Expected and observed upper limits on the AQGC operators $a^Z_C/\Lambda^2$, with no unitarization. The $y$ axis shows the limit on the ratio of the observed cross section to the cross section predicted for each anomalous coupling value ($\sigma_\mathrm{AQGC}$).

Limits on LEP-like dimension-6 anomalous quartic gauge coupling parameters, with and without unitarization via a clipping procedure.

Conversion of limits on $a^W_0$ to dimension-8 $f_{M,i}$ operators, using the assumption of vanishing $WWZ\gamma$ couplings to eliminate some parameters. When quoting limits on one of the operators, the other is fixed to zero. The results for $|f_{M,0}/\Lambda^{4}|$ and $|f_{M,4}/\Lambda^{4}|$ are shown with and without clipping of the signal model at 1.4 TeV, when the other parameter is fixed to the SM value of zero.

Conversion of limits on $a^W_0$ and $a^W_C$ to dimension-8 $f_{M,i}$ operators, using the assumption that all $f_{M,i}$ except one are equal to zero. The results are shown with and without clipping of the signal model at 1.4 TeV.

{Expected and observed limits in the two-dimensional plane of $a^W_0/\Lambda^2$ vs. $a^W_C/\Lambda^2$. The limits are described by analytical ellipses of equation $(x-x0)^2/a^2 + (y-y0)^2/b^2 = 1$ and rotated counter-clockwise by $\theta$ degrees, where $x$ and $y$ in the equation correspond to the $a_0^W$ and $a_C^W$ couplings, respectively.

{Expected and observed limits in the two-dimensional plane of $a^W_0/\Lambda^2$ vs. $a^W_C/\Lambda^2$ with unitarization imposed by clipping the signal model at 1.4 TeV. The limits are described by analytical ellipses of equation $(x-x0)^2/a^2 + (y-y0)^2/b^2 = 1$ and rotated counter-clockwise by $\theta$ degrees, where $x$ and $y$ in the equation correspond to the $a_0^W$ and $a_C^W$ couplings, respectively.

{Expected and observed limits in the two-dimensional plane of $a^Z_0/\Lambda^2$ vs. $a^Z_C/\Lambda^2$. The limits are described by analytical ellipses of equation $(x-x0)^2/a^2 + (y-y0)^2/b^2 = 1$ and rotated counter-clockwise by $\theta$ degrees, where $x$ and $y$ in the equation correspond to the $a_0^Z$ and $a_C^Z$ couplings, respectively.

Correlation between the measured fiducial cross sections in the different bins of $p_{\mathrm{T}}^{\gamma\gamma}$

Differential fiducial higgs to diphoton cross section with respect to $n_{\mathrm{jets}}$

Differential fiducial higgs to diphoton cross section with respect to $n_{\mathrm{jets}}$

Correlation between the measured fiducial cross sections in the different bins of $n_{\mathrm{jets}}$

Correlation between the measured fiducial cross sections in the different bins of $n_{\mathrm{jets}}$

Differential fiducial higgs to diphoton cross section with respect to $\left|\cos\theta^{\ast}\right|$

Differential fiducial higgs to diphoton cross section with respect to $\left|\cos\theta^{\ast}\right|$

Correlation between the measured fiducial cross sections in the different bins of $\left|\cos\theta^{\ast}\right|$

Correlation between the measured fiducial cross sections in the different bins of $\left|\cos\theta^{\ast}\right|$

Differential fiducial higgs to diphoton cross section with respect to $\left|y^{\gamma\gamma}\right|$

Differential fiducial higgs to diphoton cross section with respect to $\left|y^{\gamma\gamma}\right|$

Correlation between the measured fiducial cross sections in the different bins of $\left|y^{\gamma\gamma}\right|$

Correlation between the measured fiducial cross sections in the different bins of $\left|y^{\gamma\gamma}\right|$

Differential fiducial higgs to diphoton cross section with respect to $p_{\mathrm{T}}^{j_{1}}$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Differential fiducial higgs to diphoton cross section with respect to $p_{\mathrm{T}}^{j_{1}}$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Correlation between the measured fiducial cross sections in the different bins of $p_{\mathrm{T}}^{j_{1}}$

Correlation between the measured fiducial cross sections in the different bins of $p_{\mathrm{T}}^{j_{1}}$

Differential fiducial higgs to diphoton cross section with respect to $\left|y^{j_{1}}\right|$

Differential fiducial higgs to diphoton cross section with respect to $\left|y^{j_{1}}\right|$

Correlation between the measured fiducial cross sections in the different bins of $\left|y^{j_{1}}\right|$

Correlation between the measured fiducial cross sections in the different bins of $\left|y^{j_{1}}\right|$

Differential fiducial higgs to diphoton cross section with respect to $\left|\Delta y_{\gamma\gamma,j_{1}}\right|$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Differential fiducial higgs to diphoton cross section with respect to $\left|\Delta y_{\gamma\gamma,j_{1}}\right|$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Correlation between the measured fiducial cross sections in the different bins of $\left|\Delta y_{\gamma\gamma,j_{1}}\right|$

Correlation between the measured fiducial cross sections in the different bins of $\left|\Delta y_{\gamma\gamma,j_{1}}\right|$

Differential fiducial higgs to diphoton cross section with respect to $\left|\Delta\phi_{\gamma\gamma,j_{1}}\right|$

Differential fiducial higgs to diphoton cross section with respect to $\left|\Delta\phi_{\gamma\gamma,j_{1}}\right|$

Correlation between the measured fiducial cross sections in the different bins of $\left|\Delta\phi_{\gamma\gamma,j_{1}}\right|$

Correlation between the measured fiducial cross sections in the different bins of $\left|\Delta\phi_{\gamma\gamma,j_{1}}\right|$

Differential fiducial higgs to diphoton cross section with respect to $p_{\mathrm{T}}^{j_{2}}$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Differential fiducial higgs to diphoton cross section with respect to $p_{\mathrm{T}}^{j_{2}}$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Correlation between the measured fiducial cross sections in the different bins of $p_{\mathrm{T}}^{j_{2}}$

Correlation between the measured fiducial cross sections in the different bins of $p_{\mathrm{T}}^{j_{2}}$

Differential fiducial higgs to diphoton cross section with respect to $\left|y^{j_{2}}\right|$

Differential fiducial higgs to diphoton cross section with respect to $\left|y^{j_{2}}\right|$

Correlation between the measured fiducial cross sections in the different bins of $\left|y^{j_{2}}\right|$

Correlation between the measured fiducial cross sections in the different bins of $\left|y^{j_{2}}\right|$

Differential fiducial higgs to diphoton cross section with respect to $|\Delta\phi_{\gamma\gamma,j_{1}j_{2}}|$

Differential fiducial higgs to diphoton cross section with respect to $|\Delta\phi_{\gamma\gamma,j_{1}j_{2}}|$

Correlation between the measured fiducial cross sections in the different bins of $|\Delta\phi_{\gamma\gamma,j_{1}j_{2}}|$

Correlation between the measured fiducial cross sections in the different bins of $|\Delta\phi_{\gamma\gamma,j_{1}j_{2}}|$

Differential fiducial higgs to diphoton cross section with respect to $|\Delta\phi_{j_{1},j_{2}}|$

Differential fiducial higgs to diphoton cross section with respect to $|\Delta\phi_{j_{1},j_{2}}|$

Correlation between the measured fiducial cross sections in the different bins of $|\Delta\phi_{j_{1},j_{2}}|$

