The best-fit predicted and observed distributions of the combined NN output in the high-$p_\text{T}$-SR for the $\mu\tau_e$ channel. The first and last bin include underflow and overflow events, respectively.

The best-fit predicted and observed distributions of the collinear mass $m_\text{coll}$ in the high-$p_\text{T}$-SR for the $e\tau_\mu$ channel. The first and last bin include underflow and overflow events, respectively.

The best-fit predicted and observed distributions of the collinear mass $m_\text{coll}$ in the high-$p_\text{T}$-SR for the $\mu\tau_e$ channel. The first and last bin include underflow and overflow events, respectively.

Observed and expected upper limits on $\mathcal{B}(Z\rightarrow\ell\tau)$ with leptonically decaying $\tau$ at 95% confidence level.

Observed and expected upper limits on $\mathcal{B}(Z\rightarrow\ell\tau)$ at 95% confidence level, combination of hadronically and leptonically decaying $\tau$ channels.

The best-fit predicted and observed distributions of the collinear mass $m_\text{coll}$ in the CRZ$\tau\tau$ for the $e\tau_\mu$ channel. The first and last bin include underflow and overflow events, respectively.

The best-fit predicted and observed distributions of the collinear mass $m_\text{coll}$ in the CRZ$\tau\tau$ for the $\mu\tau_e$ channel. The first and last bin include underflow and overflow events, respectively.

The best-fit predicted and observed distributions of the combined NN output in the CRZ$\tau\tau$ for the $e\tau_\mu$ channel. The first and last bin include underflow and overflow events, respectively.

The best-fit predicted and observed distributions of the combined NN output in the CRZ$\tau\tau$ for the $\mu\tau_e$ channel. The first and last bin include underflow and overflow events, respectively.

The best-fit predicted and observed distributions of the leading lepton transverse momentum $p_\text{T}(e)$ in the high-$p_\text{T}$-SR for the $e\tau_\mu$ channel. The first and last bin include underflow and overflow events, respectively.

The best-fit predicted and observed distributions of the leading lepton transverse momentum $p_\text{T}(\mu)$ in the high-$p_\text{T}$-SR for the $\mu\tau_e$ channel. The first and last bin include underflow and overflow events, respectively.

The best-fit predicted and observed distributions of the missing transverse momentum $E^\text{miss}_\text{T}$ in the low-$p_\text{T}$-SR for the $e\tau_\mu$ channel. The first and last bin include underflow and overflow events, respectively.

The best-fit predicted and observed distributions of the missing transverse momentum $E^\text{miss}_\text{T}$ in the low-$p_\text{T}$-SR for the $\mu\tau_e$ channel. The first and last bin include underflow and overflow events, respectively.

The +1 $\sigma$ band of the observed exclusion contor for the $Z^{\prime}_{B}$ model in the $m_{\chi}$-$m_{Z^{\prime}_{B}}$ plane.

The -1 $\sigma$ band of the observed exclusion contor for the $Z^{\prime}_{B}$ model in the $m_{\chi}$-$m_{Z^{\prime}_{B}}$ plane.

A comparison of the inferred limits to the constraints from direct detection experiments on the spin-independent DM--nucleon cross section in the context of the $Z'_B$ simplified model with vector couplings. Limits are shown at 90% CL.

The observed exclusion contor for the $Z^{\prime}$-2HDM model in the $m_{A}$-$m_{Z^{\prime}}$ plane.

The expected exclusion contor for the $Z^{\prime}$-2HDM model in the $m_{A}$-$m_{Z^{\prime}}$ plane.

The +1 $\sigma$ band of the observed exclusion contor for the $m_{A}$-$Z^{\prime}$-2HDM model in the $m_{Z^{\prime}}$ plane.

The -1 $\sigma$ band of the observed exclusion contor for the $m_{A}$-$Z^{\prime}$-2HDM model in the $m_{Z^{\prime}}$ plane.

The observed exclusion contor for the 2HDM-a model in the $m_{A}$-$m_{a}$ plane.

The expected exclusion contor for the 2HDM-a model in the $m_{A}$-$m_{a}$ plane.

The +1 $\sigma$ band of the observed exclusion contor for the 2HDM-a model in the $m_{A}$-$m_{a}$ plane.

The -1 $\sigma$ band of the observed exclusion contor for the 2HDM-a model in the $m_{A}$-$m_{a}$ plane.

The observed exclusion contor for the 2HDM-a model in the $tan\beta$-$m_{a}$ plane.

The expected exclusion contor for the 2HDM-a model in the $tan\beta$-$m_{a}$ plane.

The +1 $\sigma$ band of the observed exclusion contor for the 2HDM-a model in the $tan\beta$-$m_{a}$ plane.

The -1 $\sigma$ band of the observed exclusion contor for the 2HDM-a model in the $tan\beta$-$m_{a}$ plane.

The exclusion limits at 95% CL for the 2HDM+a model as a function of $\sin \theta$ for $m_{A,H^{\pm},H}$= 600GeV, $m_a$ = 200GeV, $\tan \beta$ = 1.0$.

The exclusion limits at 95% CL for the 2HDM+a model as a function of $\sin \theta$ for $m_{A,H^{\pm},H}$= 1000GeV, $m_a$ = 350GeV, $\tan \beta$ = 1.0$.

Breakdown of the dominant systematic uncertainties.

Event yields in the range of 120 $<m_{\gamma\gamma}<$ 130 GeV for data, signal models, the SM Higgs boson background and non-resonant background in each analysis category, for an integrated luminosity of $139$fb$^{-1}$.

Detailed background contributions from the SM Higgs boson and continuum background for each cut

Detailed contributions from the signals for each cut.

Acceptance times efficiency for several signals in each category.

The definitions of the four tetralepton signal regions. The regions are defined to target different $b$-jet multiplicities and flavour combinations of the non-Z leptons.

The absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}$ of the $Z$ boson in the 3$\ell$+4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}$ of the $Z$ boson in the 3$\ell$+4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}$ of the $Z$ boson in the 3$\ell$+4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}$ of the $Z$ boson in the 3$\ell$+4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the absolute value of rapidity of the $Z$ boson in the 3$\ell$+4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the number of jets in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the number of jets in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{l \textrm{non-}Z}$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta y (Z, t_{\textrm{lep}})|$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (t\bar{t}, Z)|/\pi$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{t\bar{t}}$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{l \textrm{non-}Z}$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta y (Z, t_{\textrm{lep}})|$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (t\bar{t}, Z)|/\pi$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{t\bar{t}}$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the absolute value of rapidity of the $Z$ boson in the 3$\ell$+4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{l \textrm{non-}Z}$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta y (Z, t_{\textrm{lep}})|$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (t\bar{t}, Z)|/\pi$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{t\bar{t}}$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the absolute value of rapidity of the $Z$ boson in the 3$\ell$+4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{l \textrm{non-}Z}$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta y (Z, t_{\textrm{lep}})|$ in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (t\bar{t}, Z)|/\pi$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{t\bar{t}}$ in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the absolute value of rapidity of the $Z$ boson in the 3$\ell$+4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the number of jets in the 3$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the number of jets in the 4$\ell$ channel. The uncertainty is decomposed into four components which are the signal modelling uncertainty, the background modelling uncertainty, the experimental uncertainty, and the data statistical uncertainty.

The total correlation matrix of the absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}$ of the $Z$ boson in the 3$\ell$+4$\ell$ channel.

The total correlation matrix of the absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the absolute value of rapidity of the $Z$ boson in the 3$\ell$+4$\ell$ channel.

The total correlation matrix of the absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{l \textrm{non-}Z}$ in the 3$\ell$ channel.

The total correlation matrix of the absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel.

The total correlation matrix of the absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta y (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel.

The total correlation matrix of the absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the 4$\ell$ channel.

The total correlation matrix of the absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (t\bar{t}, Z)|/\pi$ in the 4$\ell$ channel.

The total correlation matrix of the absolute parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{t\bar{t}}$ in the 4$\ell$ channel.

The total correlation matrix of the normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}$ of the $Z$ boson in the 3$\ell$+4$\ell$ channel.

The total correlation matrix of the normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the absolute value of rapidity of the $Z$ boson in the 3$\ell$+4$\ell$ channel.

The total correlation matrix of the normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{l \textrm{non-}Z}$ in the 3$\ell$ channel.

The total correlation matrix of the normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel.

The total correlation matrix of the normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta y (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel.

The total correlation matrix of the normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the 4$\ell$ channel.

The total correlation matrix of the normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (t\bar{t}, Z)|/\pi$ in the 4$\ell$ channel.

The total correlation matrix of the normalised parton-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{t\bar{t}}$ in the 4$\ell$ channel.

The total correlation matrix of the absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}$ of the $Z$ boson in the 3$\ell$+4$\ell$ channel.

The total correlation matrix of the absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the absolute value of rapidity of the $Z$ boson in the 3$\ell$+4$\ell$ channel.

The total correlation matrix of the absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{l \textrm{non-}Z}$ in the 3$\ell$ channel.

The total correlation matrix of the absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel.

The total correlation matrix of the absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta y (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel.

The total correlation matrix of the absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the number of jets in the 3$\ell$ channel.

The total correlation matrix of the absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the 4$\ell$ channel.

The total correlation matrix of the absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (t\bar{t}, Z)|/\pi$ in the 4$\ell$ channel.

The total correlation matrix of the absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{t\bar{t}}$ in the 4$\ell$ channel.

The total correlation matrix of the absolute particle-level differential cross-section measured in the fiducial phase-space as a function of the number of jets in the 4$\ell$ channel.

The total correlation matrix of the normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}$ of the $Z$ boson in the 3$\ell$+4$\ell$ channel.

The total correlation matrix of the normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the absolute value of rapidity of the $Z$ boson in the 3$\ell$+4$\ell$ channel.

The total correlation matrix of the normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{l \textrm{non-}Z}$ in the 3$\ell$ channel.

The total correlation matrix of the normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel.

The total correlation matrix of the normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta y (Z, t_{\textrm{lep}})|/\pi$ in the 3$\ell$ channel.

The total correlation matrix of the normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the number of jets in the 3$\ell$ channel.

The total correlation matrix of the normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the 4$\ell$ channel.

The total correlation matrix of the normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $|\Delta \phi (t\bar{t}, Z)|/\pi$ in the 4$\ell$ channel.

The total correlation matrix of the normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the $p_{\textrm{T}}^{t\bar{t}}$ in the 4$\ell$ channel.

The total correlation matrix of the normalised particle-level differential cross-section measured in the fiducial phase-space as a function of the number of jets in the 4$\ell$ channel.

The $m_{\mathrm{eff}}$ distribution in SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$ and SR0$_{\mathrm{bveto}}^{\mathrm{tight}}$ for events passing the signal region requirements except the $m_{\mathrm{eff}}$ requirement. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band. The red arrows indicate the $m_{\mathrm{eff}}$ selections in the signal regions.

The $m_{\mathrm{eff}}$ distribution in SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$ and SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$ for events passing the signal region requirements except the $m_{\mathrm{eff}}$ requirement. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band. The red arrows indicate the $m_{\mathrm{eff}}$ selections in the signal regions.

The $m_{\mathrm{eff}}$ distribution in SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$ and SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$ for events passing the signal region requirements except the $m_{\mathrm{eff}}$ requirement. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band. The red arrows indicate the $m_{\mathrm{eff}}$ selections in the signal regions.

The $m_{\mathrm{eff}}$ distribution in SR0$_{\mathrm{breq}}$ for events passing the signal region requirements except the $m_{\mathrm{eff}}$ requirement. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band. The red arrows indicate the $m_{\mathrm{eff}}$ selections in the signal regions.

The $m_{\mathrm{eff}}$ distribution in SR1$_{\mathrm{breq}}$ for events passing the signal region requirements except the $m_{\mathrm{eff}}$ requirement. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band. The red arrows indicate the $m_{\mathrm{eff}}$ selections in the signal regions.

The $m_{\mathrm{eff}}$ distribution in SR2$_{\mathrm{breq}}$ for events passing the signal region requirements except the $m_{\mathrm{eff}}$ requirement. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band. The red arrows indicate the $m_{\mathrm{eff}}$ selections in the signal regions.

