Observed and predicted mTtot distribution in the b-tag category of the 2tau_h channel. Despite listing this as an exclusive final state (as there must be at least one b-jets), there is no explicit selection on the presence of additional light-flavour jets. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 300, 500 and 800 GeV and $\tan\beta$ = 10 in the hMSSM scenario are also provided.

Observed and predicted mTtot distribution for the b-inclusive selection in the 1l1tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. In the paper, the first bin is cut off at 60 GeV for aesthetics but contains underflows down to 50 GeV as in the HepData table. The last bin includes overflows. The prediction for a SSM Zprime with masses of 1500, 2000 and 2500 GeV are also provided.

Observed and predicted mTtot distribution for the b-inclusive selection in the 2tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The prediction for a SSM Zprime with masses of 1500, 2000 and 2500 GeV are also provided.

Observed and expected 95% CL upper limits on the b-associated Higgs boson production cross section times ditau branching fraction as a function of the boson mass.

Observed and expected 95% CL upper limits on the Drell Yan production cross section times ditau branching fraction as a function of the Zprime boson mass.

Observed and expected 95% CL upper limits on the Higgs boson production cross section times ditau branching fraction as a function of the boson mass and the relative strength of the b-associated production.

Ratio of the 95% CL upper limits on the production cross section times branching fraction for alternate Zprime models with respect to the SSM, both observed and expected are shown.

Acceptance, acceptance times efficiency and b-tag category fraction for a scalar boson produced by gluon-gluon fusion as a function of the scalar boson mass.

Acceptance, acceptance times efficiency and b-tag category fraction for a scalar boson produced by b-associated production as a function of the scalar boson mass.

Acceptance and acceptance times efficiency for a heavy gauge boson produced by Drell Yan as a function of the gauge boson mass.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.

Observed and expected 95% CL upper limits on the gluon-gluon fusion Higgs boson production cross section times ditau branching fraction as a function of the boson mass.

Upper limits at the 95% CL on the cross section for SSM W' production and decay to the muon+neutrino channel as a function of the W' pole mass.

Combined (electron and muon channels) upper limits at the 95% CL on the cross section for SSM W' production and decay to a single lepton generation as a function of the W' pole mass.

Product of acceptance and efficiency for the electron and muon selections as a function of the W' pole mass.

Event yields for the different processes estimated with the fit to the $O_\mathrm{NN}$ distribution compared to the numbers of observed events. Only the statistical uncertainties are quoted. The $Z,VV+\mathrm{jets}$ contributions and the multijet background are fixed in the fit; therefore no uncertainty is quoted for these processes.

Detailed list of the contribution from each source of uncertainty to the total uncertainty in the measured values of $\sigma_{\mathrm{fid}}(tq)$ and $\sigma_{\mathrm{fid}}(\bar tq)$. The estimation of the systematic uncertainties has a statistical uncertainty of $0.3\%$. Uncertainties contributing less than $0.5\%$ are marked with ‘<0.5’.

Significant contributions to the total relative uncertainty in the measured value of $R_{t}$. The estimation of the systematic uncertainties has a statistical uncertainty of $0.3~\%$. Uncertainties contributing less than $0.5~\%$ are not shown.

Slopes $a$ of the mass dependence of the measured cross$-$sections.

Predicted (post-fit) and observed event yields for the signal region (SR), after the requirement on the neural network discriminant, $O_{\mathrm{NN}}~>~0.8$. The multijet background prediction is obtained from the fit to the $E_{\mathrm{T}}^{\mathrm{miss}}$ distribution described in Section 6, while all the other predictions and uncertainties are derived from the total cross$-$section measurement. In some cases there is no uncertainty quoted. In these cases the uncertainty is < 0.5.

Predicted (post-fit) and observed event yields for the signal region (SR), after the requirement on the second neural network discriminant, $O_{\mathrm{NN2}}~>~0.8$. The multijet background prediction is obtained from the fit to the $E_{\mathrm{T}}^{\mathrm{miss}}$ distribution described in Section 6, while all the other predictions and uncertainties are derived from the total cross$-$section measurement. In some cases there is no uncertainty quoted. In these cases the uncertainty is < 0.5.

Migration matrix for $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ at the particle level. The pseudo top quark is shown on the $y$-axis and the reconstructed variable is shown on the $x$-axis.

Migration matrix for $p_{\mathrm{T}}(t)$ at the parton level. The parton-level quark is shown on the $y$-axis and the reconstructed variable is shown on the $x$-axis.

Migration matrix for $|y(\hat{t\hspace{-0.2mm}})|$ at the particle level. The pseudo top quark is shown on the $y$-axis and the reconstructed variable is shown on the $x$-axis.

Migration matrix for $|y(t)|$ at the parton level. The parton-level quark is shown on the $y$-axis and the reconstructed variable is shown on the $x$-axis.

Uncertainties in the normalisations of the different backgrounds for all processes, as derived from the total cross-section measurement.

Absolute and normalised unfolded differential $tq$ production cross$-$section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ at particle level.

Absolute and normalised unfolded differential $\bar tq$ production cross$-$section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ at particle level.

Absolute and normalised unfolded differential $tq$ production cross$-$section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ at particle level.

Absolute and normalised unfolded differential $\bar tq$ production cross$-$section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ at particle level.

Absolute and normalised unfolded differential $tq$ production cross$-$section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ at particle level.

Absolute and normalised unfolded differential $\bar tq$ production cross$-$section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ at particle level.

Absolute and normalised unfolded differential $tq$ production cross$-$section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ at particle level.

Absolute and normalised unfolded differential $\bar tq$ production cross$-$section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ at particle level.

