU}$, Standard Model background and observed events passing the optimal $m_{\rm T}$ threshold for each considered signal mass hypothesis. The expectations include the total statistical and systematic uncertainty added in quadrature. The yields and uncertainties are calculated before applying the statistical fitting procedure.
Acceptance for $W^{\prime}_{\rm SSM}$ as a function of the $W^{\prime}_{\rm SSM}$ mass, shown after successively applying selection at generator-level. The acceptance times efficiency is calculated with respect to all $W^{\prime}_{\rm SSM} \to \tau\nu$ events with a generated $\tau\nu$ mass above 120 GeV. The "selected tau" criteria include the requirement of a $\tau_{\rm had-vis}$ with $p_{\rm T}$ > 50 GeV and $|\eta|$ < 2.4. The $m_{\rm T}$ threshold for each $W^{\prime}_{\rm SSM}$ mass is defined in Table 5.
Acceptance for $W^{\prime}_{\rm SSM}$ as a function of the $W^{\prime}_{\rm SSM}$ mass, shown after successively applying selection at generator-level. The acceptance times efficiency is calculated with respect to all $W^{\prime}_{\rm SSM} \to \tau\nu$ events with a generated $\tau\nu$ mass above 120 GeV. The "selected tau" criteria include the requirement of a $\tau_{\rm had-vis}$ with $p_{\rm T}$ > 50 GeV and $|\eta|$ < 2.4. The $m_{\rm T}$ threshold for each $W^{\prime}_{\rm SSM}$ mass is defined in Table 5.
Acceptance for $W^{\prime}_{\rm SSM}$ as a function of the $W^{\prime}_{\rm SSM}$ mass, shown after successively applying selection at generator-level. The acceptance times efficiency is calculated with respect to all $W^{\prime}_{\rm SSM} \to \tau\nu$ events with a generated $\tau\nu$ mass above 120 GeV. The "selected tau" criteria include the requirement of a $\tau_{\rm had-vis}$ with $p_{\rm T}$ > 50 GeV and $|\eta|$ < 2.4. The $m_{\rm T}$ threshold for each $W^{\prime}_{\rm SSM}$ mass is defined in Table 5.
Acceptance times efficiency for $W^{\prime}_{\rm SSM}$ as a function of the $W^{\prime}_{\rm SSM}$ mass, shown after successively applying selection at reconstruction-level. The acceptance times efficiency is calculated with respect to all $W^{\prime}_{\rm SSM} \to \tau\nu$ events with a generated $\tau\nu$ mass above 120 GeV. "Preselection" includes all criteria prior to those shown. The $m_{\rm T}$ threshold for each $W^{\prime}_{\rm SSM}$ mass is defined in Table 5.
Acceptance times efficiency for $W^{\prime}_{\rm SSM}$ as a function of the $W^{\prime}_{\rm SSM}$ mass, shown after successively applying selection at reconstruction-level. The acceptance times efficiency is calculated with respect to all $W^{\prime}_{\rm SSM} \to \tau\nu$ events with a generated $\tau\nu$ mass above 120 GeV. "Preselection" includes all criteria prior to those shown. The $m_{\rm T}$ threshold for each $W^{\prime}_{\rm SSM}$ mass is defined in Table 5.
Acceptance times efficiency for $W^{\prime}_{\rm SSM}$ as a function of the $W^{\prime}_{\rm SSM}$ mass, shown after successively applying selection at reconstruction-level. The acceptance times efficiency is calculated with respect to all $W^{\prime}_{\rm SSM} \to \tau\nu$ events with a generated $\tau\nu$ mass above 120 GeV. "Preselection" includes all criteria prior to those shown. The $m_{\rm T}$ threshold for each $W^{\prime}_{\rm SSM}$ mass is defined in Table 5.
Reconstruction efficiency as a function of $m_{\rm T}$ (see HepData abstract for parameterization), defined as the ratio of the number of $\tau\nu$ events remaining after applying the full selection at reconstruction-level to those remaining after applying the fiducial selection at generator-level. The efficiency is largely model independent, with an uncertainty of ~10% due to model choice.
Reconstruction efficiency as a function of $m_{\rm T}$ (see HepData abstract for parameterization), defined as the ratio of the number of $\tau\nu$ events remaining after applying the full selection at reconstruction-level to those remaining after applying the fiducial selection at generator-level. The efficiency is largely model independent, with an uncertainty of ~10% due to model choice.
