The relative statistical and systematic uncertainties in % from various sources for the absolute cross section measurements in bins of Z pt on dimuons.

The relative statistical and systematic uncertainties in % from various sources for the absolute cross section measurements in bins of Z pt on dielectrons.

The relative statistical and systematic uncertainties in % from various sources for the absolute cross section measurements in bins of |y(Z)| on dimuons.

The relative statistical and systematic uncertainties in % from various sources for the absolute cross section measurements in bins of |y(Z)| on dielectrons.

The relative statistical and systematic uncertainties in % from various sources for the absolute cross section measurements in bins of $\phi^{\scriptscriptstyle *}_\eta$ on dimuons.

The relative statistical and systematic uncertainties in % from various sources for the absolute cross section measurements in bins of $\phi^{\scriptscriptstyle *}_\eta$ on dielectrons.

The relative statistical and systematic uncertainties in % from various sources for the normalized cross section measurements in bins of Z pt on dimuons.

The relative statistical and systematic uncertainties in % from various sources for the normalized cross section measurements in bins of Z pt on dielectrons.

The relative statistical and systematic uncertainties in % from various sources for the normalized cross section measurements in bins of |y(Z)| on dimuons.

The relative statistical and systematic uncertainties in % from various sources for the normalized cross section measurements in bins of |y(Z)| on dielectrons.

The relative statistical and systematic uncertainties in % from various sources for the normalized cross section measurements in bins of $\phi^{\scriptscriptstyle *}_\eta$ on dimuons.

The relative statistical and systematic uncertainties in % from various sources for the normalized cross section measurements in bins of $\phi^{\scriptscriptstyle *}_\eta$ on dielectrons.

The relative statistical and systematic uncertainties in % from various sources for the absolute double-differential cross section measurements in bins of Z pt for the 0 < |y(Z)| < 0.4 bin in the dimuon final state.

The relative statistical and systematic uncertainties in % from various sources for the absolute double-differential cross section measurements in bins of Z pt for the 0.4 < |y(Z)| < 0.8 bin in the dimuon final state.

The relative statistical and systematic uncertainties in % from various sources for the absolute double-differential cross section measurements in bins of Z pt for the 0.8 < |y(Z)| < 1.2 bin in the dimuon final state.

The relative statistical and systematic uncertainties in % from various sources for the absolute double-differential cross section measurements in bins of Z pt for the 1.2 < |y(Z)| < 1.6 bin in the dimuon final state.

The relative statistical and systematic uncertainties in % from various sources for the absolute double-differential cross section measurements in bins of Z pt for the 1.6 < |y(Z)| < 2.4 bin in the dimuon final state.

The relative statistical and systematic uncertainties in % from various sources for the absolute double-differential cross section measurements in bins of Z pt for the 0 < |y(Z)| < 0.4 bin in the dielectron final state.

The relative statistical and systematic uncertainties in % from various sources for the absolute double-differential cross section measurements in bins of Z pt for the 0.4 < |y(Z)| < 0.8 bin in the dielectron final state.

The relative statistical and systematic uncertainties in % from various sources for the absolute double-differential cross section measurements in bins of Z pt for the 0.8 < |y(Z)| < 1.2 bin in the dielectron final state.

The relative statistical and systematic uncertainties in % from various sources for the absolute double-differential cross section measurements in bins of Z pt for the 1.2 < |y(Z)| < 1.6 bin in the dielectron final state.

The relative statistical and systematic uncertainties in % from various sources for the absolute double-differential cross section measurements in bins of Z pt for the 1.6 < |y(Z)| < 2.4 bin in the dielectron final state.

The measured absolute cross sections in bins of |y(Z)|, using dressed level leptons. The cross sections are normalized by the bin width.

The measured absolute cross sections in bins of Z pt, using dressed level leptons. The cross sections are normalized by the bin width.

The measured absolute cross sections in bins of $\phi^{\scriptscriptstyle *}_\eta$, using dressed level leptons. The cross sections are normalized by the bin width.

The measured absolute cross sections in bins of Z pt different |y(Z)| bins, using dressed level leptons. The cross sections are normalized by the bin width.

The measured normalized cross sections in bins of Z pt, using dressed level leptons.

The measured normalized cross sections in bins of $\phi^{\scriptscriptstyle *}_\eta$, using dressed level leptons.

The measured normalized cross sections in bins of |y(Z)|, using dressed level leptons.

The measured normalized cross sections (left) in bins of Z pt in |y(Z)| bins, using dressed level leptons.

Covariance matrix using dressed level leptons for all bins used in bins of Z pt in the dimuon final state.

Covariance matrix using dressed level leptons for all bins used in bins of |y(Z)| in the dimuon final state.

Covariance matrix using dressed level leptons for all bins used in bins of $\phi^{\scriptscriptstyle *}_\eta$ in the dimuon final state.

Covariance matrix using dressed level leptons for all bins used in bins of Z pt for the 0 < |y(Z)| < 0.4 bin in the dimuon final state.

Covariance matrix using dressed level leptons for all bins used in bins of Z pt for the 0.4 < |y(Z)| < 0.8 bin in the dimuon final state.

Covariance matrix using dressed level leptons for all bins used in bins of Z pt for the 0.8 < |y(Z)| < 1.2 bin in the dimuon final state.

Covariance matrix using dressed level leptons for all bins used in bins of Z pt for the 1.2 < |y(Z)| < 1.6 bin in the dimuon final state.

Covariance matrix using dressed level leptons for all bins used in bins of Z pt for the 1.6 < |y(Z)| < 2.4 bin in the dimuon final state.

Covariance matrix using dressed level leptons for all bins used in bins of Z pt in the dielectron final state.

Covariance matrix using dressed level leptons for all bins used in bins of |y(Z)| in the dielectron final state.

Covariance matrix using dressed level leptons for all bins used in bins of $\phi^{\scriptscriptstyle *}_\eta$ in the dielectron final state.

Covariance matrix using dressed level leptons for all bins used in bins of Z pt for the 0 < |y(Z)| < 0.4 bin in the dielectron final state.

Covariance matrix using dressed level leptons for all bins used in bins of Z pt for the 0.4 < |y(Z)| < 0.8 bin in the dielectron final state.

Covariance matrix using dressed level leptons for all bins used in bins of Z pt for the 0.8 < |y(Z)| < 1.2 bin in the dielectron final state.

Covariance matrix using dressed level leptons for all bins used in bins of Z pt for the 1.2 < |y(Z)| < 1.6 bin in the dielectron final state.

Covariance matrix using dressed level leptons for all bins used in bins of Z pt for the 1.6 < |y(Z)| < 2.4 bin in the dielectron final state.

Covariance matrix using born level leptons for all bins used in bins of Z pt in the dimuon final state.

Covariance matrix using born level leptons for all bins used in bins of |y(Z)| in the dimuon final state.

Covariance matrix using born level leptons for all bins used in bins of $\phi^{\scriptscriptstyle *}_\eta$ in the dimuon final state.

Covariance matrix using born level leptons for all bins used in bins of Z pt for the 0 < |y(Z)| < 0.4 bin in the dimuon final state.

Covariance matrix using born level leptons for all bins used in bins of Z pt for the 0.4 < |y(Z)| < 0.8 bin in the dimuon final state.