Absolute and normalised unfolded differential $tq$ production cross$-$section as a function of $p_{\mathrm{T}}(t)$ at parton level.

Absolute and normalised unfolded differential $\bar tq$ production cross$-$section as a function of $p_{\mathrm{T}}(t)$ at parton level.

Absolute and normalised unfolded differential $tq$ production cross$-$section as a function of $|y(t)|$ at parton level.

Absolute and normalised unfolded differential $\bar tq$ production cross$-$section as a function of $|y(t)|$ at parton level.

Statistical correlation matrix for the absolute differential cross-section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ for $tq$ events(at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the absolute differential cross-section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ for $ \bar tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the normalised differential cross-section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ for $tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the normalised differential cross-section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ for $\bar tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the absolute differential cross-section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ for $tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the absolute differential cross-section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ for $ \bar tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the normalised differential cross-section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ for $tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the normalised differential cross-section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ for $\bar tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the absolute differential cross-section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ for $tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the absolute differential cross-section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ for $\bar tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the normalised differential cross-section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ for $tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the normalised differential cross-section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ for $\bar tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the absolute differential cross-section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ for $tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the absolute differential cross-section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ for $\bar tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the normalised differential cross-section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ for $tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the normalised differential cross-section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ for $\bar tq$ events (at the particle level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the absolute differential cross-section as a function of $p_{\mathrm{T}}(t)$ for $tq$ events (at the parton level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the absolute differential cross-section as a function of $p_{\mathrm{T}}(t)$ for $ \bar tq$ events (at the parton level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the normalised differential cross-section as a function of $p_{\mathrm{T}}(t)$ for $tq$ events (at the parton level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the normalised differential cross-section as a function of $p_{\mathrm{T}}(t)$ for $ \bar tq$ events (at the parton level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the absolute differential cross-section as a function of $|y(t)|$ for $tq$ events (at the parton level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the absolute differential cross-section as a function of $|y(t)|$ for $\bar tq$ events (at the parton level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the normalised differential cross-section as a function of $|y(t)|$ for $tq$ events (at the parton level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Statistical correlation matrix for the normalised differential cross-section as a function of $|y(t)|$ for $\bar tq$ events (at the parton level). It includes the statistical uncertainty due to the number of data events and MC statistics.

Fiducial acceptance $A_{\mathrm{fid}}$ for different $t$-channel single top-quark MC samples. $^{\mathrm{(a)}}$ Calculation taken from AcerMC $+$ $\mathrm{P{\scriptsize YTHIA}6}$. $^{\mathrm{(b)}}$ Calculation taken from $\mathrm{P{\scriptsize OWHEG}}$-$\mathrm{B{\scriptsize OX}}$ $+$ $\mathrm{P{\scriptsize YTHIA}6}$.

Fiducial acceptance $A_{\mathrm{fid}}$ for different $t$-channel single top-antiquark MC samples. $^{\mathrm{(a)}}$ Calculation taken from AcerMC $+$ $\mathrm{P{\scriptsize YTHIA}6}$. $^{\mathrm{(b)}}$ Calculation taken from $\mathrm{P{\scriptsize OWHEG}}$-$\mathrm{B{\scriptsize OX}}$ $+$ $\mathrm{P{\scriptsize YTHIA}6}$.

Uncertainties for the absolute differential $tq$ cross-section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ at particle level per bin ([0,35,50,75,100,150,200,300] GeV) in percent of $\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the normalised differential $tq$ cross-section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ at particle level per bin ([0,35,50,75,100,150,200,300] GeV) in percent of $\left( \dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the absolute differential $\bar tq$ cross-section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ at particle level per bin ([0,35,50,75,100,150,300] GeV) in percent of $\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})}$.

Uncertainties for the normalised differential $\bar tq$ cross-section as a function of $p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})$ at particle level per bin ([0,35,50,75,100,150,300] GeV) in percent of $\left( \dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}p_{\mathrm{T}}(\hat{t\hspace{-0.2mm}})}$.

Uncertainties for the absolute differential $tq$ cross-section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ at particle level per bin ([0,0.15,0.3,0.45,0.7,1.0,1.3,2.2]) in percent of $\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}|y(\hat{t\hspace{-0.2mm}})|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the normalised differential $tq$ cross-section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ at particle level per bin ([0,0.15,0.3,0.45,0.7,1.0,1.3,2.2]) in percent of $\left(\dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}|y(\hat{t\hspace{-0.2mm}})|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the absolute differential $\bar tq$ cross-section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ at particle level per bin ([0,0.15,0.3,0.45,0.7,1.0,1.3,2.2]) in percent of $\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}|y(\hat{t\hspace{-0.2mm}})|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the normalised differential $\bar tq$ cross-section as a function of $|y(\hat{t\hspace{-0.2mm}})|$ at particle level per bin ([0,0.15,0.3,0.45,0.7,1.0,1.3,2.2]) in percent of $\left(\dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}|y(\hat{t\hspace{-0.2mm}})|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the absolute differential $tq$ cross-section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ at particle level per bin ([30,45,60,75,100,150,300] GeV) in percent of $\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the normalised differential $tq$ cross-section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ at particle level per bin ([30,45,60,75,100,150,300] GeV) in percent of $\left(\dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the absolute differential $\bar tq$ cross-section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ at particle level per bin ([30,45,60,75,100,150,300] GeV) in percent of $\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the normalised differential $\bar tq$ cross-section as a function of $p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})$ at particle level per bin ([30,45,60,75,100,150,300] GeV) in percent of $\left(\dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}p_{\mathrm{T}}(\hat{j\hspace{-0.2mm}})}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the absolute differential $tq$ cross-section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ at particle level per bin ([0.0, 1.2, 1.7, 2.2, 2.7, 3.3, 4.5]) in percent of $\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}|y(\hat{j\hspace{-0.2mm}})|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the normalised differential $tq$ cross-section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ at particle level per bin ([0.0, 1.2, 1.7, 2.2, 2.7, 3.3, 4.5]) in percent of $\left(\dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}|y(\hat{j\hspace{-0.2mm}})|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the absolute differential $\bar tq$ cross-section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ at particle level per bin ([0.0, 1.2, 1.7, 2.2, 2.7, 3.3, 4.5]) in percent of $\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}|y(\hat{j\hspace{-0.2mm}})|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the normalised differential $\bar tq$ cross-section as a function of $|y(\hat{j\hspace{-0.2mm}})|$ at particle level per bin ([0.0, 1.2, 1.7, 2.2, 2.7, 3.3, 4.5]) in percent of $\left(\dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}|y(\hat{j\hspace{-0.2mm}})|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the absolute differential $tq$ cross-section as a function of $p_{\mathrm{T}}(t)$ at parton level per bin ([0,50,100,150,200,300] GeV) in percent of $\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}p_{\mathrm{T}}(t)}$.