Reconstruction efficiency as a function of $m_{\rm T}$ (see HepData abstract for parameterization), defined as the ratio of the number of $\tau\nu$ events remaining after applying the full selection at reconstruction-level to those remaining after applying the fiducial selection at generator-level. The efficiency is largely model independent, with an uncertainty of ~10% due to model choice.
Inclusive and differential cross-sections for the production of a top-quark pair in association with a photon are measured with proton-proton collision data corresponding to an integrated luminosity of 36.1 fb$^{-1}$, collected by the ATLAS detector at the LHC in 2015 and 2016 at a centre-of-mass energy of 13 TeV. The measurements are performed in single-lepton and dilepton final states in a fiducial volume. Events with exactly one photon, one or two leptons, a channel-dependent minimum number of jets, and at least one $b$-jet are selected. Neural network algorithms are used to separate the signal from the backgrounds. The fiducial cross-sections are measured to be 521 $\pm$ 9(stat.) $\pm$ 41(sys.) fb and 69 $\pm$ 3(stat.) $\pm$ 4(sys.) fb for the single-lepton and dilepton channels, respectively. The differential cross-sections are measured as a function of photon transverse momentum, photon absolute pseudorapidity, and angular distance between the photon and its closest lepton in both channels, as well as azimuthal opening angle and absolute pseudorapidity difference between the two leptons in the dilepton channel. All measurements are in agreement with the theoretical predictions.
The measured fiducial cross section in the single lepton channel. The first uncertainty is the statistical uncertainty and the second one is the systematic uncertainty.
The measured fiducial cross section in the dilepton channel. The first uncertainty is the statistical uncertainty and the second one is the systematic uncertainty.
The measured normalized differential cross section as a function of the photon pT in the single lepton channel. The uncertainty is decomposed into five components which are the signal modelling uncertainty, the experimental uncertainty, the ttbar modelling uncertainty, the other background estimation uncertainty, and the data statistical uncertainty.
The measured normalized differential cross section as a function of the photon $|\eta|$ in the single lepton channel. The uncertainty is decomposed into five components which are the signal modelling uncertainty, the experimental uncertainty, the ttbar modelling uncertainty, the other background estimation uncertainty, and the data statistical uncertainty.
The measured normalized differential cross section as a function of the $\Delta R$ between the photon and the lepton in the single lepton channel. The uncertainty is decomposed into five components which are the signal modelling uncertainty, the experimental uncertainty, the ttbar modelling uncertainty, the other background estimation uncertainty, and the data statistical uncertainty.
The measured normalized differential cross section as a function of the photon pT in the dilepton channel. The uncertainty is decomposed into five components which are the signal modelling uncertainty, the experimental uncertainty, the ttbar modelling uncertainty, the other background estimation uncertainty, and the data statistical uncertainty.
The measured normalized differential cross section as a function of the photon $|\eta|$ in the dilepton channel. The uncertainty is decomposed into five components which are the signal modelling uncertainty, the experimental uncertainty, the ttbar modelling uncertainty, the other background estimation uncertainty, and the data statistical uncertainty.
The measured normalized differential cross section as a function of minimum $\Delta R) between the photon and the leptons in the dilepton channel. The uncertainty is decomposed into five components which are the signal modelling uncertainty, the experimental uncertainty, the ttbar modelling uncertainty, the other background estimation uncertainty, and the data statistical uncertainty.
The measured normalized differential cross section as a function of $|\Delta\eta|$ between the two leptons in the dilepton channel. The uncertainty is decomposed into five components which are the signal modelling uncertainty, the experimental uncertainty, the ttbar modelling uncertainty, the other background estimation uncertainty, and the data statistical uncertainty.
The measured normalized differential cross section as a function of $\Delta\phi$ between the two leptons in the dilepton channel. The uncertainty is decomposed into five components which are the signal modelling uncertainty, the experimental uncertainty, the ttbar modelling uncertainty, the other background estimation uncertainty, and the data statistical uncertainty.
The total correlation matrix of the measured normalized differential cross section as a function of the photon pT in the single lepton channel. The individual systematic uncertainties are symmetrized before deriving the correlation matrix.