Correlation between the measured fiducial cross sections in the different bins of $|\Delta\phi_{j_{1},j_{2}}|$

Differential fiducial higgs to diphoton cross section with respect to $|\bar{\eta}_{j_{1},j_{2}}-\eta_{\gamma\gamma}|$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Differential fiducial higgs to diphoton cross section with respect to $|\bar{\eta}_{j_{1},j_{2}}-\eta_{\gamma\gamma}|$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Correlation between the measured fiducial cross sections in the different bins of $|\bar{\eta}_{j_{1},j_{2}}-\eta_{\gamma\gamma}|$

Correlation between the measured fiducial cross sections in the different bins of $|\bar{\eta}_{j_{1},j_{2}}-\eta_{\gamma\gamma}|$

Differential fiducial higgs to diphoton cross section with respect to $m_{\mathrm{jj}}$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Differential fiducial higgs to diphoton cross section with respect to $m_{\mathrm{jj}}$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Correlation between the measured fiducial cross sections in the different bins of $m_{\mathrm{jj}}$

Correlation between the measured fiducial cross sections in the different bins of $m_{\mathrm{jj}}$

Differential fiducial higgs to diphoton cross section with respect to $|\Delta\eta_{j_{1},j_{2}}|$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Differential fiducial higgs to diphoton cross section with respect to $|\Delta\eta_{j_{1},j_{2}}|$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Correlation between the measured fiducial cross sections in the different bins of $|\Delta\eta_{j_{1},j_{2}}|$

Correlation between the measured fiducial cross sections in the different bins of $|\Delta\eta_{j_{1},j_{2}}|$

Differential fiducial higgs to diphoton cross section with respect to $n_{\mathrm{leptons}}$

Differential fiducial higgs to diphoton cross section with respect to $n_{\mathrm{leptons}}$

Correlation between the measured fiducial cross sections in the different bins of $n_{\mathrm{leptons}}$

Correlation between the measured fiducial cross sections in the different bins of $n_{\mathrm{leptons}}$

Differential fiducial higgs to diphoton cross section with respect to $n_{\mathrm{b-jets}}$

Differential fiducial higgs to diphoton cross section with respect to $n_{\mathrm{b-jets}}$

Correlation between the measured fiducial cross sections in the different bins of $n_{\mathrm{b-jets}}$

Correlation between the measured fiducial cross sections in the different bins of $n_{\mathrm{b-jets}}$

Differential fiducial higgs to diphoton cross section with respect to $p_{\mathrm{T}}^{\mathrm{miss}}$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Differential fiducial higgs to diphoton cross section with respect to $p_{\mathrm{T}}^{\mathrm{miss}}$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Correlation between the measured fiducial cross sections in the different bins of $p_{\mathrm{T}}^{\mathrm{miss}}$

Correlation between the measured fiducial cross sections in the different bins of $p_{\mathrm{T}}^{\mathrm{miss}}$

Differential fiducial higgs to diphoton cross section with respect to $p_{\mathrm{T}}^{j_{2}}$ in the VBF enriched PS. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Differential fiducial higgs to diphoton cross section with respect to $p_{\mathrm{T}}^{j_{2}}$ in the VBF enriched PS. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Correlation between the measured fiducial cross sections in the different bins of $p_{\mathrm{T}}^{j_{2}}$

Correlation between the measured fiducial cross sections in the different bins of $p_{\mathrm{T}}^{j_{2}}$

Differential fiducial higgs to diphoton cross section with respect to $|\Delta\phi_{\gamma\gamma,j_{1}j_{2}}|$ in the VBF enriched PS

Differential fiducial higgs to diphoton cross section with respect to $|\Delta\phi_{\gamma\gamma,j_{1}j_{2}}|$ in the VBF enriched PS

Correlation between the measured fiducial cross sections in the different bins of $|\Delta\phi_{\gamma\gamma,j_{1}j_{2}}|$

Correlation between the measured fiducial cross sections in the different bins of $|\Delta\phi_{\gamma\gamma,j_{1}j_{2}}|$

Differential fiducial higgs to diphoton cross section with respect to $|\Delta\phi_{j_{1},j_{2}}|$ in the VBF enriched PS

Differential fiducial higgs to diphoton cross section with respect to $|\Delta\phi_{j_{1},j_{2}}|$ in the VBF enriched PS

Correlation between the measured fiducial cross sections in the different bins of $|\Delta\phi_{j_{1},j_{2}}|$

Correlation between the measured fiducial cross sections in the different bins of $|\Delta\phi_{j_{1},j_{2}}|$

Differential fiducial higgs to diphoton cross section with respect to $p_{\mathrm{T}}^{\gamma\gamma}$ in the VBF enriched PS. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Differential fiducial higgs to diphoton cross section with respect to $p_{\mathrm{T}}^{\gamma\gamma}$ in the VBF enriched PS. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Correlation between the measured fiducial cross sections in the different bins of $p_{\mathrm{T}}^{\gamma\gamma}$

Correlation between the measured fiducial cross sections in the different bins of $p_{\mathrm{T}}^{\gamma\gamma}$

Differential fiducial higgs to diphoton cross section with respect to $\tau_{\mathrm{C}}^{j}$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Differential fiducial higgs to diphoton cross section with respect to $\tau_{\mathrm{C}}^{j}$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Correlation between the measured fiducial cross sections in the different bins of $\tau_{\mathrm{C}}^{j}$

Correlation between the measured fiducial cross sections in the different bins of $\tau_{\mathrm{C}}^{j}$

Differential fiducial higgs to diphoton cross section with respect to $\left|\phi_{\eta}^{\ast}\right|$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Differential fiducial higgs to diphoton cross section with respect to $\left|\phi_{\eta}^{\ast}\right|$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Correlation between the measured fiducial cross sections in the different bins of $\left|\phi_{\eta}^{\ast}\right|$

Correlation between the measured fiducial cross sections in the different bins of $\left|\phi_{\eta}^{\ast}\right|$

Differential fiducial higgs to diphoton cross section with respect to $p_{\mathrm{T}}^{\gamma\gamma}$ vs. $\tau_{\mathrm{C}}^{j}$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Differential fiducial higgs to diphoton cross section with respect to $p_{\mathrm{T}}^{\gamma\gamma}$ vs. $\tau_{\mathrm{C}}^{j}$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Differential fiducial higgs to diphoton cross section with respect to $p_{\mathrm{T}}^{\gamma\gamma}$ vs. $\tau_{\mathrm{C}}^{j}$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Differential fiducial higgs to diphoton cross section with respect to $p_{\mathrm{T}}^{\gamma\gamma}$ vs. $\tau_{\mathrm{C}}^{j}$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Differential fiducial higgs to diphoton cross section with respect to $p_{\mathrm{T}}^{\gamma\gamma}$ vs. $\tau_{\mathrm{C}}^{j}$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Differential fiducial higgs to diphoton cross section with respect to $p_{\mathrm{T}}^{\gamma\gamma}$ vs. $\tau_{\mathrm{C}}^{j}$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Differential fiducial higgs to diphoton cross section with respect to $p_{\mathrm{T}}^{\gamma\gamma}$ vs. $\tau_{\mathrm{C}}^{j}$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Differential fiducial higgs to diphoton cross section with respect to $p_{\mathrm{T}}^{\gamma\gamma}$ vs. $\tau_{\mathrm{C}}^{j}$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Correlation between the measured fiducial cross sections in the different bins of $p_{\mathrm{T}}^{\gamma\gamma}$ and $\tau_{\mathrm{C}}^{j}$

