Correlations (stat.+syst.) between the $d\Gamma_i/d w$ bins for the individual $B \rightarrow D \ell \nu$ modes (40x40). Element indices 0-39 are organized as: - Indices 0-9: $B^+ \to D^0 e^+ \nu_e$ in $w$ bins 0-9 - Indices 10-19: $B^+ \to D^0 \mu^+ \nu_\mu$ in $w$ bins 0-9 - Indices 20-29: $B^0 \to D^- e^+ \nu_e$ in $w$ bins 0-9 - Indices 30-39: $B^0 \to D^- \mu^+ \nu_\mu$ in $w$ bins 0-9 where $w$ bins 0-9 correspond to: 0: [1.00, 1.06], 1: [1.06, 1.12], 2: [1.12, 1.18], 3: [1.18, 1.24], 4: [1.24, 1.30], 5: [1.30, 1.36], 6: [1.36, 1.42], 7: [1.42, 1.48], 8: [1.48, 1.54], 9: [1.54, 1.59]

Distributions of the VLQ-candidate mass, m_VLQ, in the (a–c) SRs, (d–f) W+jets CRs and (g–i) tt̄ CRs after the fit to the background-only hypothesis. The columns correspond from left to right to the low-, middle-, and high-p_T^W bins in each region. Other includes remaining backgrounds from top quarks or that contain two W/Z bosons. The last bin includes overflow. Note: the 'Data' values in the table are normalized by the width of the bin to correspond to the number of events per 100 GeV

Distributions of the VLQ-candidate mass, m_VLQ, in the (a–c) SRs, (d–f) W+jets CRs and (g–i) tt̄ CRs after the fit to the background-only hypothesis. The columns correspond from left to right to the low-, middle-, and high-p_T^W bins in each region. Other includes remaining backgrounds from top quarks or that contain two W/Z bosons. The last bin includes overflow. Note: the 'Data' values in the table are normalized by the width of the bin to correspond to the number of events per 100 GeV

Distributions of the VLQ-candidate mass, m_VLQ, in the (a–c) SRs, (d–f) W+jets CRs and (g–i) tt̄ CRs after the fit to the background-only hypothesis. The columns correspond from left to right to the low-, middle-, and high-p_T^W bins in each region. Other includes remaining backgrounds from top quarks or that contain two W/Z bosons. The last bin includes overflow. Note: the 'Data' values in the table are normalized by the width of the bin to correspond to the number of events per 100 GeV

Distributions of the VLQ-candidate mass, m_VLQ, in the (a–c) SRs, (d–f) W+jets CRs and (g–i) tt̄ CRs after the fit to the background-only hypothesis. The columns correspond from left to right to the low-, middle-, and high-p_T^W bins in each region. Other includes remaining backgrounds from top quarks or that contain two W/Z bosons. The last bin includes overflow. Note: the 'Data' values in the table are normalized by the width of the bin to correspond to the number of events per 100 GeV

Distributions of the VLQ-candidate mass, m_VLQ, in the (a–c) SRs, (d–f) W+jets CRs and (g–i) tt̄ CRs after the fit to the background-only hypothesis. The columns correspond from left to right to the low-, middle-, and high-p_T^W bins in each region. Other includes remaining backgrounds from top quarks or that contain two W/Z bosons. The last bin includes overflow. Note: the 'Data' values in the table are normalized by the width of the bin to correspond to the number of events per 100 GeV

Distributions of the VLQ-candidate mass, m_VLQ, in the (a–c) SRs, (d–f) W+jets CRs and (g–i) tt̄ CRs after the fit to the background-only hypothesis. The columns correspond from left to right to the low-, middle-, and high-p_T^W bins in each region. Other includes remaining backgrounds from top quarks or that contain two W/Z bosons. The last bin includes overflow. Note: the 'Data' values in the table are normalized by the width of the bin to correspond to the number of events per 100 GeV