Covariance matrix using born level leptons for all bins used in bins of Z pt for the 0.8 < |y(Z)| < 1.2 bin in the dimuon final state.

Covariance matrix using born level leptons for all bins used in bins of Z pt for the 1.2 < |y(Z)| < 1.6 bin in the dimuon final state.

Covariance matrix using born level leptons for all bins used in bins of Z pt for the 1.6 < |y(Z)| < 2.4 bin in the dimuon final state.

Covariance matrix using born level leptons for all bins used in bins of Z pt in the dielectron final state.

Covariance matrix using born level leptons for all bins used in bins of |y(Z)| in the dielectron final state.

Covariance matrix using born level leptons for all bins used in bins of $\phi^{\scriptscriptstyle *}_\eta$ in the dielectron final state.

Covariance matrix using born level leptons for all bins used in bins of Z pt for the 0 < |y(Z)| < 0.4 bin in the dielectron final state.

Covariance matrix using born level leptons for all bins used in bins of Z pt for the 0.4 < |y(Z)| < 0.8 bin in the dielectron final state.

Covariance matrix using born level leptons for all bins used in bins of Z pt for the 0.8 < |y(Z)| < 1.2 bin in the dielectron final state.

Covariance matrix using born level leptons for all bins used in bins of Z pt for the 1.2 < |y(Z)| < 1.6 bin in the dielectron final state.

Covariance matrix using born level leptons for all bins used in bins of Z pt for the 1.6 < |y(Z)| < 2.4 bin in the dielectron final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of Z pt in the dimuon final state.

The measured absolute cross sections in bins of |y(Z)|, using born level leptons. The cross sections are normalized by the bin width.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of |y(Z)| in the dimuon final state.

The measured absolute cross sections in bins of Z pt, using born level leptons. The cross sections are normalized by the bin width. The first bin (0-1 GeV) is not shown as large differences were observed in aMC@NLO and POWHEG predictions at Born level.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of $\phi^{\scriptscriptstyle *}_\eta$ in the dimuon final state.

The measured absolute cross sections in bins of $\phi^{\scriptscriptstyle *}_\eta$, using born level leptons. The cross sections are normalized by the bin width.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of Z pt for the 0 < |y(Z)| < 0.4 bin in the dimuon final state.

The measured absolute cross sections in bins of Z pt different |y(Z)| bins, using born level leptons. The cross sections are normalized by the bin width. The first bin (0-1 GeV) is not shown as large differences were observed in aMC@NLO and POWHEG predictions at Born level.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of Z pt for the 0.4 < |y(Z)| < 0.8 bin in the dimuon final state.

The measured normalized cross sections in bins of Z pt, using born level leptons. The first bin (0-1 GeV) is not shown as large differences were observed in aMC@NLO and POWHEG predictions at Born level.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of Z pt for the 0.8 < |y(Z)| < 1.2 bin in the dimuon final state.

The measured normalized cross sections in bins of $\phi^{\scriptscriptstyle *}_\eta$, using born level leptons.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of Z pt for the 1.2 < |y(Z)| < 1.6 bin in the dimuon final state.

The measured normalized cross sections in bins of |y(Z)|, using born level leptons.

The measured normalized cross sections (left) in bins of Z pt in |y(Z)| bins, using born level leptons. The first bin (0-1 GeV) is not shown as large differences were observed in aMC@NLO and POWHEG predictions at Born level.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of Z pt for the 1.6 < |y(Z)| < 2.4 bin in the dimuon final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of Z pt in the dielectron final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of |y(Z)| in the dielectron final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of $\phi^{\scriptscriptstyle *}_\eta$ in the dielectron final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of Z pt for the 0 < |y(Z)| < 0.4 bin in the dielectron final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of Z pt for the 0.4 < |y(Z)| < 0.8 bin in the dielectron final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of Z pt for the 0.8 < |y(Z)| < 1.2 bin in the dielectron final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of Z pt for the 1.2 < |y(Z)| < 1.6 bin in the dielectron final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of Z pt for the 1.6 < |y(Z)| < 2.4 bin in the dielectron final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of Z pt in the dimuon final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of |y(Z)| in the dimuon final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of $\phi^{\scriptscriptstyle *}_\eta$ in the dimuon final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of Z pt for the 0 < |y(Z)| < 0.4 bin in the dimuon final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of Z pt for the 0.4 < |y(Z)| < 0.8 bin in the dimuon final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of Z pt for the 0.8 < |y(Z)| < 1.2 bin in the dimuon final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of Z pt for the 1.2 < |y(Z)| < 1.6 bin in the dimuon final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of Z pt for the 1.6 < |y(Z)| < 2.4 bin in the dimuon final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of Z pt in the dielectron final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of |y(Z)| in the dielectron final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of $\phi^{\scriptscriptstyle *}_\eta$ in the dielectron final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of Z pt for the 0 < |y(Z)| < 0.4 bin in the dielectron final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of Z pt for the 0.4 < |y(Z)| < 0.8 bin in the dielectron final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of Z pt for the 0.8 < |y(Z)| < 1.2 bin in the dielectron final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of Z pt for the 1.2 < |y(Z)| < 1.6 bin in the dielectron final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of Z pt for the 1.6 < |y(Z)| < 2.4 bin in the dielectron final state.

The expected and observed 95% CL upper limits on the product of cross section and branching fraction for direct production of charginos as a function of chargino mass, for a chargino lifetime of 333 ns and with a purely wino LSP. The branching fraction for $\widetilde{\chi}^{\pm}_{1} \rightarrow \widetilde{\chi}^{0}_{1} \pi^{\pm}$ is set to 100%. Shown are the full Run 2 results, derived from the results of the search in the 2017 and 2018 data sets combined with those of the previous CMS result obtained in the 2015 and 2016 data sets. The cross section includes both $\widetilde{\chi}^{\pm}_{1} \widetilde{\chi}^{0}_{1}$ and $\widetilde{\chi}^{\pm}_{1}\widetilde{\chi}^{\mp}_{1}$ production in roughly a 2:1 ratio for all chargino masses considered. The dashed line indicates the theoretical prediction.

The expected and observed 95% CL upper limits on the product of cross section and branching fraction for direct production of charginos as a function of chargino mass, for a chargino lifetime of 0.3 ns and with a purely higgsino LSP. The branching fractions are set to 95.5% for $\widetilde{\chi}^{\pm}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \pi^{\pm}$, 3% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} e\nu$, and 1.5% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \mu\nu$, with equal branching fractions and production cross sections between $\widetilde{\chi}^{0}_{1}$ and $\widetilde{\chi}^{0}_{2}$. The cross section includes both $\widetilde{\chi}^{\pm}_{1} \widetilde{\chi}^{0}_{1,2}$ and $\widetilde{\chi}^{\pm}_{1}\widetilde{\chi}^{\mp}_{1}$ production in roughly a 7:2 ratio for all chargino masses considered. The dashed line indicates the theoretical prediction.

The expected and observed 95% CL upper limits on the product of cross section and branching fraction for direct production of charginos as a function of chargino mass, for a chargino lifetime of 3.3 ns and with a purely higgsino LSP. The branching fractions are set to 95.5% for $\widetilde{\chi}^{\pm}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \pi^{\pm}$, 3% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} e\nu$, and 1.5% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \mu\nu$, with equal branching fractions and production cross sections between $\widetilde{\chi}^{0}_{1}$ and $\widetilde{\chi}^{0}_{2}$. The cross section includes both $\widetilde{\chi}^{\pm}_{1} \widetilde{\chi}^{0}_{1,2}$ and $\widetilde{\chi}^{\pm}_{1}\widetilde{\chi}^{\mp}_{1}$ production in roughly a 7:2 ratio for all chargino masses considered. The dashed line indicates the theoretical prediction.