Uncertainties for the normalised differential $tq$ cross-section as a function of $p_{\mathrm{T}}(t)$ at parton level per bin ([0,50,100,150,200,300] GeV) in percent of $\left(\dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}p_{\mathrm{T}}(t)}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the absolute differential $\bar tq $ cross-section as a function of $p_{\mathrm{T}}(t)$ at parton level per bin ([0,50,100,150,300] GeV) in percent of $\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}p_{\mathrm{T}}(t)}$.

Uncertainties for the normalised differential $\bar tq $ cross-section as a function of $p_{\mathrm{T}}(t)$ at parton level per bin ([0,50,100,150,300] GeV) in percent of $\left(\dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}p_{\mathrm{T}}(t)}$.

Uncertainties for the absolute differential $ tq $ cross-section as a function of $|y(t)|$ at parton level per bin ([0,0.3,0.7,1.3,2.2]) in percent of $\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}|y(t)|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the normalised differential $ tq $ cross-section as a function of $|y(t)|$ at parton level per bin ([0,0.3,0.7,1.3,2.2]) in percent of $\left(\dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(tq)}{\mathrm{d}|y(t)|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

Uncertainties for the absolute differential $ \bar tq $ cross-section as a function of $|y(t)|$ at parton level per bin ([0,0.3,0.7,1.3,2.2]) in percent of $\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}|y(t)|}$.

Uncertainties for the normalised differential $ \bar tq $ cross-section as a function of $|y(t)|$ at parton level per bin ([0,0.3,0.7,1.3,2.2]) in percent of $\left(\dfrac{1}{\sigma}\right)\dfrac{\mathrm{d}\sigma(\bar tq)}{\mathrm{d}|y(t)|}$. If the uncertainty reported in the paper is "0.0" for both the $\textit{plus}$ and $\textit{minus}$ variation, the value "+0.01" is assigned to the $\textit{plus}$ variation for technical reasons.

HT inclusive distribution in SRZ.

Jet multiplicity distribution in SRZ.

B-tagged jet multiplicity distribution in SRZ.

Dilepton invariant mass distribution in SRMedium.

Dilepton invariant mass distribution in SRMedium.

Dilepton invariant mass in SRHigh.

Expected 95% exclusion contour for the gluino simplified model with fixed N1 mass and decays to quarks and Z bosons in SRZ.

Observed 95% exclusion contour for the gluino simplified model with fixed N1 mass and decays to quarks and Z bosons in SRZ.

Expected 95% exclusion contour for the squark simplified model with fixed N1 mass and decays to quarks and Z bosons in SRZ.

Observed 95% exclusion contour for the squark simplified model with fixed N1 mass and decays to quarks and Z bosons in SRZ.

Expected 95% exclusion contour for the gluino simplified model with varying N1 mass and decays to quarks and Z bosons in SRZ.

Observed 95% exclusion contour for the gluino simplified model with varying N1 mass and decays to quarks and Z bosons in SRZ.

Expected 95% exclusion contour for the gluino simplified model with sleptons in the edge SRs.

Observed 95% exclusion contour for the gluino simplified model with sleptons in the edge SRs.

Expected 95% exclusion contour for the gluino simplified model with decays to on- or off-shell Z bosons in the edge SRs.

Observed 95% exclusion contour for the gluino simplified model with decays to on- or off-shell Z bosons in the edge SRs.

Expected 95% exclusion contour for the gluino simplified model with decays to on- or off-shell Z bosons in SRZ.

Observed 95% exclusion contour for the gluino simplified model with decays to on- or off-shell Z bosons in SRZ.

Cutflow table for three benchmark signal points from the $\tilde{g}$--$\chi_{2}^{0}$ on-shell grid in SRZ for the $ee$ and $\mu\mu$ channels separately. The number of generated events is N RAW, while N WEIGHTED corresponds to the number of events expected in 14.7/fb, after all MC simulation corrections have been applied.

Cutflow table for three benchmark signal points for the slepton model in SR-low, SR-medium and SR-high for the $ee$ and $\mu\mu$ channels separately. The number of generated events is N RAW, while N WEIGHTED corresponds to the number of events expected in 14.7/fb, after all MC simulation corrections have been applied. The event generation was filtered to require at least two leptons (electrons or muons) with $p_{T}>5$ GeV and $|\eta|<2.8$, with 20000 events required to pass the filter. The corresponding number of unfiltered events is provided in the ``Pre-filter events'' row of the table.