Distributions of the VLQ-candidate mass, m_VLQ, in the W+jets VRs (a-f) and tt̄ VRs (g-i) after the fit to the background-only hypothesis. The columns correspond from left to right to the low-, middle-, and high-p_T^W bins in each region. Other includes remaining backgrounds from top quarks or containing combinations having two W/Z bosons. Last bin includes overflow. Note: the 'Data' values in the table are normalized by the width of the bin to correspond to the number of events per 100 GeV

Distributions of the VLQ-candidate mass, m_VLQ, in the W+jets VRs (a-f) and tt̄ VRs (g-i) after the fit to the background-only hypothesis. The columns correspond from left to right to the low-, middle-, and high-p_T^W bins in each region. Other includes remaining backgrounds from top quarks or containing combinations having two W/Z bosons. Last bin includes overflow. Note: the 'Data' values in the table are normalized by the width of the bin to correspond to the number of events per 100 GeV

Distributions of the VLQ-candidate mass, m_VLQ, in the W+jets VRs (a-f) and tt̄ VRs (g-i) after the fit to the background-only hypothesis. The columns correspond from left to right to the low-, middle-, and high-p_T^W bins in each region. Other includes remaining backgrounds from top quarks or containing combinations having two W/Z bosons. Last bin includes overflow. Note: the 'Data' values in the table are normalized by the width of the bin to correspond to the number of events per 100 GeV

Distributions of the VLQ-candidate mass, m_VLQ, in the W+jets VRs (a-f) and tt̄ VRs (g-i) after the fit to the background-only hypothesis. The columns correspond from left to right to the low-, middle-, and high-p_T^W bins in each region. Other includes remaining backgrounds from top quarks or containing combinations having two W/Z bosons. Last bin includes overflow. Note: the 'Data' values in the table are normalized by the width of the bin to correspond to the number of events per 100 GeV

Distributions of the VLQ-candidate mass, m_VLQ, in the W+jets VRs (a-f) and tt̄ VRs (g-i) after the fit to the background-only hypothesis. The columns correspond from left to right to the low-, middle-, and high-p_T^W bins in each region. Other includes remaining backgrounds from top quarks or containing combinations having two W/Z bosons. Last bin includes overflow. Note: the 'Data' values in the table are normalized by the width of the bin to correspond to the number of events per 100 GeV

Distributions of the VLQ-candidate mass, m_VLQ, in the W+jets VRs (a-f) and tt̄ VRs (g-i) after the fit to the background-only hypothesis. The columns correspond from left to right to the low-, middle-, and high-p_T^W bins in each region. Other includes remaining backgrounds from top quarks or containing combinations having two W/Z bosons. Last bin includes overflow. Note: the 'Data' values in the table are normalized by the width of the bin to correspond to the number of events per 100 GeV

Expected (background-only) and observed 95% CL upper limits on the VLQ coupling κ as functions of the VLQ mass m_Q, for T-singlet (a) and Y-triplet (b) vector-like quarks. The green and yellow bands indicate the systematic uncertainties which are profiled in the fit for the observed upper limits. For the T-singlet model, the result of the latest ATLAS combination of searches for single vector-like top-quarks  is overlaid; this includes the decay modes T→H t and T→Z t. These interpretations are limited to parameter combinations for which the model corrections are valid, by restricting the VLQ relative width to Γ_Q/m_Q < 0.5, as indicated by the grey dashed line.

Expected (background-only) and observed 95% CL upper limits on the VLQ coupling κ as functions of the VLQ mass m_Q, for T-singlet (a) and Y-triplet (b) vector-like quarks. The green and yellow bands indicate the systematic uncertainties which are profiled in the fit for the observed upper limits. For the T-singlet model, the result of the latest ATLAS combination of searches for single vector-like top-quarks  is overlaid; this includes the decay modes T→H t and T→Z t. These interpretations are limited to parameter combinations for which the model corrections are valid, by restricting the VLQ relative width to Γ_Q/m_Q < 0.5, as indicated by the grey dashed line.