Expected 95% CL exclusion limits on the higgsino GGM models. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

$+1\sigma$ expected 95% CL exclusion limits on the higgsino GGM models. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

$-1\sigma$ expected 95% CL exclusion limits on the higgsino GGM models. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

Observed 95% CL exclusion limits on the higgsino GGM models. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

$+1\sigma$ observed 95% CL exclusion limits on the higgsino GGM models. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

$-1\sigma$ observed 95% CL exclusion limits on the higgsino GGM models. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

Expected 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

$+1\sigma$ expected 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

$-1\sigma$ expected 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

Observed 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

$+1\sigma$ bserved 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

$-1\sigma$ observed 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

Expected 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

$+1\sigma$ expected 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

$-1\sigma$ expected 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

Observed 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

$+1\sigma$ observed 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

$-1\sigma$ observed 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

Expected 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

$+1\sigma$ expected 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

$-1\sigma$ expected 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

Observed 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

$+1\sigma$ observed 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

$-1\sigma$ observed 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

Expected 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

$+1\sigma$ expected 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

$-1\sigma$ expected 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

Observed 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

$+1\sigma$ observed 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

$-1\sigma$ observed 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

Expected 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

$+1\sigma$ expected 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

$-1\sigma$ expected 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

Observed 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

$+1\sigma$ observed 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

$-1\sigma$ observed 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

Expected 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

$+1\sigma$ expected 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

$-1\sigma$ expected 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

Observed 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

$+1\sigma$ observed 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

$-1\sigma$ observed 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.

Observed upper limit on the signal cross section in fb for the wino NLSP models with RPV LSP decays via $\lambda_{12k}$ where $k \in{1,2}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Observed upper limit on the signal cross section in fb for the wino NLSP models with RPV LSP decays via $\lambda_{i33}$ where $i \in{1,2}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Observed upper limit on the signal cross section in fb for the slepton/sneutrino NLSP models with RPV LSP decays via $\lambda_{12k}$ where $k \in{1,2}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Observed upper limit on the signal cross section in fb for the slepton/sneutrino NLSP models with RPV LSP decays via $\lambda_{i33}$ where $i \in{1,2}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Observed upper limit on the signal cross section in fb for the gluino NLSP models with RPV LSP decays via $\lambda_{12k}$ where $k \in{1,2}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Observed upper limit on the signal cross section in fb for the gluino NLSP models with RPV LSP decays via $\lambda_{i33}$ where $i \in{1,2}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Observed upper limit on the signal cross section in fb for the higgsino GGM models. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Best expected SR for the wino NLSP models with RPV LSP decays via $\lambda_{12k}$ where $k \in{1,2}$. A value of 1 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 2 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, 3 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 4 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, and 5 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{tight}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$.

Best expected SR for the wino NLSP models with RPV LSP decays via $\lambda_{i33}$ where $i \in{1,2}$. A value of 1 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 2 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, 3 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 4 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, and 5 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{tight}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$.

Best expected SR for the slepton/sneutrino NLSP models with RPV LSP decays via $\lambda_{12k}$ where $k \in{1,2}$. A value of 1 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 2 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, 3 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 4 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, and 5 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{tight}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$.

Best expected SR for the slepton/sneutrino NLSP models with RPV LSP decays via $\lambda_{i33}$ where $i \in{1,2}$. A value of 1 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 2 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, 3 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 4 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, and 5 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{tight}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$.

Best expected SR for the gluino NLSP models with RPV LSP decays via $\lambda_{12k}$ where $k \in{1,2}$. A value of 1 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 2 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, 3 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 4 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, and 5 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{tight}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$.

Best expected SR for the gluino NLSP models with RPV LSP decays via $\lambda_{i33}$ where $i \in{1,2}$. A value of 1 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 2 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, 3 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 4 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, and 5 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{tight}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$.

Best expected SR for the higgsino GGM models. A value of 6 corresponds to SR0-ZZ$^{\mathrm{loose}}$, 7 corresponds to SR0-ZZ$^{\mathrm{tight}}$, 8 corresponds to SR0-ZZ$^{\mathrm{loose}}_{\mathrm{bveto}}$, and 9 corresponds to SR0-ZZ$^{\mathrm{tight}}_{\mathrm{bveto}}$.

Acceptance across the wino NLSP $\lambda_{12k}\neq 0$ models for SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Efficiency across the wino NLSP $\lambda_{12k}\neq 0$ models for SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Acceptance across the wino NLSP $\lambda_{12k}\neq 0$ models for SR0$_{\mathrm{bveto}}^{\mathrm{tight}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Efficiency across the wino NLSP $\lambda_{12k}\neq 0$ models for SR0$_{\mathrm{bveto}}^{\mathrm{tight}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Acceptance across the wino NLSP $\lambda_{12k}\neq 0$ models for SR0$_{\mathrm{breq}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Efficiency across the wino NLSP $\lambda_{12k}\neq 0$ models for SR0$_{\mathrm{breq}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Acceptance across the wino NLSP $\lambda_{i33}\neq 0$ models for SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Efficiency across the wino NLSP $\lambda_{i33}\neq 0$ models for SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Acceptance across the wino NLSP $\lambda_{i33}\neq 0$ models for SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Efficiency across the wino NLSP $\lambda_{i33}\neq 0$ models for SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Acceptance across the wino NLSP $\lambda_{i33}\neq 0$ models for SR1$_{\mathrm{breq}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Efficiency across the wino NLSP $\lambda_{i33}\neq 0$ models for SR1$_{\mathrm{breq}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Acceptance across the wino NLSP $\lambda_{i33}\neq 0$ models for SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Efficiency across the wino NLSP $\lambda_{i33}\neq 0$ models for SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Acceptance across the wino NLSP $\lambda_{i33}\neq 0$ models for SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Efficiency across the wino NLSP $\lambda_{i33}\neq 0$ models for SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Acceptance across the wino NLSP $\lambda_{i33}\neq 0$ models for SR2$_{\mathrm{breq}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Efficiency across the wino NLSP $\lambda_{i33}\neq 0$ models for SR2$_{\mathrm{breq}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Acceptance across the GGM Higgsino grid for SR0-ZZ$^{\mathrm{loose}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Efficiency across the GGM Higgsino grid for SR0-ZZ$^{\mathrm{loose}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Acceptance across the GGM Higgsino grid for SR0-ZZ$^{\mathrm{tight}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Efficiency across the GGM Higgsino grid for SR0-ZZ$^{\mathrm{tight}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Acceptance across the GGM Higgsino grid for SR0-ZZ$_{\mathrm{bveto}}^{\mathrm{loose}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Efficiency across the GGM Higgsino grid for SR0-ZZ$_{\mathrm{bveto}}^{\mathrm{loose}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Acceptance across the GGM Higgsino grid for SR0-ZZ$_{\mathrm{bveto}}^{\mathrm{tight}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

Efficiency across the GGM Higgsino grid for SR0-ZZ$_{\mathrm{bveto}}^{\mathrm{tight}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.

