95% CL upper limits as a function of (left) cτ_{π_d} and (right) M_φ. The upper plots show the expected and observed limits on σ(pp →φ^†φ) for m_{π_d} = 20 GeV: (a) using M_φ = 1.6 TeV and (b) using cτ_{π_d} = 20 mm. The lower plots show a comparison of the observed limits for all three dark pion masses: (c) using M_φ = 1.4 TeV, and (d) using cτ_{π_d} = 1 mm. The mediator mass-dependent theoretical cross-section is given with the band corresponding to the uncertainty from NNLL-Fast.

95% CL upper limits as a function of (left) cτ_{π_d} and (right) M_φ. The upper plots show the expected and observed limits on σ(pp →φ^†φ) for m_{π_d} = 20 GeV: (a) using M_φ = 1.6 TeV and (b) using cτ_{π_d} = 20 mm. The lower plots show a comparison of the observed limits for all three dark pion masses: (c) using M_φ = 1.4 TeV, and (d) using cτ_{π_d} = 1 mm. The mediator mass-dependent theoretical cross-section is given with the band corresponding to the uncertainty from NNLL-Fast.

95% CL exclusion contours as a function of M_φ and cτ_{π_d}. The expected and observed limits on σ(pp →φ^†φ) are shown for (a) m_{π_d} = 5 GeV, (b) m_{π_d} = 10 GeV, and (c) m_{π_d} = 20 GeV. A comparison of the observed limits is given in (d) for each of the three dark pion masses.

95% CL exclusion contours as a function of M_φ and cτ_{π_d}. The expected and observed limits on σ(pp →φ^†φ) are shown for (a) m_{π_d} = 5 GeV, (b) m_{π_d} = 10 GeV, and (c) m_{π_d} = 20 GeV. A comparison of the observed limits is given in (d) for each of the three dark pion masses.

95% CL exclusion contours as a function of M_φ and cτ_{π_d}. The expected and observed limits on σ(pp →φ^†φ) are shown for (a) m_{π_d} = 5 GeV, (b) m_{π_d} = 10 GeV, and (c) m_{π_d} = 20 GeV. A comparison of the observed limits is given in (d) for each of the three dark pion masses.

95% CL exclusion contours as a function of M_φ and cτ_{π_d}. The expected and observed limits on σ(pp →φ^†φ) are shown for (a) m_{π_d} = 5 GeV, (b) m_{π_d} = 10 GeV, and (c) m_{π_d} = 20 GeV. A comparison of the observed limits is given in (d) for each of the three dark pion masses.

Comparison of the 95% CL exclusion contours between ATLAS and CMS  for (a) models with m_{π_d} = 10 GeV and (b) models with m_{π_d} = 20 GeV. The expected and observed limits are shown for ATLAS, while only the observed limits in both the model agnostic and GNN cases are included for CMS. The expected limits from the CMS result are omitted, but are, in general, very close to the CMS observed limits.

Comparison of the 95% CL exclusion contours between ATLAS and CMS  for (a) models with m_{π_d} = 10 GeV and (b) models with m_{π_d} = 20 GeV. The expected and observed limits are shown for ATLAS, while only the observed limits in both the model agnostic and GNN cases are included for CMS. The expected limits from the CMS result are omitted, but are, in general, very close to the CMS observed limits.

Normalized minPTF distribution in data, with three selected signal samples for comparison

95% CL exclusion contours as a function of M_φ and cτ_{π_d} for the Cut-Based analysis. The expected and observed limits on σ(pp →φ^†φ) are shown for (a) m_{π_d} = 5 GeV, (b) m_{π_d} = 10 GeV, and (c) m_{π_d} = 20 GeV. A comparison of the observed limits is given in (d) for each of the three dark pion masses.

95% CL exclusion contours as a function of M_φ and cτ_{π_d} for the Cut-Based analysis. The expected and observed limits on σ(pp →φ^†φ) are shown for (a) m_{π_d} = 5 GeV, (b) m_{π_d} = 10 GeV, and (c) m_{π_d} = 20 GeV. A comparison of the observed limits is given in (d) for each of the three dark pion masses.