Signal acceptance for the gluino simplified model with decays to quarks and Z bosons in SRZ.

Signal efficiency for the gluino simplified model with decays to quarks and Z bosons in SRZ.

Signal acceptance for the gluino simplified model with decays via sleptons in SRLow.

Signal efficiency for the gluino simplified model with decays via sleptons in SRLow.

Signal acceptance for the gluino simplified model with decays via sleptons in SRMedium.

Signal efficiency for the gluino simplified model with decays via sleptons in SRMedium.

Signal acceptance for the gluino simplified model with decays via sleptons in SRHigh.

Signal efficiency for the gluino simplified model with decays via sleptons in SRHigh.

Upper limits on the signal cross-section at 95% CL for the gluino simplified model with fixed N1 mass and decays to quarks and Z bosons in SRZ.

Upper limits on the signal cross-section at 95% CL for the squark simplified model with fixed N1 mass and decays to quarks and Z bosons in SRZ.

Upper limits on the signal cross-section at 95% CL for the gluino simplified model with varying N1 mass and decays to quarks and Z bosons in SRZ.

Upper limits on the signal cross-section at 95% CL for the gluino simplified model with decays via sleptons.

Upper limits on the signal cross-section at 95% CL for the gluino simplified model with decays to on-shell or off-shell Z bosons.

Kinematic distributions for "extended SR selections" of the 2-tau channel, for mTsum in the Compressed SR selection without the mTsum>1400 GeV requirement. The last bin includes overflow events. Cited uncertainties are statistical uncertainties only. Signal predictions are overlaid for several benchmark models, normalised to their predicted cross sections. For the simplified model, "MM" refers to a medium mass splitting, with m(gluino)=1145 GeV and m(neutralino)=265 GeV; "HM" denotes a high mass splitting scenario, with m(gluino)=1305 GeV and m(neutralino)=105 GeV. The GMSB benchmark model corresponds to Lambda = 90 TeV and tanbeta = 40.

Kinematic distributions for "extended SR selections" of the 2-tau channel, for mTtau1+mTtau2 in the High-Mass SR selection without the mTtau1+mTtau2>350GeV requirement. The last bin includes overflow events. Cited uncertainties are statistical uncertainties only. Signal predictions are overlaid for several benchmark models, normalised to their predicted cross sections. For the simplified model, "MM" refers to a medium mass splitting, with m(gluino)=1145 GeV and m(neutralino)=265 GeV; "HM" denotes a high mass splitting scenario, with m(gluino)=1305 GeV and m(neutralino)=105 GeV. The GMSB benchmark model corresponds to Lambda = 90 TeV and tanbeta = 40.

Kinematic distributions for "extended SR selections" of the 2-tau channel, for HT in the GMSB SR selection without the HT > 1700 GeV requirement. The last bin includes overflow events. Cited uncertainties are statistical uncertainties only. Signal predictions are overlaid for several benchmark models, normalised to their predicted cross sections. For the simplified model, "MM" refers to a medium mass splitting, with m(gluino)=1145 GeV and m(neutralino)=265 GeV; "HM" denotes a high mass splitting scenario, with m(gluino)=1305 GeV and m(neutralino)=105 GeV. The GMSB benchmark model corresponds to Lambda = 90 TeV and tanbeta = 40.

Expected exclusion contour at the 95% confidence level for the simplified model of gluino pair production, based on the combined results from the 1tau and 2tau channel. The result is obtained using 3.2 fb-1 of sqrt(s) = 13 TeV ATLAS data.

Observed exclusion contour at the 95% confidence level for the simplified model of gluino pair production, based on the combined results from the 1tau and 2tau channel. The result is obtained using 3.2 fb-1 of sqrt(s) = 13 TeV ATLAS data.

Expected exclusion contour at the 95% confidence level for the simplified model of gluino pair production, based on results from the 2tau channel. The result is obtained using 3.2 fb-1 of sqrt(s) = 13 TeV ATLAS data.

Expected exclusion contour at the 95% confidence level for the simplified model of gluino pair production, based on results from the 1tau channel. The result is obtained using 3.2 fb-1 of sqrt(s) = 13 TeV ATLAS data.

Observed exclusion contours at the 95% confidence level for the gauge-mediated supersymmetry-breaking model, based on results from the 2 tau channel. The result is obtained using 3.2 fb-1 of sqrt(s) = 13 TeV ATLAS data. Additional model parameters are M(mess) = 250 TeV, N5 = 3, mu>0 and Cgrav =1.

Expected exclusion contours at the 95% confidence level for the gauge-mediated supersymmetry-breaking model, based on results from the 2 tau channel. The result is obtained using 3.2 fb-1 of sqrt(s) = 13 TeV ATLAS data. Additional model parameters are M(mess) = 250 TeV, N5 = 3, mu>0 and Cgrav =1.

Observed upper cross section limits in pb for the simplified model of gluino pair production for the combination of all SRs.

Best expected signal region for the simplified model of gluino pair production. The respective SR has been used in the combination of the results.

Acceptance for the gluino production simplified model grid in the Compressed 1tau signal region.

Efficiency for the gluino production simplified model grid in the Compressed 1tau signal region.

Acceptance times Efficiency for the gluino production simplified model grid in the Compressed 1tau signal region.

Acceptance for the gluino production simplified model grid in the medium mass 1tau signal region.

Efficiency for the gluino production simplified model grid in the medium mass 1tau signal region.

Acceptance times Efficiency for the gluino production simplified model grid in the medium mass 1tau signal region.

Acceptance for the gluino production simplified model grid in the high mass 1tau signal region.