The $p_{\mathrm{T}}$ of the light leptons in distribution in SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.

The $p_{\mathrm{T}}$ of the light leptons in distribution in SR0-ZZ$^{\mathrm{loose}}$. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.

The $p_{\mathrm{T}}$ of the light leptons in distribution in SR0-ZZ$^{\mathrm{tight}}$. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.

The $p_{\mathrm{T}}$ of the light leptons in distribution in SR0-ZZ$_{\mathrm{bveto}}^{\mathrm{loose}}$. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.

The $p_{\mathrm{T}}$ of the light leptons in distribution in SR5L. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.

The $p_{\mathrm{T}}$ of the light leptons in distribution in SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.

The $p_{\mathrm{T}}$ of the taus leptons in distribution in SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.

The $p_{\mathrm{T}}$ of the light taus in distribution in SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.

The lepton flavour and multiplicities in events with four light leptons and a Z veto. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.

The lepton flavour and multiplicities in events with four light leptons and one Z candidate. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.

The lepton flavour and multiplicities in events with four light leptons and two Z candidates. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.

The lepton flavour and multiplicities in events with exactly five light leptons. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.

The lepton flavour and multiplicities in events with three light leptons and one tau and a Z veto. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.

The lepton flavour and multiplicities in events with three light leptons and one tau and one Z candidate. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.

The lepton flavour and multiplicities in events with two light leptons and two taus and a Z veto. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.

The lepton flavour and multiplicities in events with two light leptons and two taus and one Z candidate. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.

Cutflow event yields in regions SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$, SR0$_{\mathrm{bveto}}^{\mathrm{tight}}$, SR0$_{\mathrm{breq}}$, and SR5L for RPV models with the $\lambda_{12k}\neq 0$ coupling. All yields correspond to weighted events, so that effects from lepton reconstruction efficiencies, trigger corrections, pileup reweighting, etc., are included. They are normalized to the integrated luminosity of the data sample, $\int L dt = 139\,\mbox{fb\(^{-1}\)}$. The preliminary event reduction is a centralized stage where at least two electrons/muons with uncalibrated $p_{\mathrm{T}} >$ 9 GeV are required.

Cutflow event yields in regions SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$, SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$, and SR1$_{\mathrm{breq}}$ for RPV models with the $\lambda_{i33}\neq 0$ coupling. All yields correspond to weighted events, so that effects from lepton reconstruction efficiencies, trigger corrections, pileup reweighting, etc., are included. They are normalized to the integrated luminosity of the data sample, $\int L dt = 139\,\mbox{fb\(^{-1}\)}$. The preliminary event reduction is a centralized stage where at least two electrons/muons with uncalibrated $p_{\mathrm{T}} >$ 9 GeV are required.

Cutflow event yields in regions SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, and SR2$_{\mathrm{breq}}$ for RPV models with the $\lambda_{i33}\neq 0$ coupling. All yields correspond to weighted events, so that effects from lepton reconstruction efficiencies, trigger corrections, pileup reweighting, etc., are included. They are normalized to the integrated luminosity of the data sample, $\int L dt = 139\,\mbox{fb\(^{-1}\)}$. The preliminary event reduction is a centralized stage where at least two electrons/muons with uncalibrated $p_{\mathrm{T}} >$ 9 GeV are required.

Cutflow event yields in regions SR0-ZZ$^{\mathrm{loose}}$, SR0-ZZ$^{\mathrm{tight}}$, SR0-ZZ$_{\mathrm{bveto}}^{\mathrm{loose}}$, SR0-ZZ$_{\mathrm{bveto}}^{\mathrm{tight}}$, and SR5L the higgsino GGM RPC model with BR($\tilde{\chi}^{0}_1 \rightarrow Z \tilde{G}$) = 50% and higgsino masses of 200 GeV, or BR($\tilde{\chi}^{0}_1 \rightarrow Z \tilde{G}$) = 100% and higgsino masses of 300 GeV. All yields correspond to weighted events, so that effects from lepton reconstruction efficiencies, trigger corrections, pileup reweighting, etc., are included. They are normalized to the integrated luminosity of the data sample, $\int L dt = 139\,\mbox{fb\(^{-1}\)}$. The generator filter is a selection of $\geq$4e/$\mu$/$\tau_{\mathrm{had-vis}}$ leptons with $p_{\mathrm{T}}(e,\mu)>4$GeV, $p_{\mathrm{T}}(\tau_{\mathrm{had-vis}})>15$GeV and $|\eta|<2.8$ and is applied during the MC generation of the simulated events. The preliminary event reduction is a centralized stage where at least two electrons/muons with uncalibrated $p_{\mathrm{T}} > 9$ GeV are required.

The best-fit expected and observed distributions of the combined NN output in the VRSS for the $e\tau$ channel for events with 3-prong $\tau_\text{had-vis}$ candidates. The last bin in each plot includes overflow events.

The best-fit expected and observed distributions of the combined NN output in the SR for the $e\tau$ channel for events with 1-prong $\tau_\text{had-vis}$ candidates. The last bin in each plot includes overflow events.

The best-fit expected and observed distributions of the combined NN output in the SR for the $e\tau$ channel for events with 3-prong $\tau_\text{had-vis}$ candidates. The last bin in each plot includes overflow events.

The best-fit expected and observed distributions of the combined NN output in the SR for the $\mu\tau$ channel for events with 1-prong $\tau_\text{had-vis}$ candidates. The last bin in each plot includes overflow events.

The best-fit expected and observed distributions of the combined NN output in the SR for the $\mu\tau$ channel for events with 3-prong $\tau_\text{had-vis}$ candidates. The last bin in each plot includes overflow events.