95% CL exclusion contours as a function of M_φ and cτ_{π_d} for the Cut-Based analysis. The expected and observed limits on σ(pp →φ^†φ) are shown for (a) m_{π_d} = 5 GeV, (b) m_{π_d} = 10 GeV, and (c) m_{π_d} = 20 GeV. A comparison of the observed limits is given in (d) for each of the three dark pion masses.

95% CL exclusion contours as a function of M_φ and cτ_{π_d} for the Cut-Based analysis. The expected and observed limits on σ(pp →φ^†φ) are shown for (a) m_{π_d} = 5 GeV, (b) m_{π_d} = 10 GeV, and (c) m_{π_d} = 20 GeV. A comparison of the observed limits is given in (d) for each of the three dark pion masses.

Comparison of observed and expected 95% CL limits of the Cut-Based analysis against the corresponding BDT-based analysis. Limits on σ(pp →φ^†φ) are shown as a function of M_φ and cτ_{π_d} for (a) m_{π_d} = 5 GeV, (b) m_{π_d} = 10 GeV, and (c) m_{π_d} = 20 GeV.

Comparison of observed and expected 95% CL limits of the Cut-Based analysis against the corresponding BDT-based analysis. Limits on σ(pp →φ^†φ) are shown as a function of M_φ and cτ_{π_d} for (a) m_{π_d} = 5 GeV, (b) m_{π_d} = 10 GeV, and (c) m_{π_d} = 20 GeV.

Comparison of observed and expected 95% CL limits of the Cut-Based analysis against the corresponding BDT-based analysis. Limits on σ(pp →φ^†φ) are shown as a function of M_φ and cτ_{π_d} for (a) m_{π_d} = 5 GeV, (b) m_{π_d} = 10 GeV, and (c) m_{π_d} = 20 GeV.

Normalized event-level BDT response distribution in data, with three selected signal samples for comparison.

Normalized jet-matched displaced vertex multiplicity (N_DV) distribution in data, with three selected signal samples for comparison.

Normalized event-level BDT response distribution in data, with three selected signal samples for comparison. All three signal models have M_φ = 1.8 TeV and cτ_{π_d} = 75 mm, but different m_{π_d}.

Normalized event-level BDT response distribution in data, with three selected signal samples for comparison. All three signal models have m_{π_d} = 10 GeV and cτ_{π_d} = 20 mm, but different M_φ.

Normalized event-level BDT response distribution in data, with three selected signal samples for comparison. All three signal models have m_{π_d} = 10 GeV and M_φ = 1.4 TeV, but different cτ_{π_d}.

Observed 95% CL limits for models with m_{π_d} = 5, 10, and 20 GeV and cτ_{π_d} = 1000 mm as a function of dark mediator mass. The mediator mass-dependent theoretical cross-section is given with the band corresponding to the uncertainty from NNLL-Fast.

Observed 95% CL limits for models with m_{π_d} = 5, 10, and 20 GeV and cτ_{π_d} = 500 mm as a function of dark mediator mass. The mediator mass-dependent theoretical cross-section is given with the band corresponding to the uncertainty from NNLL-Fast.

Observed 95% CL limits for models with m_{π_d} = 5, 10, and 20 GeV and cτ_{π_d} = 300 mm as a function of dark mediator mass. The mediator mass-dependent theoretical cross-section is given with the band corresponding to the uncertainty from NNLL-Fast.

Observed 95% CL limits for models with m_{π_d} = 5, 10, and 20 GeV and cτ_{π_d} = 150 mm as a function of dark mediator mass. The mediator mass-dependent theoretical cross-section is given with the band corresponding to the uncertainty from NNLL-Fast.

Observed 95% CL limits for models with m_{π_d} = 5, 10, and 20 GeV and cτ_{π_d} = 75 mm as a function of dark mediator mass. The mediator mass-dependent theoretical cross-section is given with the band corresponding to the uncertainty from NNLL-Fast.

Observed 95% CL limits for models with m_{π_d} = 5, 10, and 20 GeV and cτ_{π_d} = 20 mm as a function of dark mediator mass. The mediator mass-dependent theoretical cross-section is given with the band corresponding to the uncertainty from NNLL-Fast.

Observed 95% CL limits for models with m_{π_d} = 5, 10, and 20 GeV and cτ_{π_d} = 5 mm as a function of dark mediator mass. The mediator mass-dependent theoretical cross-section is given with the band corresponding to the uncertainty from NNLL-Fast.