Exclusion limit (at 95% CL) for (a) T-singlet and (b) Y-triplet, expressed in terms of an upper limit on the VLQ relative width Γ_Q/m_Q, within its validity range for the modelling used, as a function of the VLQ mass m_Q. This is an alternative presentation of the upper limit set in terms of the coupling κ in Figure 6. As can be seen by the fact the interference-included and signal-only exclusion curves overlap almost entirely, the effect of neglecting the interference is negligible for the vector-like Y-quark.

Exclusion limit (at 95% CL) for (a) T-singlet and (b) Y-triplet, expressed in terms of an upper limit on the VLQ relative width Γ_Q/m_Q, within its validity range for the modelling used, as a function of the VLQ mass m_Q. This is an alternative presentation of the upper limit set in terms of the coupling κ in Figure 6. As can be seen by the fact the interference-included and signal-only exclusion curves overlap almost entirely, the effect of neglecting the interference is negligible for the vector-like Y-quark.

Covariance matrix of the absolute differential cross-section as function of $m^{bl}_{minimax}$ at particle level in the exclusive topology, accounting for the MC statistical uncertainties.

Relative differential cross-section as a function of $m^{bl}_{minimax}$ at particle level in the exclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $m^{bl}_{minimax}$ at particle level in the exclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the relative differential cross-section as function of $m^{bl}_{minimax}$ at particle level in the exclusive topology, accounting for the MC statistical uncertainties.

Total cross-section at particle level in the exclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $\sigma_{WbWb}$ at particle level in the exclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the absolute differential cross-section as function of $\sigma_{WbWb}$ at particle level in the exclusive topology, accounting for the MC statistical uncertainties.

Absolute differential cross-section as a function of $N^{jets}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator. The last bin includes overflow events.

Covariance matrix of the absolute differential cross-section as function of $N^{jets}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the absolute differential cross-section as function of $N^{jets}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Relative differential cross-section as a function of $N^{jets}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator. The last bin includes overflow events.