The total correlation matrix of the measured normalized differential cross section as a function of the photon $|\eta|$ in the single lepton channel. The individual systematic uncertainties are symmetrized before deriving the correlation matrix.
The total correlation matrix of the measured normalized differential cross section as a function of the $\Delta R$ between the photon and the lepton in the single lepton channel. The individual systematic uncertainties are symmetrized before deriving the correlation matrix.
The total correlation matrix of the measured normalized differential cross section as a function of the photon pT in the dilepton channel. The individual systematic uncertainties are symmetrized before deriving the correlation matrix.
The total correlation matrix of the measured normalized differential cross section as a function of the photon $|\eta|$ in the dilepton channel. The individual systematic uncertainties are symmetrized before deriving the correlation matrix.
The total correlation matrix of the measured normalized differential cross section as a function of the minimum $\Delta R$ between the photon and the leptons in the dilepton channel. The individual systematic uncertainties are symmetrized before deriving the correlation matrix.
The total correlation matrix of the measured normalized differential cross section as a function of the $|\Delta\eta|$ between the two leptons in the dilepton channel. The individual systematic uncertainties are symmetrized before deriving the correlation matrix.
The total correlation matrix of the measured normalized differential cross section as a function of the $\Delta\phi$ between the two leptons in the dilepton channel. The individual systematic uncertainties are symmetrized before deriving the correlation matrix.
The statistical correlation matrix of all the measured normalized differential cross sections in the single lepton channel.
The statistical correlation matrix of all the measured normalized differential cross sections in the dilepton channel.
The inclusive production rates of isolated, prompt photons in $p$+Pb collisions at $\sqrt{s_\mathrm{NN}} = 8.16$ TeV are studied with the ATLAS detector at the Large Hadron Collider using a dataset with an integrated luminosity of 165 nb$^{-1}$ recorded in 2016. The cross-section and nuclear modification factor $R_{p\mathrm{Pb}}$ are measured as a function of photon transverse energy from 20 GeV to 550 GeV and in three nucleon-nucleon centre-of-mass pseudorapidity regions, (-2.83,-2.02), (-1.84,0.91), and (1.09,1.90). The cross-section and $R_{p\mathrm{Pb}}$ values are compared with the results of a next-to-leading-order perturbative QCD calculation, with and without nuclear parton distribution function modifications, and with expectations based on a model of the energy loss of partons prior to the hard scattering. The data disfavour a large amount of energy loss and provide new constraints on the parton densities in nuclei.
The measured cross sections for prompt, isolated photons with rapidity in (1.09,1.90).
The measured cross sections for prompt, isolated photons with rapidity in (−1.84,0.91).
The measured cross sections for prompt, isolated photons with rapidity in (−2.83,−2.02).
The nuclear modification factor R_pPb for prompt, isolated photons with rapidity in (1.09,1.90).
The nuclear modification factor R_pPb for prompt, isolated photons with rapidity in (−1.84,0.91).
The nuclear modification factor R_pPb for prompt, isolated photons with rapidity in (−2.83,−2.02).
The ratio of R_{pPb} from rapidity (1.09,1.90) to that of rapidity (−2.83,−2.02).
This paper describes precision measurements of the transverse momentum $p_\mathrm{T}^{\ell\ell}$ ($\ell=e,\mu$) and of the angular variable $\phi^{*}_{\eta}$ distributions of Drell-Yan lepton pairs in a mass range of 66-116 GeV. The analysis uses data from 36.1 fb$^{-1}$ of proton-proton collisions at a centre-of-mass energy of $\sqrt{s}=13$ TeV collected by the ATLAS experiment at the LHC in 2015 and 2016. Measurements in electron-pair and muon-pair final states are performed in the same fiducial volumes, corrected for detector effects, and combined. Compared to previous measurements in proton-proton collisions at $\sqrt{s}=$7 and 8 TeV, these new measurements probe perturbative QCD at a higher centre-of-mass energy with a different composition of initial states. They reach a precision of 0.2% for the normalized spectra at low values of $p_\mathrm{T}^{\ell\ell}$. The data are compared with different QCD predictions, where it is found that predictions based on resummation approaches can describe the full spectrum within uncertainties.
Selected signal candidate events in data for both decay channels as well as the expected background contributions including their total uncertainties.