Correlation between the measured fiducial cross sections in the different bins of $p_{\mathrm{T}}^{\gamma\gamma}$ and $\tau_{\mathrm{C}}^{j}$

Differential fiducial higgs to diphoton cross section with respect to $p_{\mathrm{T}}^{\gamma\gamma}$ vs. $n_{\mathrm{jets}}$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Differential fiducial higgs to diphoton cross section with respect to $p_{\mathrm{T}}^{\gamma\gamma}$ vs. $n_{\mathrm{jets}}$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Differential fiducial higgs to diphoton cross section with respect to $p_{\mathrm{T}}^{\gamma\gamma}$ vs. $n_{\mathrm{jets}}$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Differential fiducial higgs to diphoton cross section with respect to $p_{\mathrm{T}}^{\gamma\gamma}$ vs. $n_{\mathrm{jets}}$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Differential fiducial higgs to diphoton cross section with respect to $p_{\mathrm{T}}^{\gamma\gamma}$ vs. $n_{\mathrm{jets}}$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Differential fiducial higgs to diphoton cross section with respect to $p_{\mathrm{T}}^{\gamma\gamma}$ vs. $n_{\mathrm{jets}}$. The last bin in the differential observable extends to infinity and the measured fiducial cross section in this bin is devided by the given bin width

Correlation between the measured fiducial cross sections in the different bins of $p_{\mathrm{T}}^{\gamma\gamma}$ and $n_{\mathrm{jets}}$

Correlation between the measured fiducial cross sections in the different bins of $p_{\mathrm{T}}^{\gamma\gamma}$ and $n_{\mathrm{jets}}$

Cross sections measured in different regions of the fiducial phase space

Cross sections measured in different regions of the fiducial phase space

Left pannel. The vertical bars (boxes) represent the statistical (bin-to-bin systematic) uncertainties, while the horizontal bars give the bin widths. The global uncertainty (of 2.3%) is not graphically represented. The blue line represents the average for $p_T > 18$ GeV. For comparison, the LHCb measurement [10.1103/PhysRevLett.124.122002] is also shown. $ 12 < \mathrm{B} \, p_T < 70$ GeV and $ 0 < |y| < 2.4 $. Global uncertanties are not included in the table (2.3%)

Left pannel. The vertical bars (boxes) represent the statistical (bin-to-bin systematic) uncertainties, while the horizontal bars give the bin widths. The global uncertainty (of 2.3%) is not graphically represented. The blue line represents the average for $p_T > 18$ GeV. For comparison, the LHCb measurement [10.1103/PhysRevLett.124.122002] is also shown. $ 12 < \mathrm{B} \, p_T < 70$ GeV and $ 0 < |y| < 2.4 $. Global uncertanties are not included in the table (2.3%)

Left pannel. The vertical bars (boxes) represent the statistical (bin-to-bin systematic) uncertainties, while the horizontal bars give the bin widths. The global uncertainty (of 2.3%) is not graphically represented. The blue line represents the average for $p_T > 18$ GeV. For comparison, the LHCb measurement [10.1103/PhysRevLett.124.122002] is also shown. $ 12 < \mathrm{B} \, p_T < 70$ GeV and $ 0 < |y| < 2.4 $. Global uncertanties are not included in the table (2.3%)

Right pannel. The vertical bars (boxes) represent the statistical (bin-to-bin systematic) uncertainties, while the horizontal bars give the bin widths. The global uncertainty (of 2.3%) is not graphically represented. The blue line represents the average for $p_T > 18$ GeV. For comparison, the LHCb measurement [10.1103/PhysRevLett.124.122002] is also shown. $ 12 < \mathrm{B} \, p_T < 70$ GeV and $ 0 < |y| < 2.4 $. Global uncertanties are not included in the table (2.3%)

Right pannel. The vertical bars (boxes) represent the statistical (bin-to-bin systematic) uncertainties, while the horizontal bars give the bin widths. The global uncertainty (of 2.3%) is not graphically represented. The blue line represents the average for $p_T > 18$ GeV. For comparison, the LHCb measurement [10.1103/PhysRevLett.124.122002] is also shown. $ 12 < \mathrm{B} \, p_T < 70$ GeV and $ 0 < |y| < 2.4 $. Global uncertanties are not included in the table (2.3%)

Right pannel. The vertical bars (boxes) represent the statistical (bin-to-bin systematic) uncertainties, while the horizontal bars give the bin widths. The global uncertainty (of 2.3%) is not graphically represented. The blue line represents the average for $p_T > 18$ GeV. For comparison, the LHCb measurement [10.1103/PhysRevLett.124.122002] is also shown. $ 12 < \mathrm{B} \, p_T < 70$ GeV and $ 0 < |y| < 2.4 $. Global uncertanties are not included in the table (2.3%)

Left panel.The vertical bars (boxes) represent the statistical (bin-to-bin systematic) uncertainties, while the horizontal bars give the bin widths. The global uncertainty (of 4.9\%) is not graphically represented. The blue line represents the average of all the points. $ 12 < \mathrm{B} \, p_T < 70$ GeV and $ 0 < |y| < 2.4 $. Global uncertanties are not included in the table (4.9%)

Left panel.The vertical bars (boxes) represent the statistical (bin-to-bin systematic) uncertainties, while the horizontal bars give the bin widths. The global uncertainty (of 5.7%) is not graphically represented. The blue line represents the average of all the points. $ 12 < \mathrm{B} \, p_T < 70$ GeV and $ 0 < |y| < 2.4 $. Global uncertanties are not included in the table (5.7%)

Left panel.The vertical bars (boxes) represent the statistical (bin-to-bin systematic) uncertainties, while the horizontal bars give the bin widths. The global uncertainty (of 5.7%) is not graphically represented. The blue line represents the average of all the points. $ 12 < \mathrm{B} \, p_T < 70$ GeV and $ 0 < |y| < 2.4 $. Global uncertanties are not included in the table (5.7%)

Right panel.The vertical bars (boxes) represent the statistical (bin-to-bin systematic) uncertainties, while the horizontal bars give the bin widths. The global uncertainty (of 4.9\%) is not graphically represented. The blue line represents the average of all the points. $ 12 < \mathrm{B} \, p_T < 70$ GeV and $ 0 < |y| < 2.4 $. Global uncertanties are not included in the table (4.9%)

Right panel.The vertical bars (boxes) represent the statistical (bin-to-bin systematic) uncertainties, while the horizontal bars give the bin widths. The global uncertainty (of 5.7%) is not graphically represented. The blue line represents the average of all the points. $ 12 < \mathrm{B} \, p_T < 70$ GeV and $ 0 < |y| < 2.4 $. Global uncertanties are not included in the table (5.7%)

Right panel.The vertical bars (boxes) represent the statistical (bin-to-bin systematic) uncertainties, while the horizontal bars give the bin widths. The global uncertainty (of 5.7%) is not graphically represented. The blue line represents the average of all the points. $ 12 < \mathrm{B} \, p_T < 70$ GeV and $ 0 < |y| < 2.4 $. Global uncertanties are not included in the table (5.7%)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The measured normalized cross sections in bins of Z pt, using dressed level leptons. The cross sections are divided by the bin width and then the distributions are normalized to 1.