The expected and observed 95% CL upper limits on the product of cross section and branching fraction for direct production of charginos as a function of chargino mass, for a chargino lifetime of 33 ns and with a purely higgsino LSP. The branching fractions are set to 95.5% for $\widetilde{\chi}^{\pm}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \pi^{\pm}$, 3% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} e\nu$, and 1.5% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \mu\nu$, with equal branching fractions and production cross sections between $\widetilde{\chi}^{0}_{1}$ and $\widetilde{\chi}^{0}_{2}$. The cross section includes both $\widetilde{\chi}^{\pm}_{1} \widetilde{\chi}^{0}_{1,2}$ and $\widetilde{\chi}^{\pm}_{1}\widetilde{\chi}^{\mp}_{1}$ production in roughly a 7:2 ratio for all chargino masses considered. The dashed line indicates the theoretical prediction.

The expected and observed 95% CL upper limits on the product of cross section and branching fraction for direct production of charginos as a function of chargino mass, for a chargino lifetime of 333 ns and with a purely higgsino LSP. The branching fractions are set to 95.5% for $\widetilde{\chi}^{\pm}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \pi^{\pm}$, 3% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} e\nu$, and 1.5% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \mu\nu$, with equal branching fractions and production cross sections between $\widetilde{\chi}^{0}_{1}$ and $\widetilde{\chi}^{0}_{2}$. The cross section includes both $\widetilde{\chi}^{\pm}_{1} \widetilde{\chi}^{0}_{1,2}$ and $\widetilde{\chi}^{\pm}_{1}\widetilde{\chi}^{\mp}_{1}$ production in roughly a 7:2 ratio for all chargino masses considered. The dashed line indicates the theoretical prediction.

The expected and observed constraints on chargino lifetime and mass for a purely wino LSP in the context of AMSB, where the chargino lifetime is explicitly varied. The chargino branching fraction is set to 100% for $\widetilde{\chi}^{\pm}_{1} \rightarrow \widetilde{\chi}^{0}_{1} \pi^{\pm}$. Shown are the full Run 2 results, derived from the results of the search in the 2017 and 2018 data sets combined with those of the previous CMS result obtained in the 2015 and 2016 data sets. The region to the left of the curve is excluded at 95% CL. The prediction from PLB 721 (2013) 252 is indicated in the dashed line.

The expected and observed 95% CL upper limits on the product of cross section and branching fraction for direct production of charginos as a function of chargino mass and mean proper lifetime, with a purely wino LSP. The branching fraction for $\widetilde{\chi}^{\pm}_{1} \rightarrow \widetilde{\chi}^{0}_{1} \pi^{\pm}$ is set to 100%. Shown are the full Run 2 results, derived from the results of the search in the 2017 and 2018 data sets combined with those of the previous CMS result obtained in the 2015 and 2016 data sets. The cross section includes both $\widetilde{\chi}^{\pm}_{1} \widetilde{\chi}^{0}_{1}$ and $\widetilde{\chi}^{\pm}_{1}\widetilde{\chi}^{\mp}_{1}$ production in roughly a 2:1 ratio for all chargino masses considered.

The expected and observed constraints on chargino lifetime and mass for a purely higgsino LSP in the context of AMSB, where the chargino lifetime is explicitly varied. The chargino branching fraction is set to 95.5% for $\widetilde{\chi}^{\pm}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \pi^{\pm}$, 3% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} e\nu$, and 1.5% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \mu\nu$, with equal branching fractions and production cross sections between $\widetilde{\chi}^{0}_{1}$ and $\widetilde{\chi}^{0}_{2}$. The region to the left of the curve is excluded at 95% CL. The prediction from Phys. Lett. B 781 (2018) 306 is indicated in the dashed line.

The expected and observed 95% CL upper limits on the product of cross section and branching fraction for direct production of charginos as a function of chargino mass and mean proper lifetime, with a purely higgsino LSP. The branching fractions are set to 95.5% for $\widetilde{\chi}^{\pm}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \pi^{\pm}$, 3% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} e\nu$, and 1.5% for $\widetilde{\chi}^{-}_{1} \rightarrow \widetilde{\chi}^{0}_{1,2} \mu\nu$, with equal branching fractions and production cross sections between $\widetilde{\chi}^{0}_{1}$ and $\widetilde{\chi}^{0}_{2}$. The cross section includes both $\widetilde{\chi}^{\pm}_{1} \widetilde{\chi}^{0}_{1,2}$ and $\widetilde{\chi}^{\pm}_{1}\widetilde{\chi}^{\mp}_{1}$ production in roughly a 7:2 ratio for all chargino masses considered.

Predicted signal yields for the 2017 data-taking period, corresponding to $41.5\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $700\,\text{GeV}{}$ in the case of a purely wino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2017 data-taking period, corresponding to $41.5\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $700\,\text{GeV}{}$ in the case of a purely higgsino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2017 data-taking period, corresponding to $41.5\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $300\,\text{GeV}{}$ in the case of a purely wino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2017 data-taking period, corresponding to $41.5\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $300\,\text{GeV}{}$ in the case of a purely higgsino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2018A data-taking period, corresponding to $21.1\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $700\,\text{GeV}{}$ in the case of a purely wino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2018A data-taking period, corresponding to $21.1\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $700\,\text{GeV}{}$ in the case of a purely higgsino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2018A data-taking period, corresponding to $21.1\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $300\,\text{GeV}{}$ in the case of a purely wino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2018A data-taking period, corresponding to $21.1\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $300\,\text{GeV}{}$ in the case of a purely higgsino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2018B data-taking period, corresponding to $38.6\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $700\,\text{GeV}{}$ in the case of a purely wino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2018B data-taking period, corresponding to $38.6\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $700\,\text{GeV}{}$ in the case of a purely higgsino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2018B data-taking period, corresponding to $38.6\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $300\,\text{GeV}{}$ in the case of a purely wino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Predicted signal yields for the 2018B data-taking period, corresponding to $38.6\,\text{fb}^{-1}$, after the application of each search requirement for three chargino lifetime hypotheses ($\tau = 0.3$, $3.3$, and $33\,\text{ns}{}$) with a chargino mass of $300\,\text{GeV}{}$ in the case of a purely higgsino neutralino LSP. Excepting the final three, the requirements listed are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. In the case of the final three requirements on the number of tracker layers with measurement, these are exclusive signal category selections where only one is applied for each category. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events, in the case of a purely wino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2017 data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1}$ events, in the case of a purely wino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2017 data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events, in the case of a purely higgsino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2017 data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1,2}$ events, in the case of a purely higgsino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1,2}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2017 data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events, in the case of a purely wino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2018A data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1}$ events, in the case of a purely wino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2018A data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events, in the case of a purely higgsino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2018A data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1,2}$ events, in the case of a purely higgsino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1,2}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2018A data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events, in the case of a purely wino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2018B data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1}$ events, in the case of a purely wino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2018B data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events, in the case of a purely higgsino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^\mp_{1}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2018B data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Signal acceptance times efficiency ($A\times\epsilon$) for each of the generated chargino masses and lifetimes for $\mathrm{p}\mathrm{p} \rightarrow \widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1,2}$ events, in the case of a purely higgsino neutralino LSP. The denominator for the acceptance is the total number of $\widetilde{\chi}^\pm_{1} \widetilde{\chi}^0_{1,2}$ events generated, while the numerator is the number of those events that are selected by the signal selection after being processed with the same reconstruction software used on the data. These $A\times\epsilon$ values correspond to the conditions simulated for the 2018B data-taking period. The uncertainties are only the statistical uncertainties resulting from the sizes of the generated samples.