Selected signal candidate events in data for both decay channels as well as the expected background contributions including their total uncertainties.
Overview of the detector efficiency correction factors, $C_{Z}$ , for the electron and muon channels and their systematic uncertainty contributions.
Overview of the detector efficiency correction factors, $C_{Z}$ , for the electron and muon channels and their systematic uncertainty contributions.
Measured inclusive cross-section in the fiducial volume in the electron and muon decay channels at Born level and their combination as well as the theory prediction at NNLO in $\alpha_{s}$ using the CT14 PDF set.
Measured inclusive cross-section in the fiducial volume in the electron and muon decay channels at Born level and their combination as well as the theory prediction at NNLO in $\alpha_{s}$ using the CT14 PDF set.
The measured combined normalized differential cross-sections, divided by the bin-width, in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle level.
The measured combined normalized differential cross-sections, divided by the bin-width, in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle level.
The measured combined normalized differential cross-sections, divided by the bin-width, in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle level.
The measured combined normalized differential cross-sections, divided by the bin-width, in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle level.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid}\times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}p_{T}^{ll}$ measured on born level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid}\times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}p_{T}^{ll}$ measured on born level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid}\times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}\phi_{\eta}^{*}$ measured on born level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid}\times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}\phi_{\eta}^{*}$ measured on born level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid}\times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}p_{T}^{ll}$ measured on born level for the $Z\rightarrow ee$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) and Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. for the electron momentum scale and resolution uncertainties; Elec. (Reco), Elec. (ID), Isolation, Trigger and Charge-ID denote the correlated uncertainties of the data/MC scale-factors for the electron reconstruction, identification, isolation, trigger and charge-identification efficiencies; The uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid}\times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}p_{T}^{ll}$ measured on born level for the $Z\rightarrow ee$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) and Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. for the electron momentum scale and resolution uncertainties; Elec. (Reco), Elec. (ID), Isolation, Trigger and Charge-ID denote the correlated uncertainties of the data/MC scale-factors for the electron reconstruction, identification, isolation, trigger and charge-identification efficiencies; The uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid} \times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}\phi_{\eta}^{*}$ measured on born level for the $Z\rightarrow ee$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) and Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. for the electron momentum scale and resolution uncertainties; Elec. (Reco), Elec. (ID), Isolation, Trigger and Charge-ID denote the correlated uncertainties of the data/MC scale-factors for the electron reconstruction, identification, isolation, trigger and charge-identification efficiencies; The uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid} \times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}\phi_{\eta}^{*}$ measured on born level for the $Z\rightarrow ee$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) and Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. for the electron momentum scale and resolution uncertainties; Elec. (Reco), Elec. (ID), Isolation, Trigger and Charge-ID denote the correlated uncertainties of the data/MC scale-factors for the electron reconstruction, identification, isolation, trigger and charge-identification efficiencies; The uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid} \times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}p_{T}^{ll}$ measured on bare level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid} \times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}p_{T}^{ll}$ measured on bare level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid} \times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}\phi_{\eta}^{*}$ measured on bare level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid} \times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}\phi_{\eta}^{*}$ measured on bare level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Measured combined normalized differential cross-section in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle.
Measured combined normalized differential cross-section in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle.
Measured combined normalized differential cross-section in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle.
Measured combined normalized differential cross-section in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle.
The distribution of events passing the selection requirements in the electron channel as a function of dilepton invariant mass $m_{ll}$ , the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the electron channel as a function of dilepton invariant mass $m_{ll}$ , the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of dilepton invariant mass $m_{ll}$, the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of dilepton invariant mass $m_{ll}$, the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the electron channel as a function of lepton pseudorapidity $\eta$, the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the electron channel as a function of lepton pseudorapidity $\eta$, the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of lepton pseudorapidity $\eta$, the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of lepton pseudorapidity $\eta$, the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the electron channel as a function of dilepton transverse momentum. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the electron channel as a function of dilepton transverse momentum. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of dilepton transverse momentum. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of dilepton transverse momentum. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the electron channel as a function of $\phi_{\eta}^{*}$. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the electron channel as a function of $\phi_{\eta}^{*}$. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of $\phi_{\eta}^{*}$. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of $\phi_{\eta}^{*}$. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The measured normalized cross section as a function of $p_{ll}$ for the electron and muon channels and the combined result as well as their ratio together with the total uncertainties, shown as a blue band. The pull distribution between the electron and muon channels, defined as the difference between the two channels divided by the combined uncorrelated uncertainty, is also shown. The $p_{ll}$ distribution is split into linear and logarithmic scales at 30 GeV.