The measured normalized cross sections in bins of $\phi^{\scriptscriptstyle *}_\eta$, using dressed level leptons. The cross sections are divided by the bin width and then the distributions are normalized to 1.

The measured normalized cross sections in bins of |y(Z)|, using dressed level leptons. The cross sections are divided by the bin width and then the distributions are normalized to 1.

The measured normalized cross sections in bins of Z pt in |y(Z)| bins, using dressed level leptons. The cross sections are divided by the bin width and then the distributions are normalized to 1.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The measured normalized cross sections in bins of $\phi^{\scriptscriptstyle *}_\eta$, using born level leptons. The cross sections are divided by the bin width and then the distributions are normalized to 1.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Feynman diagrams of the effective neutralino pair production in the GMSB simplified model in which the two neutralinos decay into two gravitinos ($\tilde{G}$) and two $Z$ bosons (left), a $Z$ and a Higgs boson ($H$) (center), or two Higgs bosons (right).

Feynman diagrams of the effective neutralino pair production in the GMSB simplified model in which the two neutralinos decay into two gravitinos ($\tilde{G}$) and two $Z$ bosons (left), a $Z$ and a Higgs boson ($H$) (center), or two Higgs bosons (right).

Feynman diagrams of the effective neutralino pair production in the GMSB simplified model in which the two neutralinos decay into two gravitinos ($\tilde{G}$) and two $Z$ bosons (left), a $Z$ and a Higgs boson ($H$) (center), or two Higgs bosons (right).

Feynman diagrams of the effective neutralino pair production in the GMSB simplified model in which the two neutralinos decay into two gravitinos ($\tilde{G}$) and two $Z$ bosons (left), a $Z$ and a Higgs boson ($H$) (center), or two Higgs bosons (right).

Feynman diagrams of the effective neutralino pair production in the GMSB simplified model in which the two neutralinos decay into two gravitinos ($\tilde{G}$) and two $Z$ bosons (left), a $Z$ and a Higgs boson ($H$) (center), or two Higgs bosons (right).

The distributions of the most impactful input variables to the TD jet tagger for signal (red, lighter) and collision background (blue, darker). They include the charged (upper left) and neutral (upper right) hadron energy fractions, the number of track constituents in the jet (middle left), the $\Delta R$ between the jet axis and the closest track associated with the PV (middle right), and the jet time (lower).

The distributions of the most impactful input variables to the TD jet tagger for signal (red, lighter) and collision background (blue, darker). They include the charged (upper left) and neutral (upper right) hadron energy fractions, the number of track constituents in the jet (middle left), the $\Delta R$ between the jet axis and the closest track associated with the PV (middle right), and the jet time (lower).

The distributions of the most impactful input variables to the TD jet tagger for signal (red, lighter) and collision background (blue, darker). They include the charged (upper left) and neutral (upper right) hadron energy fractions, the number of track constituents in the jet (middle left), the $\Delta R$ between the jet axis and the closest track associated with the PV (middle right), and the jet time (lower).

The distributions of the most impactful input variables to the TD jet tagger for signal (red, lighter) and collision background (blue, darker). They include the charged (upper left) and neutral (upper right) hadron energy fractions, the number of track constituents in the jet (middle left), the $\Delta R$ between the jet axis and the closest track associated with the PV (middle right), and the jet time (lower).

The distributions of the most impactful input variables to the TD jet tagger for signal (red, lighter) and collision background (blue, darker). They include the charged (upper left) and neutral (upper right) hadron energy fractions, the number of track constituents in the jet (middle left), the $\Delta R$ between the jet axis and the closest track associated with the PV (middle right), and the jet time (lower).

The distributions of the most impactful input variables to the TD jet tagger for signal (red, lighter) and collision background (blue, darker). They include the charged (upper left) and neutral (upper right) hadron energy fractions, the number of track constituents in the jet (middle left), the $\Delta R$ between the jet axis and the closest track associated with the PV (middle right), and the jet time (lower).

The distributions of the most impactful input variables to the TD jet tagger for signal (red, lighter) and collision background (blue, darker). They include the charged (upper left) and neutral (upper right) hadron energy fractions, the number of track constituents in the jet (middle left), the $\Delta R$ between the jet axis and the closest track associated with the PV (middle right), and the jet time (lower).

The distributions of the most impactful input variables to the TD jet tagger for signal (red, lighter) and collision background (blue, darker). They include the charged (upper left) and neutral (upper right) hadron energy fractions, the number of track constituents in the jet (middle left), the $\Delta R$ between the jet axis and the closest track associated with the PV (middle right), and the jet time (lower).

The distributions of the most impactful input variables to the TD jet tagger for signal (red, lighter) and collision background (blue, darker). They include the charged (upper left) and neutral (upper right) hadron energy fractions, the number of track constituents in the jet (middle left), the $\Delta R$ between the jet axis and the closest track associated with the PV (middle right), and the jet time (lower).

The distributions of the most impactful input variables to the TD jet tagger for signal (red, lighter) and collision background (blue, darker). They include the charged (upper left) and neutral (upper right) hadron energy fractions, the number of track constituents in the jet (middle left), the $\Delta R$ between the jet axis and the closest track associated with the PV (middle right), and the jet time (lower).

TD jet tagger score distributions (left) for signal (red, lighter) and collision background (blue, darker). Identification probability for the signal versus the misidentification probability for the background (right) with the tagger working point (w.~p.) used in the analysis shown as a blue marker.

TD jet tagger score distributions (left) for signal (red, lighter) and collision background (blue, darker). Identification probability for the signal versus the misidentification probability for the background (right) with the tagger working point (w.~p.) used in the analysis shown as a blue marker. Both are evaluated using an independent sample of testing events.

TD jet tagger score distributions (left) for signal (red, lighter) and collision background (blue, darker). Identification probability for the signal versus the misidentification probability for the background (right) with the tagger working point (w.~p.) used in the analysis shown as a blue marker.

TD jet tagger score distributions (left) for signal (red, lighter) and collision background (blue, darker). Identification probability for the signal versus the misidentification probability for the background (right) with the tagger working point (w.~p.) used in the analysis shown as a blue marker. Both are evaluated using an independent sample of testing events.

The TD jet tagger score distributions for simulation (shaded histogram) and data (black markers) when using electrons from $W\to e\nu_e$ events as proxy objects for signal jets. The last bin contains jets with tagger scores greater than 0.996, the threshold used to tag signal jets. Similar levels of agreement are observed for photon proxy objects from the $Z\to\ell^+\ell^-\gamma$ sample.

The efficiency of the TD jet tagger working point used in the analysis is shown as a function of the lab frame transverse decay length for simulated signals with $\chi$ mass of 400 GeV. The uncertainties shown account for lifetime dependence and statistical uncertainty.

The TD jet tagger misidentification probability measured using the nominal $W$+jets MR is shown along with the systematic uncertainty, quantifying the degree of process dependence measured from alternative MRs. On the left, this probability is shown for the first 19.9 fb$^{-1}$ of data collected in 2016, while on the right it is shown for the last 16.4 fb$^{-1}$ of data collected in 2016combined with data collected in 2017-2018.

The TD jet tagger score distributions for simulation (shaded histogram) and data (black markers) when using electrons from $W\to e\nu_e$ events as proxy objects for signal jets. The histograms and data points have been normalized to unit area. The last bin contains jets with tagger scores greater than 0.996, the threshold used to tag signal jets. Similar levels of agreement are observed for photon proxy objects from the $Z\to\ell^+\ell^-\gamma$ sample.