Summary of the estimated backgrounds and the observation. The first and second uncertainties shown are the statistical and systematic contributions, respectively.

Detector-level photon $\phi$ distribution

Detector-level dipoton invariant mass distribution

Detector-level diphoton rapidity distribution

Detector-level dipoton p$_{T}$ distribution

Observed exclusion limits at 95% CL in the ALP-photon coupling g$_{a \gamma}$ versus ALP mass $m_{a}$ plane.

Covariance of the differential absolute cross section as a function of the parton-level top quark rapidity

Differential absolute cross section as a function of the parton-level charged lepton $p_\textrm{T}$

Covariance of the differential absolute cross section as a function of the parton-level charged lepton $p_\textrm{T}$

Differential absolute cross section as a function of the parton-level charged lepton rapidity

Covariance of the differential absolute cross section as a function of the parton-level charged lepton rapidity

Differential absolute cross section as a function of the parton-level W boson $p_\textrm{T}$

Covariance of the differential absolute cross section as a function of the parton-level W boson $p_\textrm{T}$

Differential absolute cross section as a function of the parton-level cosine of the top quark polarisation angle

Covariance of the differential absolute cross section as a function of the parton-level cosine of the top quark polarisation angle

Differential absolute cross section as a function of the particle-level top quark $p_\textrm{T}$

Covariance of the differential absolute cross section as a function of the particle-level top quark $p_\textrm{T}$

Differential absolute cross section as a function of the particle-level top quark rapidity

Covariance of the differential absolute cross section as a function of the particle-level top quark rapidity

Differential absolute cross section as a function of the particle-level charged lepton $p_\textrm{T}$

Covariance of the differential absolute cross section as a function of the particle-level charged lepton $p_\textrm{T}$

Differential absolute cross section as a function of the particle-level charged lepton rapidity

Covariance of the differential absolute cross section as a function of the particle-level charged lepton rapidity

Differential absolute cross section as a function of the particle-level W boson $p_\textrm{T}$

Covariance of the differential absolute cross section as a function of the particle-level W boson $p_\textrm{T}$

Differential absolute cross section as a function of the particle-level cosine of the top quark polarisation angle

Covariance of the differential absolute cross section as a function of the particle-level cosine of the top quark polarisation angle

Differential normalised cross section as a function of the parton-level top quark $p_\textrm{T}$

Covariance of the differential normalised cross section as a function of the parton-level top quark $p_\textrm{T}$

Differential normalised cross section as a function of the parton-level top quark rapidity

Covariance of the differential normalised cross section as a function of the parton-level top quark rapidity

Differential normalised cross section as a function of the parton-level charged lepton $p_\textrm{T}$

Covariance of the differential normalised cross section as a function of the parton-level charged lepton $p_\textrm{T}$

Differential normalised cross section as a function of the parton-level charged lepton rapidity

Covariance of the differential normalised cross section as a function of the parton-level charged lepton rapidity

Differential normalised cross section as a function of the parton-level W boson $p_\textrm{T}$

Covariance of the differential normalised cross section as a function of the parton-level W boson $p_\textrm{T}$

Differential normalised cross section as a function of the parton-level cosine of the top quark polarisation angle

Covariance of the differential normalised cross section as a function of the parton-level cosine of the top quark polarisation angle

Differential normalised cross section as a function of the particle-level top quark $p_\textrm{T}$

Covariance of the differential normalised cross section as a function of the particle-level top quark $p_\textrm{T}$

Differential normalised cross section as a function of the particle-level top quark rapidity

Covariance of the differential normalised cross section as a function of the particle-level top quark rapidity

Differential normalised cross section as a function of the particle-level charged lepton $p_\textrm{T}$

Covariance of the differential normalised cross section as a function of the particle-level charged lepton $p_\textrm{T}$

Differential normalised cross section as a function of the particle-level charged lepton rapidity

Covariance of the differential normalised cross section as a function of the particle-level charged lepton rapidity

Differential normalised cross section as a function of the particle-level W boson $p_\textrm{T}$

Covariance of the differential normalised cross section as a function of the particle-level W boson $p_\textrm{T}$

Differential normalised cross section as a function of the particle-level cosine of the top quark polarisation angle

Covariance of the differential normalised cross section as a function of the particle-level cosine of the top quark polarisation angle

Differential charge ratio as a function of the parton-level top quark $p_\textrm{T}$

Covariance of the differential charge ratio as a function of the parton-level top quark $p_\textrm{T}$

Differential charge ratio as a function of the parton-level top quark rapidity

Covariance of the differential charge ratio as a function of the parton-level top quark rapidity

Differential charge ratio as a function of the parton-level charged lepton $p_\textrm{T}$

Covariance of the differential charge ratio as a function of the parton-level charged lepton $p_\textrm{T}$

Differential charge ratio as a function of the parton-level charged lepton rapidity

Covariance of the differential charge ratio as a function of the parton-level charged lepton rapidity

Differential charge ratio as a function of the parton-level W boson $p_\textrm{T}$

Covariance of the differential charge ratio as a function of the parton-level W boson $p_\textrm{T}$

Differential charge ratio as a function of the particle-level top quark $p_\textrm{T}$

Covariance of the differential charge ratio as a function of the particle-level top quark $p_\textrm{T}$

Differential charge ratio as a function of the particle-level top quark rapidity

Covariance of the differential charge ratio as a function of the particle-level top quark rapidity

Differential charge ratio as a function of the particle-level charged lepton $p_\textrm{T}$

Covariance of the differential charge ratio as a function of the particle-level charged lepton $p_\textrm{T}$

Differential charge ratio as a function of the particle-level charged lepton rapidity

Covariance of the differential charge ratio as a function of the particle-level charged lepton rapidity

Differential charge ratio as a function of the particle-level W boson $p_\textrm{T}$

Covariance of the differential charge ratio as a function of the particle-level W boson $p_\textrm{T}$

Top quark spin asymmetry at the parton level in the muon and electron channel and their combination

The covariance matrix containing the statistical uncertainties of Figure 2a is shown.

The covariance matrix containing the experimental uncertainties of Figure 2a is shown.

The covariance matrix containing the model uncertainties of Figure 2a is shown.

The covariance matrix containing the statistical uncertainties of Figure 2b is shown.

The covariance matrix containing the experimental uncertainties of Figure 2b is shown.

The covariance matrix containing the model uncertainties of Figure 2b is shown.