The measured normalized cross section as a function of $p_{ll}$ for the electron and muon channels and the combined result as well as their ratio together with the total uncertainties, shown as a blue band. The pull distribution between the electron and muon channels, defined as the difference between the two channels divided by the combined uncorrelated uncertainty, is also shown. The $p_{ll}$ distribution is split into linear and logarithmic scales at 30 GeV.
The measured normalized cross section as a function of $\phi_{\eta}^{*}$ for the electron and muon channels and the combined result as well as their ratio together with the total uncertainties, shown as a blue band. The pull distribution between the electron and muon channels, defined as the difference between the two channels divided by the combined uncorrelated uncertainty, is also shown.
The measured normalized cross section as a function of $\phi_{\eta}^{*}$ for the electron and muon channels and the combined result as well as their ratio together with the total uncertainties, shown as a blue band. The pull distribution between the electron and muon channels, defined as the difference between the two channels divided by the combined uncorrelated uncertainty, is also shown.
Comparison of the normalized $p_{ll}$ distributions predicted by different computations: Pythia8 with the AZ tune, Powheg+Pythia8 with the AZNLO tune, Sherpa v2.2.1 and RadISH with the Born level combined measurement. The uncertainties of the measurement are shown as vertical bars and uncertainties of the Sherpa and RadISH predictions are indicated by the coloured bands.
Comparison of the normalized $p_{ll}$ distributions predicted by different computations: Pythia8 with the AZ tune, Powheg+Pythia8 with the AZNLO tune, Sherpa v2.2.1 and RadISH with the Born level combined measurement. The uncertainties of the measurement are shown as vertical bars and uncertainties of the Sherpa and RadISH predictions are indicated by the coloured bands.
Comparison of the normalized $\phi_{\eta}^{*}$ distributions predicted by different computations: Pythia8 with the AZ tune, Powheg+Pythia8 with the AZNLO tune, Sherpa v2.2.1 and RadISH with the Born level combined measurement. The uncertainties of the measurement are shown as vertical bars and uncertainties of the Sherpa and RadISH predictions are indicated by the coloured bands.
Comparison of the normalized $\phi_{\eta}^{*}$ distributions predicted by different computations: Pythia8 with the AZ tune, Powheg+Pythia8 with the AZNLO tune, Sherpa v2.2.1 and RadISH with the Born level combined measurement. The uncertainties of the measurement are shown as vertical bars and uncertainties of the Sherpa and RadISH predictions are indicated by the coloured bands.
Comparison of the normalized $p_{ll}$ distribution in the range $p_{ll}$ > 10 GeV. The Born level combined measurement is compared with predictions by Sherpa v2.2.1, fixed-order NNLOjet and NNLOjet supplied with NLO electroweak corrections. The uncertainties in the measurement are shown as vertical bars and the uncertainties in the predictions are indicated by the coloured bands.
Comparison of the normalized $p_{ll}$ distribution in the range $p_{ll}$ > 10 GeV. The Born level combined measurement is compared with predictions by Sherpa v2.2.1, fixed-order NNLOjet and NNLOjet supplied with NLO electroweak corrections. The uncertainties in the measurement are shown as vertical bars and the uncertainties in the predictions are indicated by the coloured bands.
The results of a search for gluino and squark pair production with the pairs decaying via the lightest charginos into a final state consisting of two $W$ bosons, the lightest neutralinos ($\tilde\chi^0_1$), and quarks, are presented. The signal is characterised by the presence of a single charged lepton ($e^{\pm}$ or $\mu^{\pm}$) from a $W$ boson decay, jets, and missing transverse momentum. The analysis is performed using 139 fb$^{-1}$ of proton-proton collision data taken at a centre-of-mass energy $\sqrt{s}=13$ TeV delivered by the Large Hadron Collider and recorded by the ATLAS experiment. No statistically significant excess of events above the Standard Model expectation is found. Limits are set on the direct production of squarks and gluinos in simplified models. Masses of gluino (squark) up to 2.2 TeV (1.4 TeV) are excluded at 95% confidence level for a light $\tilde\chi^0_1$.