Observed and expected upper limits on $\mathcal{B}(Z\rightarrow\ell\tau)$ at 95% confidence level.

The number of data and fitted simulated events in each bin of the $|d_{0}^{\mu}|$ distribution in the $10<p_{\textrm{T}}^{\mu}<20$ GeV selection in the $\mu-\mu$ channel.

The number of data and fitted simulated events in each bin of the $|d_{0}^{\mu}|$ distribution in the $20<p_{\textrm{T}}^{\mu}<250$ GeV selection in the $e-\mu$ channel.

The number of data and fitted simulated events in each bin of the $|d_{0}^{\mu}|$ distribution in the $20<p_{\textrm{T}}^{\mu}<250$ GeV selection in the $\mu-\mu$ channel.

The measurement of the ratio of the rate of decay of W bosons to τ-leptons and muons, $R(\tau/\mu)=B(W\rightarrow\tau\nu_\tau)/B(W\rightarrow \mu\nu_\mu)$.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 80 to 110 GeV and absolute values of the jet rapidity from 0 to 2.8.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 110 to 160 GeV and absolute values of the jet rapidity from 0 to 2.8.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 160 to 210 GeV and absolute values of the jet rapidity from 0 to 2.8.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 210 to 260 GeV and absolute values of the jet rapidity from 0 to 2.8.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 260 to 310 GeV and absolute values of the jet rapidity from 0 to 2.8.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 310 to 400 GeV and absolute values of the jet rapidity from 0 to 2.8.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 400 to 500 GeV and absolute values of the jet rapidity from 0 to 2.8.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 500 to 600 GeV and absolute values of the jet rapidity from 0 to 2.8.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 30 to 40 GeV and absolute values of the jet rapidity from 0 to 0.3. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 30 to 40 GeV and absolute values of the jet rapidity from 0.3 to 0.8. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 30 to 40 GeV and absolute values of the jet rapidity from 0.8 to 1.2. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 30 to 40 GeV and absolute values of the jet rapidity from 1.2 to 2.1. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 30 to 40 GeV and absolute values of the jet rapidity from 2.1 to 2.8. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 40 to 60 GeV and absolute values of the jet rapidity from 0 to 0.3. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 40 to 60 GeV and absolute values of the jet rapidity from 0.3 to 0.8. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 40 to 60 GeV and absolute values of the jet rapidity from 0.8 to 1.2. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 40 to 60 GeV and absolute values of the jet rapidity from 1.2 to 2.1. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 40 to 60 GeV and absolute values of the jet rapidity from 2.1 to 2.8. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 60 to 80 GeV and absolute values of the jet rapidity from 0 to 0.3. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 60 to 80 GeV and absolute values of the jet rapidity from 0.3 to 0.8. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 60 to 80 GeV and absolute values of the jet rapidity from 0.8 to 1.2. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 60 to 80 GeV and absolute values of the jet rapidity from 1.2 to 2.1. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 60 to 80 GeV and absolute values of the jet rapidity from 2.1 to 2.8. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 80 to 110 GeV and absolute values of the jet rapidity from 0 to 0.3. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 80 to 110 GeV and absolute values of the jet rapidity from 0.3 to 0.8. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 80 to 110 GeV and absolute values of the jet rapidity from 0.8 to 1.2. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 80 to 110 GeV and absolute values of the jet rapidity from 1.2 to 2.1. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 80 to 110 GeV and absolute values of the jet rapidity from 2.1 to 2.8. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 110 to 160 GeV and absolute values of the jet rapidity from 0 to 0.3. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 110 to 160 GeV and absolute values of the jet rapidity from 0.3 to 0.8. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 110 to 160 GeV and absolute values of the jet rapidity from 0.8 to 1.2. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 110 to 160 GeV and absolute values of the jet rapidity from 1.2 to 2.1. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 110 to 160 GeV and absolute values of the jet rapidity from 2.1 to 2.8. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 160 to 210 GeV and absolute values of the jet rapidity from 0 to 0.3. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 160 to 210 GeV and absolute values of the jet rapidity from 0.3 to 0.8. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 160 to 210 GeV and absolute values of the jet rapidity from 0.8 to 1.2. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 160 to 210 GeV and absolute values of the jet rapidity from 1.2 to 2.1. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 160 to 210 GeV and absolute values of the jet rapidity from 2.1 to 2.8. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 210 to 260 GeV and absolute values of the jet rapidity from 0 to 0.3. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 210 to 260 GeV and absolute values of the jet rapidity from 0.3 to 0.8. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 210 to 260 GeV and absolute values of the jet rapidity from 0.8 to 1.2. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 210 to 260 GeV and absolute values of the jet rapidity from 1.2 to 2.1. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 210 to 260 GeV and absolute values of the jet rapidity from 2.1 to 2.8. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 260 to 310 GeV and absolute values of the jet rapidity from 0 to 0.3. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 260 to 310 GeV and absolute values of the jet rapidity from 0.3 to 0.8. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 260 to 310 GeV and absolute values of the jet rapidity from 0.8 to 1.2. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 260 to 310 GeV and absolute values of the jet rapidity from 1.2 to 2.1. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 260 to 310 GeV and absolute values of the jet rapidity from 2.1 to 2.8. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 310 to 400 GeV and absolute values of the jet rapidity from 0 to 0.3. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 310 to 400 GeV and absolute values of the jet rapidity from 0.3 to 0.8. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 310 to 400 GeV and absolute values of the jet rapidity from 0.8 to 1.2. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 310 to 400 GeV and absolute values of the jet rapidity from 1.2 to 2.1. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 400 to 500 GeV and absolute values of the jet rapidity from 0 to 0.3. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 400 to 500 GeV and absolute values of the jet rapidity from 0.3 to 0.8. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 400 to 500 GeV and absolute values of the jet rapidity from 0.8 to 1.2. This is additional data, not in the paper.

Measured Differential Jet Shape RHO as a function of r for jet transverse momentum from 400 to 500 GeV and absolute values of the jet rapidity from 1.2 to 2.1. This is additional data, not in the paper.

Measured Integrated Jet Shape 1-PSI as a function of jet transverse momentum for an r value of 0.3 and absolute values of the jet rapidity from 0 to 2.8.