The measured inclusive fiducial cross section measurements. The WW fiducial region is defined by requiring two same-sign leptons with $p_{T}>20$, $|\eta|<2.5$, and $m_{ll}>20$, and two jets with $m_{jj}>500$ and $|\Delta \eta_{jj}|>2.5$. The jets at generator level are clustered from stable particles, excluding neutrinos, using the anti-kt clustering algorithm with R = 0.4, and are required to have $p_{T}>50$ and $|\eta|<4.7$. The jets within $\Delta R<0.4$ of the selected charged leptons are not included. The WZ fiducial region is defined by requiring three leptons with $p_{T}>20$, $|\eta|<2.5$, a pair of opposite charge same-flavor lepton pair with $|m_{ll}-m_{Z}|<15$, and two jets with $m_{jj}>500$ and $|\Delta \eta_{jj}|>2.5$.

Distributions of $m_{jj}$ in the WW signal region.

Distributions of $m_{ll}$ in the WW signal region.

Distributions of $m_{jj}$ in the WZ signal region.

Distributions of BDT score in the WZ signal region.

Absolute WW cross section in $m_{jj}$ bins.

Normalized WW cross section in $m_{jj}$ bins.

Absolute WW cross section in $m_{ll}$ bins.

Normalized WW cross section in $m_{ll}$ bins.

Absolute WW cross section in $p_{T}^{l max}$ bins.

Normalized WW cross section in $p_{T}^{l max}$ bins.

Absolute WZ cross section in $m_{jj}$ bins.

Normalized WZ cross section in $m_{jj}$ bins.

Distributions of $m_{T}^{WW}$ in the WW signal region.

Distributions of $m_{T}^{WZ}$ in the WZ signal region.

Observed and expected lower and upper 95\% confidence level limits in TeV$^{-4}$ on the parameters of the quartic, obtained without using any unitarization procedure.

Observed and expected lower and upper 95\% confidence level limits in TeV$^{-4}$ on the parameters of the quartic by cutting the EFT expansion at the unitarity limit.

The fiducial cross section measured in bins of the azimuthal angle difference between the mesons for events in the fiducial region with 2 Y(1S) with absolute rapidity less than 2.0.

The expected and observed 95% CL limits on the product of the cross section and branching fraction for a tetraquark. The branching fraction is the product of the branching fraction for the decay of the resonance to a Y(1S) meson and two muons, and the Y(1S) meson dimuon branching fraction.

The expected and observed 95% CL limits on the product of the cross section and branching fraction for a scalar state. The branching fraction is the product of the branching fraction for the decay of the resonance to a Y(1S) meson and two muons, and the Y(1S) meson dimuon branching fraction.

The expected and observed 95% CL limits on the product of the cross section and branching fraction for a pseudoscalar state. The branching fraction is the product of the branching fraction for the decay of the resonance to a Y(1S) meson and two muons, and the Y(1S) meson dimuon branching fraction.

The expected and observed 95% CL limits on the product of the cross section and branching fraction for a spin-2 state. The branching fraction is the product of the branching fraction for the decay of the resonance to a Y(1S) meson and two muons, and the Y(1S) meson dimuon branching fraction.

Kinematic properties and charges of the four muons selected in data in the signal region for the measurement of the YY production cross section. MUON1 and MUON2 form the dimuon pair associated to the dimuon object required at trigger-level. The invariant mass of both muon pairs is between 8.6 and 11 GeV. All events pass the trigger requirements and have four muons with a total charge of 0 and with vertex probability above 5%. The muons have pT above 3.5 GeV if they have an absolute pseudorapidity below 0.9 and 2.5 GeV otherwise. The muons pass the medium muon identification criterion.

The normalized doubly-differential cross section within the fiducial region as a function of the $\phi^*$ (phi*) variable and rapidity

The covariance matrix for the absolute differential cross section within the fiducial region as a function of the $\phi^*$ (phi*) variable

The covariance matrix for the normalized differential cross section within the fiducial region as a function of the $\phi^*$ (phi*) variable

The covariance matrix for the absolute doubly-differential cross section within the fiducial region as a function of the $\phi^*$ (phi*) variable and rapidity

The covariance matrix for the normalized doubly-differential cross section within the fiducial region as a function of the $\phi^*$ (phi*) variable and rapidity

Model-independent constraints on the coupling strength modifier as a function of the heavy scalar boson mass, for a relative width of 5.0%.

Model-independent constraints on the coupling strength modifier as a function of the heavy scalar boson mass, for a relative width of 10.0%.

Model-independent constraints on the coupling strength modifier as a function of the heavy scalar boson mass, for a relative width of 25.0%.

Model-independent constraints on the coupling strength modifier as a function of the heavy pseudoscalar boson mass, for a relative width of 0.5%.

Model-independent constraints on the coupling strength modifier as a function of the heavy pseudoscalar boson mass, for a relative width of 0.5%.

Model-independent constraints on the coupling strength modifier as a function of the heavy pseudoscalar boson mass, for a relative width of 1.0%.

Model-independent constraints on the coupling strength modifier as a function of the heavy pseudoscalar boson mass, for a relative width of 1.0%.

Model-independent constraints on the coupling strength modifier as a function of the heavy pseudoscalar boson mass, for a relative width of 2.5%.

Model-independent constraints on the coupling strength modifier as a function of the heavy pseudoscalar boson mass, for a relative width of 2.5%.

Model-independent constraints on the coupling strength modifier as a function of the heavy pseudoscalar boson mass, for a relative width of 5.0%.

Model-independent constraints on the coupling strength modifier as a function of the heavy pseudoscalar boson mass, for a relative width of 5.0%.

Model-independent constraints on the coupling strength modifier as a function of the heavy pseudoscalar boson mass, for a relative width of 10.0%.

Model-independent constraints on the coupling strength modifier as a function of the heavy pseudoscalar boson mass, for a relative width of 10.0%.

Model-independent constraints on the coupling strength modifier as a function of the heavy pseudoscalar boson mass, for a relative width of 25.0%.

Model-independent constraints on the coupling strength modifier as a function of the heavy pseudoscalar boson mass, for a relative width of 25.0%.

Exclusion in the (mA, tan beta) plane of the hMSSM. Both H and A boson signals are included with masses and widths that correspond to a given point in the plane.

Exclusion in the (mA, tan beta) plane of the hMSSM. Both H and A boson signals are included with masses and widths that correspond to a given point in the plane.

Electron pT in data and SM backgrounds, and various aTGC scenarios after the event preselection, in the electron channel.

Measured cross section and signal strength, relative to the standard model expectation.

One-dimensional limits on the ATGC EFT parameters at 95% CL.

One-dimensional limits on the ATGC effective Lagrangian (LEP parametrization) parameters at 95% CL.

One-dimensional limits on the ATGC EFT parameters at 95% CL from the combination of EW Wjj and EW Zjj analyses.

One-dimensional limits on the ATGC effective Lagrangian (LEP parametrization) parameters at 95% CL from the combination of EW Wjj and EW Zjj analyses.

Hadronic activity veto efficiencies in the signal-enriched BDT> 0.95 region for the muon and electron channels combined, as a function of the leading additional jet $p_T$. The data are compared with the background-only prediction as well as background+signal with PYTHIA parton showering and background+signal with HERWIG++ parton showering. In addition, the background+signal prediction from POWHEG plus HERWIG++ parton showering is included. The uncertainty bands include only the statistical uncertainty in the prediction from simulation.