The TD jet tagger misidentification probability measured using the nominal $W$+jets MR is shown along with the systematic uncertainty, quantifying the degree of process dependence measured from alternative MRs. On the left, this probability is shown for the first 19.9 fb$^{-1}$ of data collected in 2016, while on the right it is shown for the last 16.4 fb$^{-1}$ of data collected in 2016combined with data collected in 2017-2018.

The TD jet tagger misidentification probability measured using the nominal $W$+jets MR (black round markers) is shown along with the systematic uncertainty (gray band), quantifying the degree of process dependence measured from alternative MRs. The measurements in the alternative MRs are displayed as well ($Z$+jets MR as green round markers, $t\bar{t}$ MR as red squared markers, QCD MR as blue triangular markers) along with their respective statistical uncertainty. On the left, this probability is shown for the first 19.9 fb$^{-1}$ of data collected in 2016, while on the right it is shown for the last 16.4 fb$^{-1}$ of data collected in 2016combined with data collected in 2017-2018.

Distribution of the number of TD tagged jets for the $m_{\chi} = 400$ GeVsimulated signal samples with $c\tau_{\chi} = 0.5$ m (solid red line) and $c\tau_{\chi} = 3.0$ m (dotted green line), estimated background (blue square markers), and data (black round markers). The blue shaded region indicates the systematic uncertainty in the background prediction. No background prediction is shown for the bin with zero TD tagged jets as it is the main control region used to predict the background for the other two bins. There are zero observed events in the bin with two or more TD tagged jets.

The TD jet tagger misidentification probability measured using the nominal $W$+jets MR (black round markers) is shown along with the systematic uncertainty (gray band), quantifying the degree of process dependence measured from alternative MRs. The measurements in the alternative MRs are displayed as well ($Z$+jets MR as green round markers, $t\bar{t}$ MR as red squared markers, QCD MR as blue triangular markers) along with their respective statistical uncertainty. On the left, this probability is shown for the first 19.9 fb$^{-1}$ of data collected in 2016, while on the right it is shown for the last 16.4 fb$^{-1}$ of data collected in 2016combined with data collected in 2017-2018.

Expected and observed 95% CL upper limits on $\sigma_{\chi\chi}$ as functions of $m_\chi$ in a scenario with $\mathcal{B}(\chi\to HG) = 0.5$ and $c\tau = 0.5$ m (left) or 3 m (right).

Distribution of the number of TD tagged jets for the $m_{\chi} = 400$ GeVsimulated signal samples with $c\tau_{\chi} = 0.5$ m (solid red line) and $c\tau_{\chi} = 3.0$ m (dotted green line), estimated background (blue square markers), and data (black round markers). The signal distributions are normalized to the expected cross section limit. The blue shaded region indicates the systematic uncertainty in the background prediction. No background prediction is shown for the bin with zero TD tagged jets as it is the main control region used to predict the background for the other two bins. There are zero observed events in the bin with two or more TD tagged jets.

Expected and observed 95% CL upper limits on $\sigma_{\chi\chi}$ as functions of $m_\chi$ in a scenario with $\mathcal{B}(\chi\to HG) = 0.5$ and $c\tau = 0.5$ m (left) or 3 m (right).

Expected and observed 95% CL upper limits on $\sigma_{\chi\chi}$ as functions of $m_\chi$ in a scenario with $\mathcal{B}(\chi\to HG) = 0.5$ and $c\tau = 0.5$ m (left) or 3 m (right).

Expected and observed 95% CL upper limits on $\sigma_{\chi\chi}$ as functions of $c\tau_{\chi}$ in a scenario with $\mathcal{B}(\chi\to H\tilde{G}) = 0.5$ and $m_{\chi} = 400$ GeV (left) or 1000 GeV (right).

Expected and observed 95% CL upper limits on $\sigma_{\chi\chi}$ as functions of $m_\chi$ in a scenario with $\mathcal{B}(\chi\to HG) = 0.5$ and $c\tau = 0.5$ m (left) or 3 m (right).

Expected and observed 95% CL upper limits on $\sigma_{\chi\chi}$ as functions of $c\tau_{\chi}$ in a scenario with $\mathcal{B}(\chi\to H\tilde{G}) = 0.5$ and $m_{\chi} = 400$ GeV (left) or 1000 GeV (right).

Expected and observed 95% CL upper limits on $\sigma_{\chi\chi}$ as functions of $c\tau_{\chi}$ in a scenario with $\mathcal{B}(\chi\to H\tilde{G}) = 0.5$ and $m_{\chi} = 400$ GeV (left) or 1000 GeV (right).

The observed 95% CL upper limit on $\sigma_{\chi\chi}$ as a function of $m_{\chi}$ and $c\tau_{\chi}$ in a scenario with $\mathcal{B}(\chi\to H\tilde{G}) = 0.5$. The area enclosed by the dotted black line corresponds to the observed excluded region.

Expected and observed 95% CL upper limits on $\sigma_{\chi\chi}$ as functions of $c\tau_{\chi}$ in a scenario with $\mathcal{B}(\chi\to H\tilde{G}) = 0.5$ and $m_{\chi} = 400$ GeV (left) or 1000 GeV (right).

The observed 95% CL upper limit on $\sigma_{\chi\chi}$ as a function of $m_{\chi}$ and $c\tau_{\chi}$ in a scenario with $\mathcal{B}(\chi\to H\tilde{G}) = 0.5$. The area enclosed by the dotted black line corresponds to the observed excluded region.

The distribution of the jet charged hadron energy fraction, a variable used as input to the TD jet tagger score, for simulation (shaded histogram) and data (black markers) when using electrons from $W\to e\nu_e$ events as proxy objects for signal jets. The histograms and data points have been normalized to unit area. Similar levels of agreement are observed for photon proxy objects from the $Z\to\ell^+\ell^-\gamma$ sample.

The distribution of the jet neutral hadron energy fraction, a variable used as input to the TD jet tagger score, for simulation (shaded histogram) and data (black markers) when using electrons from $W\to e\nu_e$ events as proxy objects for signal jets. The histograms and data points have been normalized to unit area. Similar levels of agreement are observed for photon proxy objects from the $Z\to\ell^+\ell^-\gamma$ sample.

The distribution of the number of track constituents in the jet, a variable used as input to the TD jet tagger score, for simulation (shaded histogram) and data (black markers) when using electrons from $W\to e\nu_e$ events as proxy objects for signal jets. The histograms and data points have been normalized to unit area. Similar levels of agreement are observed for photon proxy objects from the $Z\to\ell^+\ell^-\gamma$ sample.

The $\eta$ distribution of TD-tagged jets in a background-enriched control region that comprises events with exactly one TD-tagged jet. Observed data (black round markers) and the corresponding prediction based on control samples in data (empty squared markers), measured using the nominal $W$+jets MR, are compared. The prediction uncertainty (gray band) includes the systematic uncertainty quantifying the degree of process dependence measured from alternative MRs. The predictions for the shape and the normalization of the $\eta$ distribution are consistent with the data.

Jet time distribution in a sample of b-tagged jets from dilepton $t \bar{t}$ events in 2017 data-taking period (black round markers) and simulation (filled histogram). A Gaussian smearing procedure is applied to the jet time in the $t \bar{t}$ sample (green line) to correct for effects that are difficult to simulate (timing drift caused by crystals transparency loss due to detector aging, electronics jitter).