Measured Integrated Jet Shape 1-PSI as a function of jet transverse momentum for an r value of 0.3 and absolute values of the jet rapidity from 0 to 0.3.

Measured Integrated Jet Shape 1-PSI as a function of jet transverse momentum for an r value of 0.3 and absolute values of the jet rapidity from 0.3 to 0.8.

Measured Integrated Jet Shape 1-PSI as a function of jet transverse momentum for an r value of 0.3 and absolute values of the jet rapidity from 0.8 to 1.2.

Measured Integrated Jet Shape 1-PSI as a function of jet transverse momentum for an r value of 0.3 and absolute values of the jet rapidity from 1.2 to 2.1.

Measured Integrated Jet Shape 1-PSI as a function of jet transverse momentum for an r value of 0.3 and absolute values of the jet rapidity from 2.1 to 2.8.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 30 to 40 GeV and absolute values of the jet rapidity from 0 to 0.3. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 30 to 40 GeV and absolute values of the jet rapidity from 0.3 to 0.8. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 30 to 40 GeV and absolute values of the jet rapidity from 0.8 to 1.2. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 30 to 40 GeV and absolute values of the jet rapidity from 1.2 to 2.1. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 30 to 40 GeV and absolute values of the jet rapidity from 2.1 to 2.8. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 30 to 40 GeV and absolute values of the jet rapidity from 0 to 2.8. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 40 to 60 GeV and absolute values of the jet rapidity from 0 to 0.3. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 40 to 60 GeV and absolute values of the jet rapidity from 0.3 to 0.8. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 40 to 60 GeV and absolute values of the jet rapidity from 0.8 to 1.2. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 40 to 60 GeV and absolute values of the jet rapidity from 1.2 to 2.1. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 40 to 60 GeV and absolute values of the jet rapidity from 2.1 to 2.8. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 40 to 60 GeV and absolute values of the jet rapidity from 0 to 2.8. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 60 to 80 GeV and absolute values of the jet rapidity from 0 to 0.3. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 60 to 80 GeV and absolute values of the jet rapidity from 0.3 to 0.8. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 60 to 80 GeV and absolute values of the jet rapidity from 0.8 to 1.2. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 60 to 80 GeV and absolute values of the jet rapidity from 1.2 to 2.1. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 60 to 80 GeV and absolute values of the jet rapidity from 2.1 to 2.8. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 60 to 80 GeV and absolute values of the jet rapidity from 0 to 2.8. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 80 to 110 GeV and absolute values of the jet rapidity from 0 to 0.3. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 80 to 110 GeV and absolute values of the jet rapidity from 0.3 to 0.8. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 80 to 110 GeV and absolute values of the jet rapidity from 0.8 to 1.2. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 80 to 110 GeV and absolute values of the jet rapidity from 1.2 to 2.1. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 80 to 110 GeV and absolute values of the jet rapidity from 2.1 to 2.8. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 80 to 110 GeV and absolute values of the jet rapidity from 0 to 2.8. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 110 to 160 GeV and absolute values of the jet rapidity from 0 to 0.3. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 110 to 160 GeV and absolute values of the jet rapidity from 0.3 to 0.8. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 110 to 160 GeV and absolute values of the jet rapidity from 0.8 to 1.2. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 110 to 160 GeV and absolute values of the jet rapidity from 1.2 to 2.1. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 110 to 160 GeV and absolute values of the jet rapidity from 2.1 to 2.8. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 110 to 160 GeV and absolute values of the jet rapidity from 0 to 2.8. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 160 to 210 GeV and absolute values of the jet rapidity from 0 to 0.3. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 160 to 210 GeV and absolute values of the jet rapidity from 0.3 to 0.8. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 160 to 210 GeV and absolute values of the jet rapidity from 0.8 to 1.2. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 160 to 210 GeV and absolute values of the jet rapidity from 1.2 to 2.1. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 160 to 210 GeV and absolute values of the jet rapidity from 2.1 to 2.8. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 160 to 210 GeV and absolute values of the jet rapidity from 0 to 2.8. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 210 to 260 GeV and absolute values of the jet rapidity from 0 to 0.3. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 210 to 260 GeV and absolute values of the jet rapidity from 0.3 to 0.8. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 210 to 260 GeV and absolute values of the jet rapidity from 0.8 to 1.2. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 210 to 260 GeV and absolute values of the jet rapidity from 1.2 to 2.1. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 210 to 260 GeV and absolute values of the jet rapidity from 2.1 to 2.8. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 210 to 260 GeV and absolute values of the jet rapidity from 0 to 2.8. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 260 to 310 GeV and absolute values of the jet rapidity from 0 to 0.3. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 260 to 310 GeV and absolute values of the jet rapidity from 0.3 to 0.8. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 260 to 310 GeV and absolute values of the jet rapidity from 0.8 to 1.2. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 260 to 310 GeV and absolute values of the jet rapidity from 1.2 to 2.1. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 260 to 310 GeV and absolute values of the jet rapidity from 2.1 to 2.8. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 260 to 310 GeV and absolute values of the jet rapidity from 0 to 2.8. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 310 to 400 GeV and absolute values of the jet rapidity from 0 to 0.3. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 310 to 400 GeV and absolute values of the jet rapidity from 0.3 to 0.8. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 310 to 400 GeV and absolute values of the jet rapidity from 0.8 to 1.2. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 310 to 400 GeV and absolute values of the jet rapidity from 1.2 to 2.1. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 310 to 400 GeV and absolute values of the jet rapidity from 0 to 2.8. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 400 to 500 GeV and absolute values of the jet rapidity from 0 to 0.3. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 400 to 500 GeV and absolute values of the jet rapidity from 0.3 to 0.8. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 400 to 500 GeV and absolute values of the jet rapidity from 0.8 to 1.2. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 400 to 500 GeV and absolute values of the jet rapidity from 1.2 to 2.1. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 400 to 500 GeV and absolute values of the jet rapidity from 0 to 2.8. This is additional data, not in the paper.

Measured Integrated Jet Shape PSI as a function of r for jet transverse momentum from 500 to 600 GeV and absolute values of the jet rapidity from 0 to 2.8. This is additional data, not in the paper.