Hadronic activity veto efficiencies in the signal-enriched BDT> 0.95 region for the muon and electron channels combined, as a function of additional jet $H_T$. The data are compared with the background-only prediction as well as background+signal with PYTHIA parton showering and background+signal with HERWIG++ parton showering. In addition, the background+signal prediction from POWHEG plus HERWIG++ parton showering is included. The uncertainty bands include only the statistical uncertainty in the prediction from simulation.

Hadronic activity veto efficiencies in the signal-enriched BDT> 0.95 region for the muon and electron channels combined, as a function of leading soft-activity jet $p_T$. The data are compared with the background-only prediction as well as background+signal with PYTHIA parton showering and background+signal with HERWIG++ parton showering. In addition, the background+signal prediction from POWHEG plus HERWIG++ parton showering is included. The uncertainty bands include only the statistical uncertainty in the prediction from simulation.

Hadronic activity veto efficiencies in the signal-enriched BDT> 0.95 region for the muon and electron channels combined, as a function of soft-activity jet $H_T$. The data are compared with the background-only prediction as well as background+signal with PYTHIA parton showering and background+signal with HERWIG++ parton showering. In addition, the background+signal prediction from POWHEG plus HERWIG++ parton showering is included. The uncertainty bands include only the statistical uncertainty in the prediction from simulation.

Double-differential cross section times the dimuon branching fraction of the Y(2S) meson for different ranges of pT in bins of |y| and for the full |y| < 1.2 range, for the unpolarized decay hypothesis. The global uncertainty in the integrated luminosity of 2.3% is not included in the systematic uncertainties.

Double-differential cross section times the dimuon branching fraction of the Y(3S) meson for different ranges of pT in bins of |y| and for the full |y| < 1.2 range, for the unpolarized decay hypothesis. The global uncertainty in the integrated luminosity of 2.3% is not included in the systematic uncertainties.

Multiplicative scaling factors to obtain the J/psi differential cross sections for different polarization scenarios (Lambda_{Theta} = +1, +0.10, -1) from the unpolarized cross section measurements given in Table 1.

Multiplicative scaling factors to obtain the psi(2S) differential cross sections for different polarization scenarios (Lambda_{Theta} = +1, +0.03, -1) from the unpolarized cross section measurements given in Table 2.

Multiplicative scaling factors to obtain the Y(1S) differential cross sections for different polarization scenarios (Lambda_{Theta} = +1, k, -1) from the unpolarized cross section measurements given in Table 3. The parameter k corresponds to a linear interpolation of the CMS measured value as a function of pT for pT < 50 GeV. For pT > 50 GeV, where no measurements exist, k is taken as the average of all the measured values for pT < 50 GeV.

Multiplicative scaling factors to obtain the Y(2S) differential cross sections for different polarization scenarios (Lambda_{Theta} = +1, k, -1) from the unpolarized cross section measurements given in Table 3. The parameter k corresponds to a linear interpolation of the CMS measured value as a function of pT for pT < 50 GeV. For pT > 50 GeV, where no measurements exist, k is taken as the average of all the measured values for pT < 50 GeV.

Multiplicative scaling factors to obtain the Y(3S) differential cross sections for different polarization scenarios (Lambda_{Theta} = +1, k, -1) from the unpolarized cross section measurements given in Table 3. The parameter k corresponds to a linear interpolation of the CMS measured value as a function of pT for pT < 50 GeV. For pT > 50 GeV, where no measurements exist, k is taken as the average of all the measured values for pT < 50 GeV.

Ratio of differential cross section times branching fractions of the prompt psi(2S) to J/psi mesons assuming unpolarized productions as a function of pT for |y| < 1.2.

Ratios of differential cross section times branching fractions of the prompt Y(2S) to Y(1S) and Y(3S) to Y(1S) mesons assuming unpolarized productions as a function of pT for |y| < 1.2.

Differential cross section dsigma(Z+c)/dpTZ times branching ratio and differential cross sections ratio dsigma(Z+c)/dpTZ / dsigma(Z+b)/dpTZ for three ranges of the transverse momentum of the Z boson and combining the dielectron and dimuon Z0 decay channels

Differential cross section dsigma(Z+c)/dpTjet times branching ratio and differential cross sections ratio dsigma(Z+c)/dpTZ / dsigma(Z+b)/dpTjet for three ranges of the transverse momentum of the jet and combining the dielectron and dimuon Z0 decay channels

Transverse momentum distribution of the selected muon-inside-a-jet for events with an identified muon among the jet constituents in the dielectron channel

Transverse momentum distribution of the selected muon-inside-a-jet for events with an identified muon among the jet constituents in the dimuon channel

The invariant mass distribution of three-prong secondary vertices for events selected in the D± mode, in the dielectron channel

The invariant mass distribution of three-prong secondary vertices for events selected in the D ± mode, in the dimuon channel

The invariant mass distribution of the three-track system composed of a two-prong secondary vertex and a primary particle for events selected in the D∗(2010)± mode, in the dielectron channel

The invariant mass distribution of the three-track system composed of a two-prong secondary vertex and a primary particle for events selected in the D ∗ (2010) ± mode, in the dimuon channel

Transverse momentum distribution of the c-tagged jet normalized to unity, in simulated W+c and Z+c samples and in W+c data events.

Number of reconstructed secondary vertices normalized to unity, in simulated W+c and Z+c samples and in W+c data events.

Distribution of the corrected secondary-vertex mass normalized to unity, in simulated W + c and Z + c samples, and in W + c data events.

Distribution of the JP discriminant for the D± mode normalized to unity, in simulated W + c and Z + c samples, and in W + c data events.

Distribution of the JP discriminant for the D∗(2010) ± mode normalized to unity, in simulated W + c and Z + c samples, and in W + c data events.

Distribution of the corrected secondary-vertex mass normalized to unity from simulated Z + b and eμ-tt data events

Corrected secondary-vertex mass distributions, after background subtraction in the dielectron channel for events selected in the semileptonic mode.

Corrected secondary-vertex mass distributions, after background subtraction in the dimuon channel for events selected in the semileptonic mode.

Background-subtracted distributions of the JP discriminant in the dielectron channel for Z + jets events with a D± → K∓ π± π± candidate.

Background-subtracted distributions of the JP discriminant in the dimuon channel for Z + jets events with a D± → K∓ π± π± candidate.

Background-subtracted distributions of the JP discriminant in the dielectron channel for Z +jets events with a D∗(2010)± → D0 π± → K∓ π± π± candidate.

Background-subtracted distributions of the JP discriminant in the dimuon channel for Z +jets events with a D∗(2010)± → D0 π± → K∓ π± π± candidate.

ontributions to the systematic uncertainty in the measured Z+c cross section and in the (Z+c)/(Z+b) cross section ratio.

Differential Z + c cross section as a function of the transverse momentum of the Z boson

(Z +c)/(Z +b) cross section ratio as a function of the transverse momentum of teh Z boson

Differential Z + c cross section as a function of the transverse momentum of the jet

(Z +c)/(Z +b) cross section ratio as a function of the transverse momentum of the jet.

$v_3\{4\}$ as a function of $N_{trk}^{offline}$ in PbPb collisions at $\sqrt{s_{NN}} = 5.02$ TeV.

$v_2\{4\}$ as a function of $N_{trk}^{offline}$ in pPb collisions at $\sqrt{s_{NN}} = 8.16$ TeV.