Covariance matrix of the relative differential cross-section as function of $N^{jets}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the relative differential cross-section as function of $N^{jets}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Absolute differential cross-section as a function of $m^{bbll}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $m^{bbll}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the absolute differential cross-section as function of $m^{bbll}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Relative differential cross-section as a function of $m^{bbll}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $m^{bbll}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the relative differential cross-section as function of $m^{bbll}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Absolute differential cross-section as a function of $m_{T}^{bb4l}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $m_{T}^{bb4l}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the absolute differential cross-section as function of $m_{T}^{bb4l}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Relative differential cross-section as a function of $m_{T}^{bb4l}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $m_{T}^{bb4l}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the relative differential cross-section as function of $m_{T}^{bb4l}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Absolute differential cross-section as a function of $p_{T}^{b1b2}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $p_{T}^{b1b2}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the absolute differential cross-section as function of $p_{T}^{b1b2}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Relative differential cross-section as a function of $p_{T}^{b1b2}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{b1b2}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{b1b2}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Absolute differential cross-section as a function of $p_{T}^{jet1}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $p_{T}^{jet1}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the absolute differential cross-section as function of $p_{T}^{jet1}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Relative differential cross-section as a function of $p_{T}^{jet1}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{jet1}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{jet1}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Absolute differential cross-section as a function of $p_{T}^{jet2}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $p_{T}^{jet2}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the absolute differential cross-section as function of $p_{T}^{jet2}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Relative differential cross-section as a function of $p_{T}^{jet2}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{jet2}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{jet2}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Absolute differential cross-section as a function of $p_{T}^{lep1}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $p_{T}^{lep1}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the absolute differential cross-section as function of $p_{T}^{lep1}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Relative differential cross-section as a function of $p_{T}^{lep1}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{lep1}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{lep1}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Absolute differential cross-section as a function of $p_{T}^{lep2}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $p_{T}^{lep2}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the absolute differential cross-section as function of $p_{T}^{lep2}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Relative differential cross-section as a function of $p_{T}^{lep2}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{lep2}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{lep2}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Absolute differential cross-section as a function of $p_{T}^{bb4l}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $p_{T}^{bb4l}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the absolute differential cross-section as function of $p_{T}^{bb4l}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Relative differential cross-section as a function of $p_{T}^{bb4l}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{bb4l}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{bb4l}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Absolute differential cross-section as a function of $p_{T}^{bbll}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $p_{T}^{bbll}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the absolute differential cross-section as function of $p_{T}^{bbll}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Relative differential cross-section as a function of $p_{T}^{bbll}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{bbll}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{bbll}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Total cross-section at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $\sigma_{WbWb}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the absolute differential cross-section as function of $\sigma_{WbWb}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the exclusive topology and as function of $m^{bl}_{minimax}$ in the exclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $m^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $p_{T}^{jet1}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $p_{T}^{jet2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $p_{T}^{lep1}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $p_{T}^{lep2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $p_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $p_{T}^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $\sigma_{WbWb}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the exclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the exclusive topology and as function of $m^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the exclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the exclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the exclusive topology and as function of $p_{T}^{jet1}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the exclusive topology and as function of $p_{T}^{jet2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the exclusive topology and as function of $p_{T}^{lep1}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the exclusive topology and as function of $p_{T}^{lep2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the exclusive topology and as function of $p_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the exclusive topology and as function of $p_{T}^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the exclusive topology and as function of $\sigma_{WbWb}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $m^{bbll}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $m^{bbll}$ in the inclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $m^{bbll}$ in the inclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{jet1}$ in the inclusive topology and as function of $m^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{jet2}$ in the inclusive topology and as function of $p_{T}^{jet1}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{lep1}$ in the inclusive topology and as function of $p_{T}^{jet2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $p_{T}^{lep1}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $p_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $p_{T}^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the inclusive topology and as function of $p_{T}^{lep2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $m_{T}^{bb4l}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{b1b2}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{jet1}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{jet1}$ in the inclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{jet1}$ in the inclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{jet2}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{jet2}$ in the inclusive topology and as function of $m^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{jet2}$ in the inclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{jet2}$ in the inclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{lep1}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{lep1}$ in the inclusive topology and as function of $m^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{lep1}$ in the inclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{lep1}$ in the inclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{lep1}$ in the inclusive topology and as function of $p_{T}^{jet1}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $m^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $p_{T}^{jet1}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $p_{T}^{jet2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $N^{jets}$ in the inclusive topology and as function of $p_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{bbll}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{bbll}$ in the inclusive topology and as function of $m^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{bbll}$ in the inclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{bbll}$ in the inclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{jet1}$ in the inclusive topology and as function of $p_{T}^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the inclusive topology and as function of $m^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the inclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the inclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the inclusive topology and as function of $p_{T}^{jet1}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the inclusive topology and as function of $p_{T}^{jet2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the inclusive topology and as function of $p_{T}^{lep1}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the inclusive topology and as function of $p_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the inclusive topology and as function of $p_{T}^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $m^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $p_{T}^{jet1}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $p_{T}^{jet2}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $p_{T}^{lep1}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $p_{T}^{lep2}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $p_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $p_{T}^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $m^{bbll}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $m^{bbll}$ in the inclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $m^{bbll}$ in the inclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{jet1}$ in the inclusive topology and as function of $m^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{jet2}$ in the inclusive topology and as function of $p_{T}^{jet1}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{lep1}$ in the inclusive topology and as function of $p_{T}^{jet2}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $p_{T}^{lep1}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $p_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $p_{T}^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $m_{T}^{bb4l}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{b1b2}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{jet1}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{jet1}$ in the inclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{jet1}$ in the inclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{jet2}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{jet2}$ in the inclusive topology and as function of $m^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{jet2}$ in the inclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{jet2}$ in the inclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{lep1}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{lep1}$ in the inclusive topology and as function of $m^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{lep1}$ in the inclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{lep1}$ in the inclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{lep1}$ in the inclusive topology and as function of $p_{T}^{jet1}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $m^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $p_{T}^{jet1}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $p_{T}^{jet2}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $N^{jets}$ in the inclusive topology and as function of $p_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{bbll}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{bbll}$ in the inclusive topology and as function of $m^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{bbll}$ in the inclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{bbll}$ in the inclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{jet1}$ in the inclusive topology and as function of $p_{T}^{bbll}$ in the inclusive topology.