The observed 95% CL upper limit on $\sigma_{\chi\chi}$ as a function of $m_{\chi}$ and $c\tau_{\chi}$ in a scenario with $\mathcal{B}(\chi\to H\tilde{G}) = 1$. The area enclosed by the dotted black line corresponds to the observed excluded region.

The observed 95% CL upper limit on $\sigma_{\chi\chi}$ as a function of $m_{\chi}$ and $c\tau_{\chi}$ in a scenario with $\mathcal{B}(\chi\to H\tilde{G}) = 0.75$, $\mathcal{B}(\chi\to Z\tilde{G}) = 0.25$. The area enclosed by the dotted black line corresponds to the observed excluded region.

The observed 95% CL upper limit on $\sigma_{\chi\chi}$ as a function of $m_{\chi}$ and $c\tau_{\chi}$ in a scenario with $\mathcal{B}(\chi\to H\tilde{G}) = 0.25$, $\mathcal{B}(\chi\to Z\tilde{G}) = 0.75$. The area enclosed by the dotted black line corresponds to the observed excluded region.

The observed 95% CL upper limit on $\sigma_{\chi\chi}$ as a function of $m_{\chi}$ and $c\tau_{\chi}$ in a scenario with $\mathcal{B}(\chi\to Z\tilde{G}) = 1$. The area enclosed by the dotted black line corresponds to the observed excluded region.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 127 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the merged topology, namely, the H (or Z) decay products are produced with an angular separation $\Delta R < 0.8$, and the H (or Z) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 3\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 127 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with exactly one quark in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and only one b-quark (or light quark) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 5\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 127 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with two quarks in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and both b-quarks (or light quarks) have $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 7\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 150 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the merged topology, namely, the H (or Z) decay products are produced with an angular separation $\Delta R < 0.8$, and the H (or Z) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 3\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 150 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with exactly one quark in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and only one b-quark (or light quark) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 5\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 150 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with two quarks in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and both b-quarks (or light quarks) have $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 7\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 175 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the merged topology, namely, the H (or Z) decay products are produced with an angular separation $\Delta R < 0.8$, and the H (or Z) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 3\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 175 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with exactly one quark in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and only one b-quark (or light quark) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 5\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 175 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with two quarks in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and both b-quarks (or light quarks) have $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 7\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 200 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the merged topology, namely, the H (or Z) decay products are produced with an angular separation $\Delta R < 0.8$, and the H (or Z) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 3\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 200 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with exactly one quark in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and only one b-quark (or light quark) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 5\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 200 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with two quarks in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and both b-quarks (or light quarks) have $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 7\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 250 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the merged topology, namely, the H (or Z) decay products are produced with an angular separation $\Delta R < 0.8$, and the H (or Z) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 3\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 250 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with exactly one quark in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and only one b-quark (or light quark) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 5\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 250 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with two quarks in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and both b-quarks (or light quarks) have $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 7\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 300 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the merged topology, namely, the H (or Z) decay products are produced with an angular separation $\Delta R < 0.8$, and the H (or Z) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 3\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 300 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with exactly one quark in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and only one b-quark (or light quark) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 5\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 300 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with two quarks in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and both b-quarks (or light quarks) have $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 7\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 400 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the merged topology, namely, the H (or Z) decay products are produced with an angular separation $\Delta R < 0.8$, and the H (or Z) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 3\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 400 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with exactly one quark in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and only one b-quark (or light quark) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 5\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 400 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with two quarks in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and both b-quarks (or light quarks) have $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 7\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 600 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the merged topology, namely, the H (or Z) decay products are produced with an angular separation $\Delta R < 0.8$, and the H (or Z) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 3\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 600 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with exactly one quark in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and only one b-quark (or light quark) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 5\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 600 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with two quarks in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and both b-quarks (or light quarks) have $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 7\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 800 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the merged topology, namely, the H (or Z) decay products are produced with an angular separation $\Delta R < 0.8$, and the H (or Z) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 3\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 800 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with exactly one quark in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and only one b-quark (or light quark) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 5\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 800 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with two quarks in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and both b-quarks (or light quarks) have $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 7\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 1000 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the merged topology, namely, the H (or Z) decay products are produced with an angular separation $\Delta R < 0.8$, and the H (or Z) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 3\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 1000 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with exactly one quark in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and only one b-quark (or light quark) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 5\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 1000 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with two quarks in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and both b-quarks (or light quarks) have $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 7\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 1250 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the merged topology, namely, the H (or Z) decay products are produced with an angular separation $\Delta R < 0.8$, and the H (or Z) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 3\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 1250 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with exactly one quark in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and only one b-quark (or light quark) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 5\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 1250 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with two quarks in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and both b-quarks (or light quarks) have $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 7\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 1500 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the merged topology, namely, the H (or Z) decay products are produced with an angular separation $\Delta R < 0.8$, and the H (or Z) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 3\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 1500 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with exactly one quark in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and only one b-quark (or light quark) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 5\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 1500 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with two quarks in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and both b-quarks (or light quarks) have $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 7\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 1800 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the merged topology, namely, the H (or Z) decay products are produced with an angular separation $\Delta R < 0.8$, and the H (or Z) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 3\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 1800 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with exactly one quark in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and only one b-quark (or light quark) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 5\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 1800 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with two quarks in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and both b-quarks (or light quarks) have $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 7\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

Cutflow table for a $\tilde{\chi}_{1}^{0}$ signal sample with a mass of 127 GeV.

Cutflow table for a $\tilde{\chi}_{1}^{0}$ signal sample with a mass of 127 GeV.

Cutflow table for a $\tilde{\chi}_{1}^{0}$ signal sample with a mass of 150 GeV.

Cutflow table for a $\tilde{\chi}_{1}^{0}$ signal sample with a mass of 150 GeV.

Cutflow table for a $\tilde{\chi}_{1}^{0}$ signal sample with a mass of 175 GeV.

Cutflow table for a $\tilde{\chi}_{1}^{0}$ signal sample with a mass of 175 GeV.

Cutflow table for a $\tilde{\chi}_{1}^{0}$ signal sample with a mass of 200 GeV.

Cutflow table for a $\tilde{\chi}_{1}^{0}$ signal sample with a mass of 200 GeV.

Cutflow table for a $\tilde{\chi}_{1}^{0}$ signal sample with a mass of 250 GeV.

Cutflow table for a $\tilde{\chi}_{1}^{0}$ signal sample with a mass of 250 GeV.

Cutflow table for a $\tilde{\chi}_{1}^{0}$ signal sample with a mass of 300 GeV.

Cutflow table for a $\tilde{\chi}_{1}^{0}$ signal sample with a mass of 300 GeV.

Cutflow table for a $\tilde{\chi}_{1}^{0}$ signal sample with a mass of 400 GeV.

Differential cross sections for the EW W$\gamma$jj production. Given that the ranges of some variables extend to infinity, the last bins accommodate all the events up to infinity as marked by the bin label.

Differential cross sections for the EW W$\gamma$jj production. Given that the ranges of some variables extend to infinity, the last bins accommodate all the events up to infinity as marked by the bin label.

Differential cross sections for the EW W$\gamma$jj production. Given that the ranges of some variables extend to infinity, the last bins accommodate all the events up to infinity as marked by the bin label.

Differential cross sections for the EW W$\gamma$jj production. Given that the ranges of some variables extend to infinity, the last bins accommodate all the events up to infinity as marked by the bin label.

Differential cross sections for the EW W$\gamma$jj production. Given that the ranges of some variables extend to infinity, the last bins accommodate all the events up to infinity as marked by the bin label.