Efficiency for the gluino production simplified model grid in the high mass 1tau signal region.

Acceptance times Efficiency for the gluino production simplified model grid in the high mass 1tau signal region.

Acceptance for the gluino production simplified model grid in the compressed 2tau signal region.

Efficiency for the gluino production simplified model grid in the compressed 2tau signal region.

Acceptance times Efficiency for the gluino production simplified model grid in the compressed 2tau signal region.

Acceptance for the gluino production simplified model grid in the high mass 2tau signal region.

Efficiency for the gluino production simplified model grid in the high mass 2tau signal region.

Acceptance times Efficiency for the gluino production simplified model grid in the high mass 2tau signal region.

Acceptance for the GMSB model grid in the 2tau signal region.

Efficiency for the GMSB model grid in the 2tau signal region.

Acceptance times Efficiency for the GMSB model grid in the 2tau signal region.

The $p_{\rm T}$ bin width and corrected yield ratios R21 and R31 for $|y| < 0.6$. The statistical and systematic uncertainties in the corrected yield ratios are given as the percentage of the ratio.

The $p_{\rm T}$ bin width and corrected yield ratios R21 and R31 for $0.6 < |y| < 1.2$. The statistical and systematic uncertainties in the corrected yield ratios are given as the percentage of the ratio.

The $p_{\rm T}$ bin width and corrected yield ratios R21 and R31 for $|y| < 1.2$. The statistical and systematic uncertainties in the corrected yield ratios are given as the percentage of the ratio.

The dimuon acceptance $\mathcal{A}$ calculated using the CMS measured polarization and its positive and negative uncertainties $\mathcal{A}(\sigma^{\pm})$, and the values of the acceptance assuming no polarization $\mathcal{A}$(unpol), transverse polarization $\mathcal{A}(T)$, and longitudinal polarization $\mathcal{A}(L)$ for the $\Upsilon$(1S) state and $|y| <0.6$.

The dimuon acceptance $\mathcal{A}$ calculated using the CMS measured polarization and its positive and negative uncertainties $\mathcal{A}(\sigma^{\pm})$, and the values of the acceptance assuming no polarization $\mathcal{A}$(unpol), transverse polarization $\mathcal{A}(T)$, and longitudinal polarization $\mathcal{A}(L)$ for the $\Upsilon $(1S) state and $0.6 < |y| < 1.2$.

The dimuon acceptance $\mathcal{A}$ calculated using the CMS measured polarization and its positive and negative uncertainties $\mathcal{A}(\sigma^{\pm})$, and the values of the acceptance assuming no polarization $\mathcal{A}$(unpol), transverse polarization $\mathcal{A}(T)$, and longitudinal polarization $\mathcal{A}(L)$ for the $\Upsilon $(1S) state and $|y| < 1.2$.

The dimuon acceptance $\mathcal{A}$ calculated using the CMS measured polarization and its positive and negative uncertainties $\mathcal{A}(\sigma^{\pm})$, and the values of the acceptance assuming no polarization $\mathcal{A}$(unpol), transverse polarization $\mathcal{A}(T)$, and longitudinal polarization $\mathcal{A}(L)$ for the $\Upsilon $(2S) state and $|y| < 0.6$.

The dimuon acceptance $\mathcal{A}$ calculated using the CMS measured polarization and its positive and negative uncertainties $\mathcal{A}(\sigma^{\pm})$, and the values of the acceptance assuming no polarization $\mathcal{A}$(unpol), transverse polarization $\mathcal{A}(T)$, and longitudinal polarization $\mathcal{A}(L)$ for the $\Upsilon $(2S) state and $0.6 < |y| < 1.2$.

The dimuon acceptance $\mathcal{A}$ calculated using the CMS measured polarization and its positive and negative uncertainties $\mathcal{A}(\sigma^{\pm})$, and the values of the acceptance assuming no polarization $\mathcal{A}$(unpol), transverse polarization $\mathcal{A}(T)$, and longitudinal polarization $\mathcal{A}(L)$ for the $\Upsilon $(2S) state and $|y| < 1.2$.

The dimuon acceptance $\mathcal{A}$ calculated using the CMS measured polarization and its positive and negative uncertainties $\mathcal{A}(\sigma^{\pm})$, and the values of the acceptance assuming no polarization $\mathcal{A}$(unpol), transverse polarization $\mathcal{A}(T)$, and longitudinal polarization $\mathcal{A}(L)$ for the $\Upsilon $(3S) state and $|y| < 0.6$.

The dimuon acceptance $\mathcal{A}$ calculated using the CMS measured polarization and its positive and negative uncertainties $\mathcal{A}(\sigma^{\pm})$, and the values of the acceptance assuming no polarization $\mathcal{A}$(unpol), transverse polarization $\mathcal{A}(T)$, and longitudinal polarization $\mathcal{A}(L)$ for the $\Upsilon $(3S) state and $0.6 < |y| < 1.2$.

The dimuon acceptance $\mathcal{A}$ calculated using the CMS measured polarization and its positive and negative uncertainties $\mathcal{A}(\sigma^{\pm})$, and the values of the acceptance assuming no polarization $\mathcal{A}$(unpol), transverse polarization $\mathcal{A}(T)$, and longitudinal polarization $\mathcal{A}(L)$ for the $\Upsilon $(3S) state and $|y| < 1.2$.

Selection acceptance times efficiency as a function of WPRIME mass at truth level for left- and right-handed WPRIME MC. The total efficiency curves correspond to the sum of the efficiencies of the one b-tag and two b-tag categories.

Cutflow (efficiency with respect to total number of events in %) for several WPRIME masses in the left-handed and in the right-handed model for hadronic top-quark decays.