$v_2\{6\}$ as a function of $N_{trk}^{offline}$ in pPb collisions at $\sqrt{s_{NN}} = 8.16$ TeV.

$v_2\{6\}$ as a function of $N_{trk}^{offline}$ in pPb collisions at $\sqrt{s_{NN}} = 8.16$ TeV.

$v_3\{4\}$ as a function of $N_{trk}^{offline}$ in pPb collisions at $\sqrt{s_{NN}} = 8.16$ TeV.

$v_2\{4\}/v_2\{2\}$ as a function of $N_{trk}^{offline}$ in PbPb collisions at $\sqrt{s_{NN}} = 5.02$ TeV.

$v_3\{4\}/v_3\{2\}$ as a function of $N_{trk}^{offline}$ in PbPb collisions at $\sqrt{s_{NN}} = 5.02$ TeV.

$v_2\{4\}/v_2\{2\}$ as a function of $N_{trk}^{offline}$ in pPb collisions at $\sqrt{s_{NN}} = 8.16$ TeV.

$v_3\{4\}/v_3\{2\}$ as a function of $N_{trk}^{offline}$ in pPb collisions at $\sqrt{s_{NN}} = 8.16$ TeV.

$v_2\{6\}/v_2\{4\}$ as a function of $v_2\{4\}/v_2\{2\}$ in pPb collisions at $\sqrt{s_{NN}} = 8.16$ TeV.

$v_2\{8\}/v_2\{6\}$ as a function of $v_2\{4\}/v_2\{2\}$ in pPb collisions at $\sqrt{s_{NN}} = 8.16$ TeV.

Expected and observed exclusion limits (95% CL, in the asymptotic approximation) on the product of the production cross section and branching fraction into two photons for an additional SM-like Higgs boson, for the VBF plus VH processes, from the analysis of the 8 TeV data. The inner and outer bands indicate the regions containing the distribution of limits located within $pm 1 and 2 $sigma, respectively, of the expectation under the background-only hypothesis.

Expected and observed exclusion limits (95% CL, in the asymptotic approximation) on the product of the production cross section and branching fraction into two photons for an additional SM-like Higgs boson, for the ggH plus ttH processes, from the analysis of the 13 TeV data. The inner and outer bands indicate the regions containing the distribution of limits located within $pm 1 and 2 $sigma, respectively, of the expectation under the background-only hypothesis.

Expected and observed exclusion limits (95% CL, in the asymptotic approximation) on the product of the production cross section and branching fraction into two photons for an additional SM-like Higgs boson, for the VBF plus VH processes, from the analysis of the 13 (bottom) TeV data. The inner and outer bands indicate the regions containing the distribution of limits located within $pm 1 and 2 $sigma, respectively, of the expectation under the background-only hypothesis.

Expected and observed exclusion limits (95% CL, in the asymptotic approximation) on the product of the production cross section and branching fraction into two photons for an additional Higgs boson, relative to the expected SM-like value, from the analysis of the 8 and 13 TeV data. The inner and outer bands indicate the regions containing the distribution of limits located within $pm 1 and 2 $sigma , respectively, of the expectation under the background-only hypothesis.

Observed yields and pre-fit background predictions for Njets 8-9.

Observed yields and pre-fit background predictions for Njets >=10.

Observed yields and pre-fit background predictions for aggregated bins.

Pre-fit background covariance matrix $\sigma_{xy}$ for the 174 analysis bins.

Pre-fit background correlation matrix $\rho_{xy}$ for the 174 analysis bins.

Observed yields and post-fit background predictions for Njets 2-3.

Observed yields and post-fit background predictions for Njets 4-5.

Observed yields and post-fit background predictions for Njets 6-7.

Observed yields and post-fit background predictions for Njets 8-9.

Observed yields and post-fit background predictions for Njets >=10.

Simulated signal yields for representative gluino signal model light-LSP points in the aggregate search regions. The uncertainties shown are statistical.

Simulated signal yields for representative gluino signal model compressed points in the aggregate search regions. The uncertainties shown are statistical.

Simulated signal yields for representative squark signal model light-LSP points in the aggregate search regions. The uncertainties shown are statistical.

Simulated signal yields for representative squark signal model compressed points in the aggregate search regions. The uncertainties shown are statistical.

The 95% CL observed and expected upper limits on the production cross sections of the T1tttt signal model as a function of the gluino and LSP masses.

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

The 95% CL observed and expected upper limits on the production cross sections of the T1bbbb signal model as a function of the gluino and LSP masses.

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

The 95% CL observed and expected upper limits on the production cross sections of the T1qqqq signal model as a function of the gluino and LSP masses.

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

The 95% CL observed and expected upper limits on the production cross sections of the T5qqqqVV signal model as a function of the gluino and LSP masses.

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

The 95% CL observed and expected upper limits on the production cross sections of the T2tt signal model as a function of the top squark and LSP masses.

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

The 95% CL observed and expected upper limits on the production cross sections of the T2bb signal model as a function of the bottom squark and LSP masses.

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

The 95% CL observed and expected upper limits on the production cross sections of the T2qq signal model as a function of the LSP and light squark masses.

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (u d s c)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (u d s c)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (u d s c)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (u d s c)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (u d s c)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (u d s c)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (u d s c)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (single flavor)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (single flavor)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (single flavor)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (single flavor)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (single flavor)

The observed significance of the SMS models for T1tttt as function of the gluino and LSP masses.

The observed significance of the SMS models for T1bbbb as function of the gluino and LSP masses.

The observed significance of the SMS models for T1qqqq as function of the gluino and LSP masses.

The observed significance of the SMS models for T5qqqqVV as function of the gluino and LSP masses.

The observed significance of the SMS models for T2tt as function of the top squark and LSP masses.

The observed significance of the SMS models for T2bb as function of the bottom squark and LSP masses.

The observed significance of the SMS models for T2qq as function of the LSP and light squark masses.

The efficiency times acceptance of the SMS models for T1tttt as function of the gluino and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions.

The efficiency times acceptance of the SMS models for T1bbbb as function of the gluino and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions.

The efficiency times acceptance of the SMS models for T1qqqq as function of the gluino and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions.

The efficiency times acceptance of the SMS models for T5qqqqVV as function of the gluino and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions.

The efficiency times acceptance of the SMS models for T2tt as function of the top squark and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions.

The efficiency times acceptance of the SMS models for T2bb as function of the bottom squark and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions.

The efficiency times acceptance of the SMS models for T2qq as function of the LSP and light squark masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions.

Absolute cumulative efficiencies in percent for each step of the event selection process, listed for four representative gluino pair production signal models with m(gluino) >> m(LSP). Only statistical uncertainties are shown.

Absolute cumulative efficiencies in percent for each step of the event selection process, listed for four representative gluino pair production signal models with m(gluino) ~ m(LSP). Only statistical uncertainties are shown.

Absolute cumulative efficiencies in percent for each step of the event selection process, listed for three representative squark pair production signal models with m(squark) >> m(LSP). Only statistical uncertainties are shown.

Absolute cumulative efficiencies in percent for each step of the event selection process, listed for three representative squark pair production signal models with m(squark) ~ m(LSP). Only statistical uncertainties are shown.