Differential cross sections for the EW + QCD W$\gamma$jj production. Given that the ranges of some variables extend to infinity, the last bins accommodate all the events up to infinity as marked by the bin label.

Differential cross sections for the EW +QCD W$\gamma$jj production. Given that the ranges of some variables extend to infinity, the last bins accommodate all the events up to infinity as marked by the bin label.

Differential cross sections for the EW + QCD W$\gamma$jj production. Given that the ranges of some variables extend to infinity, the last bins accommodate all the events up to infinity as marked by the bin label.

Differential cross sections for the EW + QCD W$\gamma$jj production. Given that the ranges of some variables extend to infinity, the last bins accommodate all the events up to infinity as marked by the bin label.

Differential cross sections for the EW + QCD W$\gamma$jj production. Given that the ranges of some variables extend to infinity, the last bins accommodate all the events up to infinity as marked by the bin label.

Differential cross sections for the EW + QCD W$\gamma$jj production. Given that the ranges of some variables extend to infinity, the last bins accommodate all the events up to infinity as marked by the bin label.

The $m_{W\gamma}$ distribution for muon events (electron events are also used and the muon events are shown here as an example.) satisfying the aQGC region selection and used to set constraints on the anomalous gauge coupling parameters (left). The gray line represents a nonzero $f_{M,2}/Λ^4$ setting. Events with $m_{W\gamma} > 1500 GeV$ are included in the last bin.

Exclusion limits at the 95% CL for each aQGC coefficient, derived from the mW$\gamma$ distribution, assuming all other coefficients are set to zero. Unitarity bounds corresponding to each operator are also listed. All coupling parameter limits are in TeV^{−4}, while Ubound values are in TeV.

Results summary.

Distribution of the subleading lepton transverse momemtum, prefit.

Distribution of the leading jet transverse momemtum, prefit.

Distribution of the leading jet transverse momemtum, prefit.

Distribution of the number of jets, prefit.

Distribution of the number of jets, prefit.

Distribution of the number of loose b-tagged jets, prefit.

Distribution of the number of loose b-tagged jets, prefit.

Distribution of the missing transverse momemtum, prefit.

Distribution of the missing transverse momemtum, prefit.

Distribution of the number of b-tagged jets, prefit.

Distribution of the number of b-tagged jets, prefit.

Distribution of the number of jets, prefit, validation region.

Distribution of the number of jets, prefit, validation region.

Distribution of the number of loose b-tagged jets, prefit, validation region.

Distribution of the number of loose b-tagged jets, prefit, validation region.

Distribution of the leading jet transverse momemtum, prefit, validation region.

Distribution of the leading jet transverse momemtum, prefit, validation region.

Distribution of the leading lepton transverse momemtum, prefit, validation region.

Distribution of the leading lepton transverse momemtum, prefit, validation region.

Distribution of the number of jets based on the number of b-tagged jets, prefit, control region enriched in WZ and ttZ.

Distribution of the number of jets based on the number of b-tagged jets, prefit, control region enriched in WZ and ttZ.

Distribution of the number of jets and b-tagged jets, prefit, control region enriched in ZZ and ttZ.

Distribution of the number of jets and b-tagged jets, prefit, control region enriched in ZZ and ttZ.

Number of predicted and observed events in the signal regions of the dilepton and trilepton channels. The last column shows the ratio between the number of predicted events obtained after and before the fit is performed. The total uncertainty in the number of predicted events is shown. The symbol “—” indicates that the corresponding background does not apply.

Number of predicted and observed events in the signal regions of the dilepton and trilepton channels. The last column shows the ratio between the number of predicted events obtained after and before the fit is performed. The total uncertainty in the number of predicted events is shown. The symbol “—” indicates that the corresponding background does not apply.

Distribution of NN discriminant with two leptons positive charges, prefit.

Distribution of NN discriminant with two leptons positive charges, prefit.

Distribution of NN discriminant with two leptons negative charges, prefit.

Distribution of NN discriminant with two leptons negative charges, prefit.

Distribution of NN discriminant with two leptons positive charges, postfit.

Distribution of NN discriminant with two leptons positive charges, postfit.

Distribution of NN discriminant with two leptons negative charges, postfit.

Distribution of NN discriminant with two leptons negative charges, postfit.

Distribution of three-lepton invariant mass with 2 b-tagged jets, positive sum of lepton charges, prefit.

Distribution of three-lepton invariant mass with 2 b-tagged jets, positive sum of lepton charges, prefit.

Distribution of three-lepton invariant mass with 3 jets of which exactly 2 are b-tagged jets, positive sum of lepton charges, prefit.

Distribution of three-lepton invariant mass with 3 jets of which exactly 2 are b-tagged jets, positive sum of lepton charges, prefit.

Distribution of three-lepton invariant mass with 2 b-tagged jets, positive sum of lepton charges, postfit.

Distribution of three-lepton invariant mass with 2 b-tagged jets, positive sum of lepton charges, postfit.

Distribution of three-lepton invariant mass with 3 jets of which exactly 2 are b-tagged jets, positive sum of lepton charges, postfit.

Distribution of three-lepton invariant mass with 3 jets of which exactly 2 are b-tagged jets, positive sum of lepton charges, postfit.

Distribution of three-lepton invariant mass with 2 b-tagged jets, negative sum of lepton charges, prefit.

Distribution of three-lepton invariant mass with 2 b-tagged jets, negative sum of lepton charges, prefit.

Distribution of three-lepton invariant mass with 3 jets of which exactly 2 are b-tagged jets, negative sum of lepton charges, prefit.

Distribution of three-lepton invariant mass with 3 jets of which exactly 2 are b-tagged jets, negative sum of lepton charges, prefit.

Distribution of three-lepton invariant mass with 2 b-tagged jets, negative sum of lepton charges, postfit.

Distribution of three-lepton invariant mass with 2 b-tagged jets, negative sum of lepton charges, postfit.

Distribution of three-lepton invariant mass with 3 jets of which exactly 2 are b-tagged jets, negative sum of lepton charges, postfit.

Distribution of three-lepton invariant mass with 3 jets of which exactly 2 are b-tagged jets, negative sum of lepton charges, postfit.

Measured cross sections

Measured cross sections

The 68 and 95% CL intervals in the likelihood fit with the ttW+ and ttW− cross sections measured independently.

The 68 and 95% CL intervals in the likelihood fit with the ttW+ and ttW− cross sections measured independently.

Negative log-likelihood value difference with respect to the best fit value for the scan of the ratio between the ttW+ and ttW- cross section.

Negative log-likelihood value difference with respect to the best fit value for the scan of the ratio between the ttW+ and ttW- cross section.

Distribution of the leading lepton transverse momemtum, postfit.

Distribution of the subleading lepton transverse momemtum, postfit.

Distribution of the leading jet transverse momemtum, postfit.

Distribution of the number of jets, postfit.

Distribution of the number of loose b-tagged jets, postfit.

Distribution of the missing transverse momemtum, postfit.

Distribution of the number of b-tagged jets, postfit.