Overview of the signal acceptance times efficiency (A x Eff) for the hadronic top-quark decay for both categories, the predicted cross section times branching ratio to TOP BOTTOM, as well as the observed 95% CL limit on the cross section times branching ratio for several WPRIME masses in the left-handed and in the right-handed model. The expected signal event yields in the two categories for 20.3 fb-1 of 8 TeV data are also shown.

The effective mass distribution in VR2Z.

The ETmiss distribution in SR0noZa.

The effective mass distribution in SR0noZa.

The ETmiss distribution in SR1noZa.

The effective mass distribution in SR1noZa.

The ETmiss distribution in SR2noZa.

The effective mass distribution in SR2noZa.

The ETmiss distribution in SR0noZb.

The effective mass distribution in SR0noZb.

The ETmiss distribution in SR1noZb.

The effective mass distribution in SR1noZb.

The ETmiss distribution in SR2noZb.

The effective mass distribution in SR2noZb.

The ETmiss distribution in SR0Z.

The effective mass distribution in SR0Z.

The ETmiss distribution in SR1Z.

The effective mass distribution in SR1Z.

The ETmiss distribution in SR2Z.

The effective mass distribution in SR2Z.

Observed 95% CL exclusion contour for the RPV chargino NLSP model with lambda_121 != 0.

Expected 95% CL exclusion contour for the RPV chargino NLSP model with lambda_121 != 0.

Observed 95% CL exclusion contour for the RPV chargino NLSP model with lambda_122 != 0.

Expected 95% CL exclusion contour for the RPV chargino NLSP model with lambda_122 != 0.

Observed 95% CL exclusion contour for the RPV chargino NLSP model with lambda_133 != 0.

Expected 95% CL exclusion contour for the RPV chargino NLSP model with lambda_133 != 0.

Observed 95% CL exclusion contour for the RPV chargino NLSP model with lambda_233 != 0.

Expected 95% CL exclusion contour for the RPV chargino NLSP model with lambda_233 != 0.

Observed 95% CL exclusion contour for the RPV gluino NLSP model with lambda_121 != 0.

Expected 95% CL exclusion contour for the RPV gluino NLSP model with lambda_121 != 0.

Observed 95% CL exclusion contour for the RPV gluino NLSP model with lambda_122 != 0.

Expected 95% CL exclusion contour for the RPV gluino NLSP model with lambda_122 != 0.

Observed 95% CL exclusion contour for the RPV gluino NLSP model with lambda_133 != 0.

Expected 95% CL exclusion contour for the RPV gluino NLSP model with lambda_133 != 0.

Observed 95% CL exclusion contour for the RPV gluino NLSP model with lambda_233 != 0.

Expected 95% CL exclusion contour for the RPV gluino NLSP model with lambda_233 != 0.

Observed 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_121 != 0.

Expected 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_121 != 0.

Observed 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_122 != 0.

Expected 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_122 != 0.

Observed 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_133 != 0.

Expected 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_133 != 0.

Observed 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_233 != 0.

Expected 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_233 != 0.

Observed 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_121 != 0.

Expected 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_121 != 0.

Observed 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_122 != 0.

Expected 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_122 != 0.

Observed 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_133 != 0.

Expected 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_133 != 0.

Observed 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_233 != 0.

Expected 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_233 != 0.

Observed 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_121 != 0.

Expected 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_121 != 0.

Observed 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_122 != 0.

Expected 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_122 != 0.

Observed 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_133 != 0.

Expected 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_133 != 0.

Observed 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_233 != 0.

Expected 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_233 != 0.

Observed 95% CL exclusion contour for the R-slepton RPC model.

Expected 95% CL exclusion contour for the R-slepton RPC model.

Observed and expected 95% CL cross-section upper limits for the Stau RPC model, together with the theoretically predicted cross-section.

Observed and expected 95% CL cross-section upper limits for the Z RPC model, together with the theoretically predicted cross-section.

Observed 95% CL exclusion contour for the GGM tan beta = 1.5 model.

Expected 95% CL exclusion contour for the GGM tan beta = 1.5 model.

Observed 95% CL exclusion contour for the GGM tan beta = 30 model.

Expected 95% CL exclusion contour for the GGM tan beta = 30 model.

Observed 95% CL cross-section upper limit for the RPV chargino NLSP models with lambda_121 != 0 and lambda_122 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV chargino NLSP models with lambda_133 != 0 and lambda_233 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV gluino NLSP models with lambda_121 != 0 and lambda_122 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV gluino NLSP models with lambda_133 != 0 and lambda_233 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV Lslepton NLSP models with lambda_121 != 0 and lambda_122 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV Lslepton NLSP models with lambda_133 != 0 and lambda_233 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV Rslepton NLSP models with lambda_121 != 0 and lambda_122 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV Rslepton NLSP models with lambda_133 != 0 and lambda_233 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV sneutrino NLSP models with lambda_121 != 0 and lambda_122 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV sneutrino NLSP models with lambda_133 != 0 and lambda_233 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the R-slepton RPC model, and the selection of Z-veto signal regions used to set limits in this model. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bbb' means that the regions SR0noZb, SR1noZb and SR2noZb were used, in addition to the three Z-rich regions (SR0-2Z). For the RPC stau and Z models, the ``aaa' combination of regions was used throughout.

Performance of the SR0noZa selection in the R-slepton RPC model: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.

Performance of the SR0noZb selection in the RPV chargino NLSP model with lambda_121 != 0: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.

Performance of the SR1noZa selection in the RPV sneutrino NLSP model with lambda_233 != 0: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.