Signal efficiencies with Full Run 2 dimuon channel in 1b final state for different bbll (destructive interference) signal scenarios

Signal efficiencies with Full Run 2 dimuon channel in 2b final state for different bbll signal scenarios

Signal efficiencies with Full Run 2 dimuon channel in 2b final state for different bbll (destructive interference) signal scenarios

Signal efficiencies with Full Run 2 dielectron channel for different bbll signal scenarios

Signal efficiencies with Full Run 2 dielectron channel for different bbll (destructive interference) signal scenarios

Signal efficiencies with Full Run 2 dielectron channel in 1b final state for different bbll signal scenarios

Signal efficiencies with Full Run 2 dielectron channel in 1b final state for different bbll (destructive interference) signal scenarios

Signal efficiencies with Full Run 2 dielectron channel in 2b final state for different bbll signal scenarios

Signal efficiencies with Full Run 2 dielectron channel in 2b final state for different bbll (destructive interference) signal scenarios

Signal efficiencies with Full Run 2 dimuon channel for bsll signal

Signal efficiencies with Full Run 2 dielectron channel for bsll signal

Observed and expected background yields for different mass ranges in the dielectron channel in 0 b jet final state. The sum of all background contributions is shown as well as a breakdown into the four main categories. The quoted uncertainty includes both the statistical and the systematic components.

Observed and expected background yields for different mass ranges in the dielectron channel in 1 b jet final state. The sum of all background contributions is shown as well as a breakdown into the four main categories. The quoted uncertainty includes both the statistical and the systematic components.

Observed and expected background yields for different mass ranges in the dielectron channel in 2 b jet final state. The sum of all background contributions is shown as well as a breakdown into the four main categories. The quoted uncertainty includes both the statistical and the systematic components.

Observed and expected background yields for different mass ranges in the dimuon channel in 0 b jet final state. The sum of all background contributions is shown as well as a breakdown into the four main categories. The quoted uncertainty includes both the statistical and the systematic components.

Observed and expected background yields for different mass ranges in the dimuon channel in 1 b jet final state. The sum of all background contributions is shown as well as a breakdown into the four main categories. The quoted uncertainty includes both the statistical and the systematic components.

Observed and expected background yields for different mass ranges in the dimuon channel in 2 b jet final state. The sum of all background contributions is shown as well as a breakdown into the four main categories. The quoted uncertainty includes both the statistical and the systematic components.

Measured flavor ratio from DY+jets MC and data in 0b channel. The quoted uncertainty includes both the statistical and the systematic components. The flavor ratio from DY+jets MC deviates slightly from unity as the ratio is not corrected for mass-dependent acceptance times efficiency.

Measured flavor ratio from DY+jets MC and data in 1b+2b channel. The quoted uncertainty includes both the statistical and the systematic components. The flavor ratio from DY+jets MC deviates slightly from unity as the ratio is not corrected for mass-dependent acceptance times efficiency.

Lower limits on the energy scale ($\Lambda$) at 95% CL for bbll signal with different chirality and interference assumptions in the dielectron channel combining all b jet final states. The limits are obtained for $m_{ee}>300$ GeV.

Lower limits on the energy scale ($\Lambda$) at 95% CL for bbll signal with different chirality and interference assumptions in the dimuon channel combining all b jet final states. The limits are obtained for $m_{\mu\mu}>300$ GeV.