The $ {{{\mathrm {B}}}\to {\mathrm {D^0}}} $ nuclear modification factor $ {R_{\mathrm {AA}}} $ for PbPb collisions at ${\sqrt {\smash [b]{s_{_{\mathrm {NN}}}}}} = $ 5.02 TeV.

The ratio of the production cross sections of inclusive $\Lambda_{c}^{+}$ to prompt $D^{0}$ versus $p_{T}$ from pp collisions. The $20\%$ normalization uncertainty in pp collisions is not included in the statistical and systematic uncertainties for each data point.

The ratio of the production cross sections of inclusive $\Lambda_{c}^{+}$ to prompt $D^{0}$ versus $p_{T}$ from $0-100\%$ centrality PbPb collisions. The $31\%$ normalization uncertainty in PbPb collisions, is not included in the statistical and systematic uncertainties for each data point.

Summary of the fitted yields for $B^{0}\rightarrow \mu^{+}\mu^{-}$ for all 14 categories of the 3D UML branching fraction fit.

Summary of the fitted yields for the combinatorial background for 5.2$<$$m_{\mu^{+}\mu^{-}}$$<$5.45 GeV for all 14 categories of the 3D UML branching fraction fit.

Summary of the fitted yields for the $B^{+}\rightarrow J/\psi K^{+}$ normalization for all 14 categories of the 3D UML branching fraction fit.

Summary of the average $p_{T}$ of the $B_{s}^{0}\rightarrow \mu^{+}\mu^{-}$ signal for all 14 categories of the 3D UML branching fraction fit.

Summary of the ratio of efficiencies between the normalization and the signal for all 14 categories of the 3D UML branching fraction fit.

Result of the branching fraction for $B_{s}^{0}\rightarrow \mu^{+}\mu^{-}$, $B^{0}\rightarrow \mu^{+}\mu^{-}$.

Summary of the effective lifetime of $B_{s}^{0}$ meson for $B_{s}^{0}\rightarrow \mu^{+}\mu^{-}$.

1 sigma contour from figure 6 (left)

2 sigma contour from figure 6 (left)

Experimental Xi values and FJF predictions for the four NRQCD terms using BK LDME parameters

Experimental Xi values and FJF predictions for the four NRQCD terms using BCKL LDME parameters

Experimental Xi values and FJF predictions for the four NRQCD terms using BK LDME parameters

Rapidity dependence of $R_{\mathrm{pPb}}$ for prompt $\psi$(2S) mesons at $\sqrt(s_{\textrm{NN}})=5.02 $ TeV, in three $p_{\mathrm{T}}$ ranges. The fully correlated global uncertainty of 4.2% is not inlcuded in the point-by-point uncertainty.

Transverse momentum dependence of $R_{\mathrm{pPb}}$ for prompt $\psi$(2S) mesons at $\sqrt(s_{\textrm{NN}})=5.02 $ TeV, in seven $y_{\mathrm{CM}}$ ranges. The fully correlated global uncertainty of 4.2% is not inlcuded in the point-by-point uncertainty.

Ratios of B+ differential production cross sections at 13 TeV and at 7 TeV as a function of |yB| for 10 < ptB < 100 GeV or 17 < ptB < 100 GeV. The calculations from FONLL and PYTHIA are provided as well.

B+ differential production cross sections DSIG/DPT for |yB|< 1.45 or |yB|< 2.1, at 13 TeV. The calculations from FONLL and PYTHIA are provided.

B+ differential production cross sections DSIG/DETARAP for 10 < ptB < 100 GeV or 17 < ptB < 100 GeV, at 13 TeV. The calculations from FONLL and PYTHIA are provided.

B+ production cross section for the phase-space region of 10 <= pTB < 17 GeV and |yB| < 1.45, and 17 <= pTB < 100 GeV and |yB| < 2.1. The calculations from FONLL and PYTHIA are provided.

Yield ratios of chi_c2 over chi_c1 mesons as a function of costh (HX) in the J/psi pT range 8-12 GeV

Yield ratios of chi_c2 over chi_c1 mesons as a function of costh (HX) in the J/psi pT range 12-18 GeV

Yield ratios of chi_c2 over chi_c1 mesons as a function of costh (HX) in the J/psi pT range 18-30 GeV

The $L_{T}$ distribution in the MisID-enriched region. The last bin contains the overflow events.

The $L_{T}+p^{miss}_{T}$ distribution in the 3L below-Z signal region. The last bin contains the overflow events.

The $M_{T}$ distribution in the 3L on-Z signal region. The last bin contains the overflow events.

The $L_{T}+p^{miss}_{T}$ distribution in the 3L above-Z signal region. The last bin contains the overflow events.

The $L_{T}+p^{miss}_{T}$ distribution in the 3L OSSF0 signal region. The last bin contains the overflow events.

The $L_{T}+p^{miss}_{T}$ distribution in the 4L OSSF0 signal region. The last bin contains the overflow events.

The $L_{T}+p^{miss}_{T}$ distribution in the 4L OSSF1 signal region. The last bin contains the overflow events.

The $L_{T}+p^{miss}_{T}$ distribution in the 4L OSSF2 signal region. The last bin contains the overflow events.

The dielectron $M_{OSSF}^{20}$ distribution in the 3L(ee) 0B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{300}$ distribution in the 3L(ee) 0B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{20}$ distribution in the 3L(ee) 0B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{300}$ distribution in the 3L(ee) 0B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{20}$ distribution in the 3L(ee) 0B, $S_{T}$>800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{300}$ distribution in the 3L(ee) 0B, $S_{T}$>800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{20}$ distribution in the 3L(ee) 1B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{300}$ distribution in the 3L(ee) 1B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{20}$ distribution in the 3L(ee) 1B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{300}$ distribution in the 3L(ee) 1B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{20}$ distribution in the 3L(ee) 1B, $S_{T}$>800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{300}$ distribution in the 3L(ee) 1B, $S_{T}$>800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{20}$ distribution in the 4L(ee) 0B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{300}$ distribution in the 4L(ee) 0B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{20}$ distribution in the 4L(ee) 0B, $S_{T}$>400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{300}$ distribution in the 4L(ee) 0B, $S_{T}$>400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{20}$ distribution in the 4L(ee) 1B signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dielectron $M_{OSSF}^{300}$ distribution in the 4L(ee) 1B signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.

The dimuon $M_{OSSF}^{20}$ distribution in the 3L($\mu\mu$) 0B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.

The dimuon $M_{OSSF}^{300}$ distribution in the 3L($\mu\mu$) 0B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.

The dimuon $M_{OSSF}^{20}$ distribution in the 3L($\mu\mu$) 0B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.

The dimuon $M_{OSSF}^{300}$ distribution in the 3L($\mu\mu$) 0B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.

The dimuon $M_{OSSF}^{20}$ distribution in the 3L($\mu\mu$) 0B, $S_{T}$>800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.

The dimuon $M_{OSSF}^{300}$ distribution in the 3L($\mu\mu$) 0B, $S_{T}$>800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.

The dimuon $M_{OSSF}^{20}$ distribution in the 3L($\mu\mu$) 1B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.

The dimuon $M_{OSSF}^{300}$ distribution in the 3L($\mu\mu$) 1B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.

The dimuon $M_{OSSF}^{20}$ distribution in the 3L($\mu\mu$) 1B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.

The dimuon $M_{OSSF}^{300}$ distribution in the 3L($\mu\mu$) 1B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.