Performance of the SR1noZb selection in the RPV gluino NLSP model with lambda_133 != 0: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.

Performance of the SR2noZa selection in the RPV sneutrino NLSP model with lambda_233 != 0: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.

Performance of the SR2noZb selection in the RPV gluino NLSP model with lambda_133 != 0: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.

Performance of the SR0Z selection in the GGM tan beta = 30 model: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.

Cut flows for a representative selection of SUSY signal points in the Z-veto signal regions. In each case, m2 and m1 refer to the axes of the plots in Sec. XI, where m2 is the larger of the two masses. The number of events expected for a luminosity of 20.3 fb-1 is quoted at each step of the selection. The preselection requires four baseline leptons, at least two of which are light leptons; the signal lepton selection is made at the ``Lepton Multiplicity' stage. ``Event Cleaning' refers to the selection criteria applied to remove non-collision backgrounds and detector noise.

Cut flows for a representative selection of SUSY signal points in the Z-rich signal regions. In each case, m2 and m1 refer to the axes of the plots in Sec. XI, where m2 is the larger of the two masses (or the value of mu in the case of GGM models). The number of events expected for a luminosity of 20.3 fb-1 is quoted at each step of the selection. The preselection requires four baseline leptons, at least two of which are light leptons; the signal lepton selection is made at the ``Lepton Multiplicity' stage. ``Event Cleaning' refers to the selection criteria applied to remove non-collision backgrounds and detector noise.

Cut flows by lepton channel for a representative selection of SUSY signal points in the SR0noZa signal region. In each case, m2 and m1 refer to the axes of the plots in Sec. XI, where m2 is the larger of the two masses. The number of events expected for a luminosity of 20.3 fb-1 is quoted at each step of the selection. The preselection requires four baseline leptons, at least two of which are light leptons; the signal lepton selection is made at the ``Lepton Multiplicity' stage. ``Event Cleaning' refers to the selection criteria applied to remove non-collision backgrounds and detector noise. The RPC R-slepton model is used, with (m2,m1) = (450,300) GeV.

Cut flows by lepton channel for a representative selection of SUSY signal points in the SR1noZb signal region. In each case, m2 and m1 refer to the axes of the plots in Sec. XI, where m2 is the larger of the two masses. The number of events expected for a luminosity of 20.3 fb-1 is quoted at each step of the selection. The preselection requires four baseline leptons, at least two of which are light leptons; the signal lepton selection is made at the ``Lepton Multiplicity' stage. ``Event Cleaning' refers to the selection criteria applied to remove non-collision backgrounds and detector noise. The RPV gluino NLSP model is used, with lambda_133 != 0 and (m2,m1) = (800,400) GeV.

Cut flows by lepton channel for a representative selection of SUSY signal points in the SR0Z signal region. In each case, m2 and m1 refer to the axes of the plots in Sec. XI, where m2 is the value of mu. The number of events expected for a luminosity of 20.3 fb-1 is quoted at each step of the selection. The preselection requires four baseline leptons, at least two of which are light leptons; the signal lepton selection is made at the ``Lepton Multiplicity' stage. ``Event Cleaning' refers to the selection criteria applied to remove non-collision backgrounds and detector noise. The GGM tan beta = 30 model is used, with (m2,m1) = (200,1000) GeV.

Observed and expected numbers of events with exactly three leptons with the scalar sum of jet transverse momentum values HT < 200 GeV. "On-Z" refers to events with at least one E+ E- or MU+ MU- (OSSF) pair with dilepton mass between 75 and 105 GeV, while "Off-Z" refers to events with one or two OSSF pairs, none of which fall in this mass range. The OSSFN designation refers to the number of E+ E- and MU+ MU- pairs in the event. Search channels binned in ET have been combined into coarse ET bins for the purposes of presentation.

The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the natural Higgsino NLSP scenario with BR(NEUTRALINO1 --> HIGGS GRAVITINO) = BR(NEUTRALINO1 --> Z GRAVITINO) = 0.5 for strong plus electroweak production.

The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the natural Higgsino NLSP scenario with BR(NEUTRALINO1 --> HIGGS GRAVITINO) = 1.0 for strong plus electroweak production.

The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the natural Higgsino NLSP scenario with BR(NEUTRALINO1 --> Z0 GRAVITINO) = 1.0 for strong plus electroweak production.

The product of acceptance and efficiency for the calculation of the 95% C.L. limit for the natural Higgsino NLSP scenario with strong plus electroweak production for BR(NEUTRALINO1 --> HIGGS GRAVITINO) = BR(NEUTRALINO1 --> Z0 GRAVITINO) = 0.5. The chargino-Higgsino mass is fixed at 150 GeV.

The product of acceptance and efficiency for the calculation of the 95% C.L. limit for the natural Higgsino NLSP scenario with strong plus electroweak production for BR(NEUTRALINO1 --> HIGGS GRAVITINO) = BR(NEUTRALINO1 --> Z0 GRAVITINO) = 0.5. The chargino-Higgsino mass is fixed at 350 GeV.

The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the natural Higgsino NLSP scenario with strong plus electroweak production for BR(NEUTRALINO1 --> HIGGS GRAVITINO) = 1.0. The chargino-Higgsino mass is fixed at 150 GeV.

The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the natural Higgsino NLSP scenario with strong plus electroweak production for BR(NEUTRALINO1 --> HIGGS GRAVITINO) = 1.0. The chargino-Higgsino mass is fixed at 350 GeV.

The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the natural Higgsino NLSP scenario with strong plus electroweak production for BR(NEUTRALINO1 --> Z0 GRAVITINO) = 1.0. The chargino-Higgsino mass is fixed at 150 GeV.