The distribution of the BDT discriminants for the 2016--2018 data set for three different categories in the combined single-electron and single-muon channels. The three categories are defined by the number of resolved t tags ($N_\textrm{RT}$), b tags ($N_\textrm{b}$), and jets ($N_\textrm{j}$), selected as representative based on their sensitivity to signal. Here, $\textrm{t}\bar{\textrm{t}} + \geq 1 \textrm{b}$ refers to $\textrm{t}\bar{\textrm{t}}$ events with at least one additional b jet, while $\textrm{t}\bar{\textrm{t}} + 0 \textrm{b}$ includes all other $\textrm{t}\bar{\textrm{t}}$ events not produced in association with a boson. The TOP grouping contains single top quark production along with the other $\textrm{t}\bar{\textrm{t}}$ processes not explicitly shown, and EW refers to events that contain W and Z bosons but no top quarks.

Measured signal strength ($\mu = \sigma_{\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}}/ \sigma_{\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}} ^{\textrm{SM}}$), corresponding cross section (in fb), and the expected and observed significance (in standard deviations) for $\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}$ production from all analysis channels. Uncertainties shown in this table are statistical and systematic uncertainties respectively. In this table, SSDL\&ML and OSDL (2016) represent results from EPJC 80 (2020) 75 and JHEP 11 (2019) 082 respectively.

The distribution of the BDT discriminants for the 2016--2018 data set for three different categories in the combined single-electron and single-muon channels. The three categories are defined by the number of resolved t tags ($N_\textrm{RT}$), b tags ($N_\textrm{b}$), and jets ($N_\textrm{j}$), selected as representative based on their sensitivity to signal. Here, $\textrm{t}\bar{\textrm{t}} + \geq 1 \textrm{b}$ refers to $\textrm{t}\bar{\textrm{t}}$ events with at least one additional b jet, while $\textrm{t}\bar{\textrm{t}} + 0 \textrm{b}$ includes all other $\textrm{t}\bar{\textrm{t}}$ events not produced in association with a boson. The TOP grouping contains single top quark production along with the other $\textrm{t}\bar{\textrm{t}}$ processes not explicitly shown, and EW refers to events that contain W and Z bosons but no top quarks. The backgrounds and $\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}$ signal (derived from the fit) are shown as a stacked histogram. The hatched bands correspond to the estimated total uncertainty after the fit. While the bins are shown to be equal width, they do not correspond to equal width in BDT value.

The distribution of the BDT discriminants for the full 2016--2018 data set in the all-hadronic channel. The SR category shown in this figure is defined by $N_\textrm{RT}=1$, $N_\textrm{BT} \geq 1$, HT > 1400 GeV. The background from QCD multijet and \ttbar production is derived from control regions in the data. Estimates for the \tttt signal and other backgrounds are shown using simulated samples.

The distribution of the BDT discriminants for the full 2016--2018 data set in the all-hadronic channel. The sample VR category shown is defined by $N_\textrm{RT}=1$, $N_\textrm{BT} \geq 1$, $H_T > 1400$ GeV. The background from QCD multijet and $\textrm{t}\bar{\textrm{t}}$ production is derived from control regions in the data. Estimates for the $\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}$ signal and other backgrounds are shown using simulated samples. The hatched bands correspond to the estimated total uncertainty.

The distribution of the BDT discriminants for the full 2016--2018 data set in the all-hadronic channel. The SR category shown in this figure is defined by $N_\textrm{BT} \geq 2$, HT > 1100 GeV. The background from QCD multijet and \ttbar production is derived from control regions in the data. Estimates for the \tttt signal and other backgrounds are shown using simulated samples.

The distribution of the BDT discriminants for the full 2016--2018 data set in the all-hadronic channel. The sample VR category shown is defined by $N_\textrm{RT} \geq 2$, $H_T > 1100$ GeV. The background from QCD multijet and $\textrm{t}\bar{\textrm{t}}$ production is derived from control regions in the data. Estimates for the $\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}$ signal and other backgrounds are shown using simulated samples. The hatched bands correspond to the estimated total uncertainty.

Expected and observed significance (in standard deviations) for $\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}$ production from each final state and the combination with previous CMS results (EPJC 80 (2020) 75 and JHEP 11 (2019) 082). The same-sign dilepton and multilepton (SSDL\&ML) final state results are from EPJC 80 (2020) 75.

The distribution of the BDT discriminants for the full 2016--2018 data set in the all-hadronic channel. The SR category shown in this figure is defined by $N_\textrm{RT}=1$, $N_\textrm{BT} \geq 1$, $H_T > 1400$ GeV. The background from QCD multijet and $\textrm{t}\bar{\textrm{t}}$ production is derived from control regions in the data. Estimates for the $\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}$ signal and other backgrounds are shown using simulated samples. The hatched bands correspond to the estimated total uncertainty after the fit.

Measured signal strength ($\mu = \sigma_{\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}}/ \sigma_{\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}} ^{\textrm{SM}}$), corresponding cross section (in fb), and the expected and observed significance (in standard deviations) for $\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}$ production from all analysis channels. Uncertainties shown in this table are statistical and systematic uncertainties respectively. In this table, SSDL\&ML and OSDL (2016) represent results from EPJC 80 (2020) 75 and JHEP 11 (2019) 082 respectively.

The distribution of the BDT discriminants for the full 2016--2018 data set in the all-hadronic channel. The SR category shown in this figure is defined by $N_\textrm{RT} = 2$, $H_T > 1100$ GeV. The background from QCD multijet and $\textrm{t}\bar{\textrm{t}}$ production is derived from control regions in the data. Estimates for the $\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}$ signal and other backgrounds are shown using simulated samples. The hatched bands correspond to the estimated total uncertainty after the fit.

Expected and observed significance (in standard deviations) for $\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}$ production from each final state and the combination with previous CMS results (EPJC 80 (2020) 75 and JHEP 11 (2019) 082). The same-sign dilepton and multilepton (SSDL\&ML) final state results are from EPJC 80 (2020) 75.

Measured signal strength ($\mu = \sigma_{\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}}/ \sigma_{\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}} ^{\textrm{SM}}$), corresponding cross section (in fb), and the expected and observed significance (in standard deviations) for $\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}$ production from all analysis channels. This table shows production from each analysis channel in this Letter, the combination of those channels, the results from previously published results, and the full combination of all CMS 2016-2018 results.

M_ttH which is one of the input variables to the XGBoost used for CP discrimination in 3l + 0tau channel, defined in table 4.

\Delta \eta_{B-B}, which is one of the input variables to the XGBoost used for CP discrimination in 3l + 0tau channel, defined in table 4.

\Delta R_{l1-l2}, which is one of the input variables to the XGBoost used for CP discrimination in 3l + 0tau channel, defined in table 4.

Postfit discriminating distributions used as input to the fit. Events in the tH{} node are caregorized in bins of CP discriminant in the 2lss + 0 au category

Postfit discriminating distributions used as input to the fit. Events in the tH{} node are caregorized in bins of CP discriminant in the 3l +0 au category

Postfit discriminating distributions used as input to the fit. Events in the tH{} node are caregorized in bins of CP discriminant in the 2lss + 1 au category

Expected likelihood scan as a function of kappa_t and #tilde{kappa_t}

Observed likelihood scan as a function of kappa_t and #tilde{kappa_t}

Likelihood scan as a function of |f_{CP}^{Htt}| for multilepton final states

Expected likelihood scan as a function of |f_{CP}^{Htt}| for multilepton, #gamma#gamma+ZZ final states and the combniation.

Observed likelihood scan as a function of |f_{CP}^{Htt}| for multilepton final states and the combniation.

Likelihood scan as a function of kappa_t and #tilde{kappa_t} for multilepton final states and the combination with #gamma#gamma and ZZ final states.