Lower limits on the energy scale ($\Lambda$) at 95% CL for bbll signal with different chirality and interference assumptions in the combined (dimuon+dielectron) channel combining all b jet final states. The limits are obtained for $m_{\ell\ell}>300$ GeV.

Observed and Expected upper limits on the product of the production cross section for the bsll signal in the dielectron and dimuon channels for 0 b-tagged jets.

Observed and Expected upper limits on the product of the production cross section for the bsll signal in the dielectron and dimuon channels for 1 b-tagged jets.

$\xi$ distributions for different jet $p_T$ bins.

$\xi$ distributions for different jet $p_T$ bins.

The $j_T/p_{T}^{\rm jet}$ distributions for different jet $p_T$ bins.

The $j_T/p_{T}^{\rm jet}$ distributions for different jet $p_T$ bins.

$r$ distributions for different jet $p_T$ bins.

Cutflows and signal efficiencies for the Stealth SYY SUSY model in the $1\ell$ channel corresponding to two values of $m_{\tilde{t}}$.

Cutflows and signal efficiencies for the RPV SUSY model in the $2\ell$ channel corresponding to two values of $m_{\tilde{t}}$.

Cutflows and signal efficiencies for the Stealth SYY SUSY model in the $2\ell$ channel corresponding to two values of $m_{\tilde{t}}$.

Signal efficiencies for the RPV SUSY model in the $0\ell$ channel corresponding to the four ABCD regions

Signal efficiencies for the SYY SUSY model in the $0\ell$ channel corresponding to the four ABCD regions

Signal efficiencies for the RPV SUSY model in the $1\ell$ channel corresponding to the four ABCD regions

Signal efficiencies for the SYY SUSY model in the $1\ell$ channel corresponding to the four ABCD regions

Signal efficiencies for the RPV SUSY model in the $2\ell$ channel corresponding to the four ABCD regions

Signal efficiencies for the SYY SUSY model in the $2\ell$ channel corresponding to the four ABCD regions

Expected and observed 95% CL upper limit on the top squark pair production cross section as a function of the top squark mass for the RPV SUSY model in the $0\ell$ channel

Expected and observed 95% CL upper limit on the top squark pair production cross section as a function of the top squark mass for the RPV SUSY model in the $1\ell$ channel

Expected and observed 95% CL upper limit on the top squark pair production cross section as a function of the top squark mass for the RPV SUSY model in the $2\ell$ channel

Expected and observed 95% CL upper limit on the top squark pair production cross section as a function of the top squark mass for the RPV SUSY model in the Combo channel

The $N_{jets}$ distributions from the background-only fits to data in the $0\ell$. The signal distribution overlaid corresponds to the RPV model with $m_{\tilde{t}} = 400$ GeV with the signal strength parameter $r$ set to one. The four pannels in each row show the $N_{jets}$ distributions for the A, B, C, and D regions (left to right).

The $N_{jets}$ distributions from the background-only fits to data in the $1\ell$. The signal distribution overlaid corresponds to the RPV model with $m_{\tilde{t}} = 400$ GeV with the signal strength parameter $r$ set to one. The four pannels in each row show the $N_{jets}$ distributions for the A, B, C, and D regions (left to right).

The $N_{jets}$ distributions from the background-only fits to data in the $2\ell$. The signal distribution overlaid corresponds to the RPV model with $m_{\tilde{t}} = 400$ GeV with the signal strength parameter $r$ set to one. The four pannels in each row show the $N_{jets}$ distributions for the A, B, C, and D regions (left to right).

The $N_{jets}$ distributions from the background-only fits to data in the $0\ell$. The signal distribution overlaid corresponds to the RPV model with $m_{\tilde{t}} = 800$ GeV with the signal strength parameter $r$ set to one. The four pannels in each row show the $N_{jets}$ distributions for the A, B, C, and D regions (left to right).

The $N_{jets}$ distributions from the background-only fits to data in the $1\ell$. The signal distribution overlaid corresponds to the RPV model with $m_{\tilde{t}} = 800$ GeV with the signal strength parameter $r$ set to one. The four pannels in each row show the $N_{jets}$ distributions for the A, B, C, and D regions (left to right).