Charged-particle multiplicities in proton-proton collisions at a centre-of mass energy of 900 GeV as a function of pseudorapidity for events with the number of charged particles >=2 having transverse momentum >100 MeV and absolute(pseudorapidity) <2.5.

Charged-particle multiplicities in proton-proton collisions at a centre-of mass energy of 7000 GeV as a function of pseudorapidity for events with the number of charged particles >=2 having transverse momentum >100 MeV and absolute(pseudorapidity) <2.5.

Charged-particle multiplicities in proton-proton collisions at a centre-of mass energy of 900 GeV as a function of pseudorapidity for events with the number of charged particles >=6 having transverse momentum >500 MeV and absolute(pseudorapidity) <2.5.

Charged-particle multiplicities in proton-proton collisions at a centre-of mass energy of 7000 GeV as a function of pseudorapidity for events with the number of charged particles >=6 having transverse momentum >500 MeV and absolute(pseudorapidity) <2.5.

Charged-particle multiplicities in proton-proton collisions at a centre-of mass energy of 900 GeV as a function of transverse momentum for events with the number of charged particles >=1 having transverse momentum >500 MeV and absolute(pseudorapidity) <2.5.

Charged-particle multiplicities in proton-proton collisions at a centre-of mass energy of 2360 GeV as a function of transverse momentum for events with the number of charged particles >=1 having transverse momentum >500 MeV and absolute(pseudorapidity) <2.5.

Charged-particle multiplicities in proton-proton collisions at a centre-of mass energy of 7000 GeV as a function of transverse momentum for events with the number of charged particles >=1 having transverse momentum >500 MeV and absolute(pseudorapidity) <2.5.

Charged-particle multiplicities in proton-proton collisions at a centre-of mass energy of 900 GeV as a function of transverse momentum for events with the number of charged particles >=2 having transverse momentum >100 MeV and absolute(pseudorapidity) <2.5.

Charged-particle multiplicities in proton-proton collisions at a centre-of mass energy of 7000 GeV as a function of transverse momentum for events with the number of charged particles >=2 having transverse momentum >100 MeV and absolute(pseudorapidity) <2.5.

Charged-particle multiplicities in proton-proton collisions at a centre-of mass energy of 900 GeV as a function of transverse momentum for events with the number of charged particles >=6 having transverse momentum >500 MeV and absolute(pseudorapidity) <2.5.

Charged-particle multiplicities in proton-proton collisions at a centre-of mass energy of 7000 GeV as a function of transverse momentum for events with the number of charged particles >=6 having transverse momentum >500 MeV and absolute(pseudorapidity) <2.5.

Charged-particle multiplicity distributions in proton-proton collisions at a centre-of mass energy of 900 GeV for events with the number of charged particles >=1 having transverse momentum >500 MeV and absolute(pseudorapidity) <2.5.

Charged-particle multiplicity distributions in proton-proton collisions at a centre-of mass energy of 2360 GeV for events with the number of charged particles >=1 having transverse momentum >500 MeV and absolute(pseudorapidity) <2.5.

Charged-particle multiplicity distributions in proton-proton collisions at a centre-of mass energy of 7000 GeV for events with the number of charged particles >=1 having transverse momentum >500 MeV and absolute(pseudorapidity) <2.5.

Charged-particle multiplicity distributions in proton-proton collisions at a centre-of mass energy of 900 GeV for events with the number of charged particles >=2 having transverse momentum >100 MeV and absolute(pseudorapidity) <2.5.

Charged-particle multiplicity distributions in proton-proton collisions at a centre-of mass energy of 7000 GeV for events with the number of charged particles >=2 having transverse momentum >100 MeV and absolute(pseudorapidity) <2.5.

Charged-particle multiplicity distributions in proton-proton collisions at a centre-of mass energy of 900 GeV for events with the number of charged particles >=6 having transverse momentum >500 MeV and absolute(pseudorapidity) <2.5.

Charged-particle multiplicity distributions in proton-proton collisions at a centre-of mass energy of 7000 GeV for events with the number of charged particles >=6 having transverse momentum >500 MeV and absolute(pseudorapidity) <2.5.

Average transverse momentum in proton-proton collisions at a centre-of mass energy of 900 GeV as a function of the number of charged particles in the event for events with the number of charged particles >=1 having transverse momentum >500 MeV and absolute(pseudorapidity) <2.5.

Average transverse momentum in proton-proton collisions at a centre-of mass energy of 7000 GeV as a function of the number of charged particles in the event for events with the number of charged particles >=1 having transverse momentum >500 MeV and absolute(pseudorapidity) <2.5.

Average transverse momentum in proton-proton collisions at a centre-of mass energy of 900 GeV as a function of the number of charged particles in the event for events with the number of charged particles >=2 having transverse momentum >100 MeV and absolute(pseudorapidity) <2.5.

Average transverse momentum in proton-proton collisions at a centre-of mass energy of 7000 GeV as a function of the number of charged particles in the event for events with the number of charged particles >=2 having transverse momentum >100 MeV and absolute(pseudorapidity) <2.5.

Charged-particle multiplicities in proton-proton collisions at a centre-of mass energy of 900 GeV as a function of pseudorapidity for events with the number of charged particles >=20 having transverse momentum >100 MeV and absolute(pseudorapidity) <2.5.

Charged-particle multiplicities in proton-proton collisions at a centre-of mass energy of 7000 GeV as a function of pseudorapidity for events with the number of charged particles >=20 having transverse momentum >100 MeV and absolute(pseudorapidity) <2.5.

Charged-particle multiplicities in proton-proton collisions at a centre-of mass energy of 900 GeV as a function of pseudorapidity for events with the number of charged particles >=1 having transverse momentum >2500 MeV and absolute(pseudorapidity) <2.5.

Charged-particle multiplicities in proton-proton collisions at a centre-of mass energy of 7000 GeV as a function of pseudorapidity for events with the number of charged particles >=1 having transverse momentum >2500 MeV and absolute(pseudorapidity) <2.5.

Charged-particle multiplicities in proton-proton collisions at a centre-of mass energy of 900 GeV as a function of transverse momentum for events with the number of charged particles >=20 having transverse momentum >100 MeV and absolute(pseudorapidity) <2.5.

Charged-particle multiplicities in proton-proton collisions at a centre-of mass energy of 7000 GeV as a function of transverse momentum for events with the number of charged particles >=20 having transverse momentum >100 MeV and absolute(pseudorapidity) <2.5.