Post-fit $m_{T}$ distribution in the SR 2J b-veto N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 2J b-tag N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 4J b-veto N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 4J b-tag N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 6J b-veto N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 6J b-tag N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Pre-fit $m_{eff}$ distribution in the TR6J control region. Uncertainties include statistical and systematic uncertainties (added in quadrature). The value 9999 is used as a placeholder for infinity.
Pre-fit $m_{eff}$ distribution in the WR6J control region. Uncertainties include statistical and systematic uncertainties (added in quadrature). The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the TR6J control region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the WR6J control region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 2J b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 2J b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 4J low-x b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 4J low-x b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 4J high-x b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 4J high-x b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 6J b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 6J b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Observed 95% CL exclusion contours for the gluino one-step x = 1/2 model.
Expected 95% CL exclusion contours for the gluino one-step x = 1/2 model. space.
Observed 95% CL exclusion contours for the gluino one-step variable-x
Expected 95% CL exclusion contours for the gluino one-step variable-x
Observed 95% CL exclusion contours for the squark one-step x = 1/2 model.
Observed 95% CL exclusion contours for the squark one-step x = 1/2 model.
Observed 95% CL exclusion contours for one-flavour schemes in one-step x = 1/2 model.
Observed 95% CL exclusion contours for one-flavour schemes in one-step x = 1/2 model.
Expected 95% CL exclusion contours for the squark one-step variable-x
Expected 95% CL exclusion contours for the squark one-step variable-x
Expected 95% CL exclusion contours for the squark one-flavour schemes in variable-x
Expected 95% CL exclusion contours for the squark one-flavour schemes in variable-x
Upper limits on the signal cross section for simplified model gluino one-step x = 1/2
Upper limits on the signal cross section for simplified model gluino one-step variable-x
Upper limits on the signal cross section for simplified model squark one-step x = 1/2
Upper limits on the signal cross section for simplified model squark one-step variable-x
Upper limits on the signal cross section for simplified model squark one-step x=1/2 in one-flavour schemes
Upper limits on the signal cross section for simplified model squark one-step variable-x in one-flavour schemes
Post-fit $m_{eff}$ distribution in the TR2J control region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the WR2J control region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the TR4J control region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the WR4J control region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 2J b-tag validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 2J b-veto validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 4J b-tag validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 4J b-veto validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 6J b-tag validation region. Uncertainties include statistical and systematic uncertainties.
Post-fit $m_{eff}$ distribution in the 6J b-veto validation region. Uncertainties include statistical and systematic uncertainties.
Event selection cutflow for two representative signal samples for the SR2JBT. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Event selection cutflow for two representative signal samples for the SR2JBV. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Event selection cutflow for two representative signal samples for the SR4JBT. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Event selection cutflow for two representative signal samples for the SR4JBV. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Event selection cutflow for two representative signal samples for the SR6JBT. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Event selection cutflow for two representative signal samples for the SR6JBV. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Signal acceptance in SR2J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery high region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery low region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx discovery region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx discovery region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin4 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J discovery high region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J discovery low region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin4 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin4 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J discovery high region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery high region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J discovery low region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery low region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx discovery region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J discovery high region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J discovery low region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx discovery region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx discovery region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx discovery region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin4 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin4 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J discovery high region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J discovery low region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin4 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin4 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J discovery high region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J discovery high region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J discovery low region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J discovery low region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx discovery region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery high region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery low region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx discovery region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx discovery region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx discovery region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin4 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin4 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J discovery high region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J discovery low region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin4 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin4 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J discovery high region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery high region for squark production one-step variable-x simplified models
Signal acceptance in SR6J discovery low region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery low region for squark production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx discovery region for squark production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR2J discovery high region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR2J discovery low region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx discovery region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx discovery region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx discovery region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin4 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin4 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J discovery high region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J discovery low region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin3 region for squark production one-step variable-x simplified models
Signal efficiency in SR2J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal acceptance in SR6J b-Tag bin4 region for squark production one-step variable-x simplified models
Signal efficiency in SR2J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal acceptance in SR6J b-Veto bin1 region for squark production one-step variable-x simplified models
Signal efficiency in SR2J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal acceptance in SR6J b-Veto bin2 region for squark production one-step variable-x simplified models
Signal efficiency in SR2J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal acceptance in SR6J b-Veto bin3 region for squark production one-step variable-x simplified models
Signal efficiency in SR2J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal acceptance in SR6J b-Veto bin4 region for squark production one-step variable-x simplified models
Signal efficiency in SR2J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal acceptance in SR6J discovery high region for squark production one-step variable-x simplified models
Signal efficiency in SR2J discovery high region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal acceptance in SR6J discovery low region for squark production one-step variable-x simplified models