The $N_{jets}$ distributions from the background-only fits to data in the $2\ell$. The signal distribution overlaid corresponds to the RPV model with $m_{\tilde{t}} = 800$ GeV with the signal strength parameter $r$ set to one. The four pannels in each row show the $N_{jets}$ distributions for the A, B, C, and D regions (left to right).

Expected and observed 95% CL upper limit on the top squark pair production cross section as a function of the top squark mass for the SYY SUSY model in the $0\ell$ channel

Expected and observed 95% CL upper limit on the top squark pair production cross section as a function of the top squark mass for the SYY SUSY model in the $1\ell$ channel

Expected and observed 95% CL upper limit on the top squark pair production cross section as a function of the top squark mass for the SYY SUSY model in the $2\ell$ channel

Expected and observed 95% CL upper limit on the top squark pair production cross section as a function of the top squark mass for the SYY SUSY model in the Combo channel

The $N_{jets}$ distributions from the background-only fits to data in the $0\ell$. The signal distribution overlaid corresponds to the Stealth SYY model with $m_{\tilde{t}} = 400$ GeV with the signal strength parameter $r$ set to one. The four pannels in each row show the $N_{jets}$ distributions for the A, B, C, and D regions (left to right).

The $N_{jets}$ distributions from the background-only fits to data in the $1\ell$. The signal distribution overlaid corresponds to the Stealth SYY model with $m_{\tilde{t}} = 400$ GeV with the signal strength parameter $r$ set to one. The four pannels in each row show the $N_{jets}$ distributions for the A, B, C, and D regions (left to right).

The $N_{jets}$ distributions from the background-only fits to data in the $2\ell$. The signal distribution overlaid corresponds to the Stealth SYY model with $m_{\tilde{t}} = 400$ GeV with the signal strength parameter $r$ set to one. The four pannels in each row show the $N_{jets}$ distributions for the A, B, C, and D regions (left to right).

The $N_{jets}$ distributions from the background-only fits to data in the $0\ell$. The signal distribution overlaid corresponds to the Stealth SYY model with $m_{\tilde{t}} = 800$ GeV with the signal strength parameter $r$ set to one. The four pannels in each row show the $N_{jets}$ distributions for the A, B, C, and D regions (left to right).

The $N_{jets}$ distributions from the background-only fits to data in the $1\ell$. The signal distribution overlaid corresponds to the Stealth SYY model with $m_{\tilde{t}} = 800$ GeV with the signal strength parameter $r$ set to one. The four pannels in each row show the $N_{jets}$ distributions for the A, B, C, and D regions (left to right).

The $N_{jets}$ distributions from the background-only fits to data in the $2\ell$. The signal distribution overlaid corresponds to the Stealth SYY model with $m_{\tilde{t}} = 800$ GeV with the signal strength parameter $r$ set to one. The four pannels in each row show the $N_{jets}$ distributions for the A, B, C, and D regions (left to right).

Distributions of discriminant for the $2_{m}^{+}$ and $0^{-}$ models.

The distributions of the $\mathrm{D}^{*}-\mathrm{D}^0$ mass difference $\Delta m$ for the normalization channel in data.

The distributions of the dimuon invariant mass $m_{\mu\mu}$ for the signal channel in data with the requirement $0.145<\Delta m<0.146$ GeV.

The distributions of the $\mathrm{D}^{*}-\mathrm{D}^0$ mass difference $\Delta m$ for the signal channel in data with the requirement $1.84<m_{\mu\mu}<1.89$ GeV.

The post-fit event yields for the signal, the combinatorial background, the $\mathrm{D}^0\to\pi^+\pi^-$ background, and the $\mathrm{D}^0\to\pi^-\mu^+\nu$ background. The observed numbers of events are given in the Data column. The subrange is in one dimension with a full range in the other dimension.