The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the natural Higgsino NLSP scenario with strong plus electroweak production for BR(NEUTRALINO1 --> Z0 GRAVITINO) = 1.0. The chargino-Higgsino mass is fixed at 350 GeV.

The product of acceptance and efficiency for the calculation of the 95% C.L. limit on BR(NEUTRALINO1 --> HIGGS GRAVITINO) for the natural Higgsino NLSP scenario with fixed chargino-Higgsino mass of 150 GeV assuming BR(NEUTRALINO1 --> HIGGS GRAVITINO) + BR(NEUTRALINO1 --> Z GRAVITINO) = 1.0 and strong plus weak production.

The product of acceptance and efficiency for the calculation of the 95% C.L. limit on BR(NEUTRALINO1 --> HIGGS GRAVITINO) for the natural Higgsino NLSP scenario with fixed chargino-Higgsino mass of 250 GeV assuming BR(NEUTRALINO1 --> HIGGS GRAVITINO) + BR(NEUTRALINO1 --> Z0 GRAVITINO) = 1.0 and strong plus weak production.

The product of acceptance and efficiency for the calculation of the 95% C.L. limit on BR(NEUTRALINO1 --> HIGGS GRAVITINO) for the natural Higgsino NLSP scenario with fixed chargino-Higgsino mass of 350 GeV assuming BR(NEUTRALINO1 --> HIGGS GRAVITINO) + BR(NEUTRALINO1 --> Z0 GRAVITINO) = 1.0 and strong plus weak production.

The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the slepton co-NLSP model in the gluino-chargino (wino-like chargino) mass plane.

The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the stau-NLSP and stau-NNLSP scenario in the degenerate smuon- and selectron- stau mass plane.

The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the T1tttt model in the gluino-neutralino mass plane.

The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the T6ttWW model in the sbottom-chargino mass plane.

Observed 95% C.L. exclusion contour for the T1tttt scenario.

Observed - 1sig(theoretical) 95% C.L. exclusion contour for the T1tttt scenario.

Observed + 1sig(theoretical) 95% C.L. exclusion contour for the T1tttt scenario.

Expected 95% C.L. exclusion contour for the T1tttt scenario.

Expected - 1sig 95% C.L. exclusion contour for the T1tttt scenario.

Expected + 1sig 95% C.L. exclusion contour for the T1tttt scenario.

Observed 95% C.L. exclusion contour for the T6ttWW scenario.

Observed - 1sig(theoretical) 95% C.L. exclusion contour for the T6ttWW scenario.

Observed + 1sig(theoretical) 95% C.L. exclusion contour for the T6ttWW scenario.

Expected 95% C.L. exclusion contour for the T6ttWW scenario.

Expected - 1sig 95% C.L. exclusion contour for the T6ttWW scenario.

Expected + 1sig 95% C.L. exclusion contour for the T6ttWW scenario.

Observed and expected 95% C.L. limits for the natural Higgsino NLSP scenario with BR(NEUTRALINO1 --> HIGGS GRAVITINO) = BR(NEUTRALINO1 --> Z GRAVITINO) = 0.5 for strong plus electroweak production.

Observed and expected 95% C.L. limits for the natural Higgsino NLSP scenario with BR(NEUTRALINO1 --> HIGGS GRAVITINO) = 1.0 for strong plus electroweak production. Successive instances of SIG(OBS) = SIG(EXP) =0 have been rebinned over M(STOP) to reduce the size of the table.

Observed and expected 95% C.L. limits for the natural Higgsino NLSP scenario with BR(NEUTRALINO1 --> Z0 GLUINO) = 1.0 for strong plus electroweak production.

Observed 95% C.L. limits on BR(NEUTRALINO1 --> HIGGS GRAVITINO) for the natural Higgsino NLSP scenario with fixed chargino-Higgsino mass of 150 GeV assuming BR(NEUTRALINO1 --> HIGGS GRAVITINO) + BR(NEUTRALINO1 --> Z GRAVITINO) = 1.0 and strong plus weak production.

Observed 95% C.L. limits on BR(NEUTRALINO1 --> HIGGS GRAVITINO) for the natural Higgsino NLSP scenario with fixed chargino-Higgsino mass of 250 GeV assuming BR(NEUTRALINO1 --> HIGGS GRAVITINO) + BR(NEUTRALINO1 --> Z GRAVITINO) = 1.0 and strong plus weak production.

Observed 95% C.L. limits on BR(NEUTRALINO1 --> HIGGS GRAVITINO) for the natural Higgsino NLSP scenario with fixed chargino-Higgsino mass of 350 GeV assuming BR(NEUTRALINO1 --> HIGGS GRAVITINO) + BR(NEUTRALINO1 --> Z GRAVITINO) = 1.0 and strong plus weak production.

Observed and expected 95% C.L. limits for the slepton co-NLSP model in the gluino-chargino (wino-like chargino) mass plane are shown.

Observed and expected 95% C.L. limits for the stau-NLSP and stau-NNLSP scenario in the degenerate smuon- and selectron- stau mass plane are shown. Successive instances of SIG(OBS) = SIG(EXP) =0 have been rebinned over M(SELECTRON) to reduce the size of the table.

Observed and expected 95% C.L. limits for the T1tttt model in the gluino-neutralino mass plane are shown.

Observed and expected 95% C.L. limits for the T6ttWW model in the sbottom-chargino mass plane are given.

The expected limit contour in the GLUINO-NEUTRALINO plane.

The observed limit contour in the SQUARK-NEUTRALINO plane.

The expected limit contour in the SQUARK-NEUTRALINO plane.