Signal efficiency in SR2J discovery low region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx discovery region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery high region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery low region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx discovery region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx discovery region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx discovery region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin4 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin4 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery high region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery low region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin4 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin4 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery high region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery high region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery low region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery low region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx discovery region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery high region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery low region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx discovery region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx discovery region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx discovery region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin4 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin4 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery high region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin4 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin4 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery high region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery low region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery high region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery low region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx discovery region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx discovery region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin4 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin4 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery high region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery low region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery high region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery low region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx discovery region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx discovery region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin4 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin4 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery high region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery low region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
A search for heavy neutral Higgs bosons is performed using the LHC Run 2 data, corresponding to an integrated luminosity of 139 fb$^{-1}$ of proton-proton collisions at $\sqrt{s}=13$ TeV recorded with the ATLAS detector. The search for heavy resonances is performed over the mass range 0.2-2.5 TeV for the $\tau^+\tau^-$ decay with at least one $\tau$-lepton decaying into final states with hadrons. The data are in good agreement with the background prediction of the Standard Model. In the $M_{h}^{125}$ scenario of the Minimal Supersymmetric Standard Model, values of $\tan\beta>8$ and $\tan\beta>21$ are excluded at the 95% confidence level for neutral Higgs boson masses of 1.0 TeV and 1.5 TeV, respectively, where $\tan\beta$ is the ratio of the vacuum expectation values of the two Higgs doublets.
Observed and predicted mTtot distribution in the b-veto category of 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.The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-veto category of 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.The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-veto category of 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.The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-veto category of 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.The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of 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. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of 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. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of 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. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of 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. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-veto category of 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 combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-veto category of 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 combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-veto category of 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 combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-veto category of 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 combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of 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 combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of 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 combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of 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 combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of 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 combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
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 Higgs boson mass.
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 Higgs boson mass.
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 Higgs boson mass.
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 Higgs boson mass.
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 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 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 b-associated Higgs boson production cross section times ditau branching fraction as a function of the boson mass.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
Acceptance times efficiency for a scalar boson produced by gluon-gluon fusion as a function of the scalar boson mass.
Acceptance times efficiency for a scalar boson produced by gluon-gluon fusion as a function of the scalar boson mass.
Acceptance times efficiency for a scalar boson produced by gluon-gluon fusion as a function of the scalar boson mass.
Acceptance times efficiency for a scalar boson produced by gluon-gluon fusion as a function of the scalar boson mass.
Acceptance times efficiency for a scalar boson produced by b-associated production as a function of the scalar boson mass.
Acceptance times efficiency for a scalar boson produced by b-associated production as a function of the scalar boson mass.
Acceptance times efficiency for a scalar boson produced by b-associated production as a function of the scalar boson mass.
Acceptance times efficiency for a scalar boson produced by b-associated production as a function of the scalar boson mass.
Observed 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Observed 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Observed 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Observed 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Expected 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Expected 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Expected 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Expected 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching 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 scalar 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. 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. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\chi})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\chi})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\chi})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\chi})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\chi})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\chi})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\chi})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\chi})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\chi})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\chi})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\chi})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\chi})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\tau})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\tau})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\tau})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\tau})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\tau})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\tau})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\tau})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\tau})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\tau})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\tau})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\tau})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\tau})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The observed 95% CL upper limits with one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(alignment)$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 1.0. The highest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 20.0. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(alignment)$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 1.0. The highest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 20.0. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(alignment)$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 1.0. The highest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 20.0. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(alignment)$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 1.0. The highest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 20.0. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(alignment)$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 1.0. The highest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 20.0. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(alignment)$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 1.0. The highest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 20.0. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The theoretical uncertainty of signal cross section is considered.
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