Charged-particle multiplicities in proton-proton collisions at a centre-of mass energy of 900 GeV as a function of transverse momentum for events with the number of charged particles >=1 having transverse momentum >2500 MeV and absolute(pseudorapidity) <2.5.

Charged-particle multiplicities in proton-proton collisions at a centre-of mass energy of 7000 GeV as a function of transverse momentum for events with the number of charged particles >=1 having transverse momentum >2500 MeV and absolute(pseudorapidity) <2.5.

Charged-particle multiplicity distributions in proton-proton collisions at a centre-of mass energy of 900 GeV for events with the number of charged particles >=20 having transverse momentum >100 MeV and absolute(pseudorapidity) <2.5.

Charged-particle multiplicity distributions in proton-proton collisions at a centre-of mass energy of 7000 GeV for events with the number of charged particles >=20 having transverse momentum >100 MeV and absolute(pseudorapidity) <2.5.

Charged-particle multiplicity distributions in proton-proton collisions at a centre-of mass energy of 900 GeV for events with the number of charged particles >=1 having transverse momentum >2500 MeV and absolute(pseudorapidity) <2.5.

Charged-particle multiplicity distributions in proton-proton collisions at a centre-of mass energy of 7000 GeV for events with the number of charged particles >=1 having transverse momentum >2500 MeV and absolute(pseudorapidity) <2.5.

Average transverse momentum in proton-proton collisions at a centre-of mass energy of 900 GeV as a function of the number of charged particles in the event for events with the number of charged particles >=1 having transverse momentum >2500 MeV and absolute(pseudorapidity) <2.5.

Average transverse momentum in proton-proton collisions at a centre-of mass energy of 7000 GeV as a function of the number of charged particles in the event for events with the number of charged particles >=1 having transverse momentum >2500 MeV and absolute(pseudorapidity) <2.5.

The average charged-particle muliplicity per unit of rapidity for ETARAP=0 as a function of the centre-of-mass energy.

The average charged-particle muliplicity per unit of rapidity in the pseudorapidity region -2.5 to 2.5 for events with 2 or more charged particles as a function of the centre-of-mass energy.

Measured fiducial cross section times leptonic branching ratio for Z/gamma* production in the Z/gamma* -> e+e- final state.

Measured fiducial cross section times leptonic branching ratio for W+ production in the W+ -> mu+ nu final state.

Measured fiducial cross section times leptonic branching ratio for W- production in the W- -> mu- nubar final state.

Measured fiducial cross section times leptonic branching ratio for W+/- production in the combined W+ -> mu+ nu and W- -> mu- nubar final state.

Measured fiducial cross section times leptonic branching ratio for Z/gamma* production in the Z/gamma* -> mu+ mu- final state.

Measured total cross section times leptonic branching ratio for W+ production in the W+ -> e+ nu final state.

Measured total cross section times leptonic branching ratio for W- production in the W- -> e- nubar final state.

Measured total cross section times leptonic branching ratio for W+/- production in the combined W+ -> e+ nu and W- -> e- nubar final state.

Measured total cross section times leptonic branching ratio for Z/gamma* production in the Z/gamma* -> e+ e- final state.

Measured total cross section times leptonic branching ratio for W+ production in the W+ -> mu+ nu final state.

Measured total cross section times leptonic branching ratio for W- production in the W- -> mu- nubar final state.

Measured total cross section times leptonic branching ratio for W+/- production in the combined W+ -> mu+ nu and W- -> mu- nubar final state.

Measured total cross section times leptonic branching ratio for Z/gamma* production in the Z/gamma* -> mu+ mu- final state.

Measured total cross section times leptonic branching ratio for W+ production in the W+ -> l+ nu (l = e, mu) final states.

Measured total cross section times leptonic branching ratio for W- production in the W- -> l- nubar (l = e, mu) final states.

Measured total cross section times leptonic branching ratio for W+/- production in the combined W+ -> l+ nu and W- -> l- nubar (l = e, mu) final states.

Measured total cross section times leptonic branching ratio for Z/gamma* production in the combined Z/gamma* -> l+ l- (l = e, mu) final states.

Measured total cross-section ratio R_{W+/Z} = sigma (W+ -> e+ nu) / sigma (Z/gamma^* -> e+ e-).

Measured total cross-section ratio R_{W-/Z} = sigma (W- -> e- nubar) / sigma (Z/gamma^* -> e+ e-).

Measured total cross-section ratio R_{W+-/Z} = sigma (W+/- -> e+/- nu/nubar) / sigma (Z/gamma^* -> e+ e-).

Measured total cross-section ratio R_{W+/Z} = sigma (W+ -> mu+ nu) / sigma (Z/gamma^* -> mu+ mu-).

Measured total cross-section ratio R_{W-/Z} = sigma (W- -> mu- nubar) / sigma (Z/gamma^* -> mu+ mu-).

Measured total cross-section ratio R_{W+-/Z} = sigma (W+/- -> mu+/- nu/nubar) / sigma (Z/gamma^* -> mu+ mu-).

Measured total cross-section ratio R_{W+/Z} = sigma (W+ -> l+ nu) / sigma (Z/gamma^* -> l+ l-) where (l = e, mu).

Measured total cross-section ratio R_{W-/Z} = sigma (W- -> l- nubar) / sigma (Z/gamma^* -> l+ l-) where (l = e, mu).

Measured total cross-section ratio R_{W+-/Z} = sigma (W+/- -> l+/- nu/nubar) / sigma (Z/gamma^* -> l+ l-) where (l = e, mu).

Measured lepton asymmetry from W+ -> e+ nu and W- -> e- nubar, binned as a function pseudorapidity.

Measured lepton asymmetry from W+ -> e+ nu and W- -> e- nubar.

Measured lepton asymmetry from W+ -> mu+ nu and W- -> mu- nubar, binned as a function pseudorapidity.

Measured lepton asymmetry from W+ -> mu+ nu and W- -> mu- nubar.

Measured lepton asymmetry from W+ -> l+ nu and W- -> l- nubar (l = e, mu), binned as a function pseudorapidity.

Measured lepton asymmetry from W+ -> l+ nu and W- -> l- nubar (l = e, mu).