Distributions of the total transverse mass $M_{T}^{tot}$ in the SRs, comparing observed data with the SM prediction in the $\mu\tau_{h}$ final states in 2018 (center right) after the simultaneous maximum likelihood fit. Representative signal distributions are shown for the 2HDM+a (dashed red curve) and baryonic Z' (dashed black curve) models. The data points are shown with their statistical uncertainties, and the last bin includes overflow. The ``Other MC'' background contribution includes events from ggh, VBF, Wh, Zh, and electroweak vector boson production. The uncertainty band accounts for all systematic and statistical sources of uncertainty, after the fit to the data.

Distributions of the total transverse mass $M_{T}^{tot}$ in the SRs, comparing observed data with the SM prediction in the $\tau_{h}\tau_{h}$ final states in 2017 (lower left) after the simultaneous maximum likelihood fit. Representative signal distributions are shown for the 2HDM+a (dashed red curve) and baryonic Z' (dashed black curve) models. The data points are shown with their statistical uncertainties, and the last bin includes overflow. The ``Other MC'' background contribution includes events from ggh, VBF, Wh, Zh, and electroweak vector boson production. The uncertainty band accounts for all systematic and statistical sources of uncertainty, after the fit to the data.

Distributions of the total transverse mass $M_{T}^{tot}$ in the SRs, comparing observed data with the SM prediction in the $\tau_{h}\tau_{h}$ final states in 2018 (lower right) after the simultaneous maximum likelihood fit. Representative signal distributions are shown for the 2HDM+a (dashed red curve) and baryonic Z' (dashed black curve) models. The data points are shown with their statistical uncertainties, and the last bin includes overflow. The ``Other MC'' background contribution includes events from ggh, VBF, Wh, Zh, and electroweak vector boson production. The uncertainty band accounts for all systematic and statistical sources of uncertainty, after the fit to the data.

The $95\%$ CL upper limits on the $\mu$ for 2HDM+a model. Observed and expected $95\%$ CL upper limits on the $\mu$ as functions of $m_{a}$ using $m_A$ = 600 GeV, $\tan\beta$ = 1, and $m_\chi$ = 10 GeV. The interpolation between the points is linear.

The $95\%$ CL upper limits on the $\mu$ for 2HDM+a model. Observed and expected $95\%$ CL upper limits on the $\mu$ as functions of $m_{A}$ using $m_{a}$ = 150 GeV, $\sin\theta$ = 0.35, and $\tan\beta$ = 1. The interpolation between the points is linear.

The $95\%$ CL upper limits on the $\mu$ for 2HDM+a model. Observed and expected $95\%$ CL upper limits on the $\mu$ as functions of $\sin\theta$ using $m_{a}$ = 200 GeV, $m_A$ = 600 GeV, $\tan\beta$ = 1, and $m_\chi$ = 10 GeV. The interpolation between the points is linear.

The $95\%$ CL upper limits on the $\mu$ for 2HDM+a model. Observed and expected $95\%$ CL upper limits on the $\mu$ as functions of $\tan\beta$ using $m_a$ = 150 GeV, $m_A$ = 600 GeV, $\sin\theta$ = 0.35, and $m_\chi$ = 10 GeV. The interpolation between the points is linear.

The $95\%$ CL upper limits on the $\mu$ in the $m_a-m_A$ plane for 2HDM+a model. The regions inside the red and black curves correspond to the observed and expected exclusions at $95\%$ CL, respectively.

The $95\%$ CL upper limits on the $\mu$ for baryonic Z' model. Observed and expected $95\%$ CL upper limits on the $\mu$ as a function of $m_{Z'}$, using $m_{\chi}$ = 1 GeV. The interpolation between the points is linear.

The $95\%$ CL upper limits on the $\mu$ for baryonic Z' model. $95\%$ CL upper limits on the $\mu$ in $m_{Z'}-m_{\chi}$ plane. The regions inside the red and black curve correspond to the observed and expected exclusions at $95\%$ CL, respectively.