Observed 95% CL limit for models with m_{π_d} = 5, 10, and 20 GeV and cτ_{π_d} = 2 mm as a function of dark mediator mass. The mediator mass-dependent theoretical cross-section is given with the band corresponding to the uncertainty from NNLL-Fast.

Observed 95% CL limits for models with m_{π_d} = 5, 10, and 20 GeV and cτ_{π_d} = 1 mm as a function of dark mediator mass. The mediator mass-dependent theoretical cross-section is given with the band corresponding to the uncertainty from NNLL-Fast.

Observed 95% CL limits for models with m_{π_d} = 5, 10, and 20 GeV and M_φ = 2.2 TeV as a function of dark pion lifetime. The mediator mass-dependent theoretical cross-section is given with the band corresponding to the uncertainty from NNLL-Fast.

Observed 95% CL limits for models with m_{π_d} = 5, 10, and 20 GeV and M_φ = 2 TeV as a function of dark pion lifetime. The mediator mass-dependent theoretical cross-section is given with the band corresponding to the uncertainty from NNLL-Fast.

Observed 95% CL limits for models with m_{π_d} = 5, 10, and 20 GeV and M_φ = 1.8 TeV as a function of dark pion lifetime. The mediator mass-dependent theoretical cross-section is given with the band corresponding to the uncertainty from NNLL-Fast.

Observed 95% CL limits for models with m_{π_d} = 5, 10, and 20 GeV and M_φ = 1.6 TeV as a function of dark pion lifetime. The mediator mass-dependent theoretical cross-section is given with the band corresponding to the uncertainty from NNLL-Fast.

Observed 95% CL limits for models with m_{π_d} = 5, 10, and 20 GeV and M_φ = 1.4 TeV as a function of dark pion lifetime. The mediator mass-dependent theoretical cross-section is given with the band corresponding to the uncertainty from NNLL-Fast.

Observed 95% CL limits for models with m_{π_d} = 5, 10, and 20 GeV and M_φ = 1 TeV as a function of dark pion lifetime. The mediator mass-dependent theoretical cross-section is given with the band corresponding to the uncertainty from NNLL-Fast.

Observed and expected 95% CL limits for models with m_{π_d} = 20 GeV as a function of M_φ and cτ_{π_d}.

Observed and expected 95% CL limits for models with m_{π_d} = 20 GeV as a function of M_φ and cτ_{π_d}.

Observed and expected 95% CL limits for models with m_{π_d} = 20 GeV as a function of M_φ and cτ_{π_d}.

Observed and expected 95% CL limits for models with m_{π_d} = 20 GeV as a function of M_φ and cτ_{π_d}.

Observed and expected 95% CL limits for models with m_{π_d} = 20 GeV as a function of M_φ and cτ_{π_d}.

Observed and expected 95% CL limits for models with m_{π_d} = 20 GeV as a function of M_φ and cτ_{π_d}.

Cut-Flow efficiencies for the m_{π_d} = 10 GeV, M_φ = 1600 GeV models for all cuts before entering the Search region (ABCD plane) and then for each of the ABCD regions separately.

Cut-Flow efficiencies for the m_{π_d} = 10 GeV, M_φ = 1400 GeV models for all cuts before entering the Search region (ABCD plane) and then for each of the ABCD regions separately.

Cut-Flow efficiencies for the m_{π_d} = 10 GeV, M_φ = 1000 GeV models for all cuts before entering the Search region (ABCD plane) and then for each of the ABCD regions separately.

Cut-Flow efficiencies for the m_{π_d} = 5 GeV, M_φ = 2200 GeV models for all cuts before entering the Search region (ABCD plane) and then for each of the ABCD regions separately.

Cut-Flow efficiencies for the m_{π_d} = 5 GeV, M_φ = 2000 GeV models for all cuts before entering the Search region (ABCD plane) and then for each of the ABCD regions separately.

Cut-Flow efficiencies for the m_{π_d} = 5 GeV, M_φ = 1800 GeV models for all cuts before entering the Search region (ABCD plane) and then for each of the ABCD regions separately.

Cut-Flow efficiencies for the m_{π_d} = 5 GeV, M_φ = 1600 GeV models for all cuts before entering the Search region (ABCD plane) and then for each of the ABCD regions separately.

Cut-Flow efficiencies for the m_{π_d} = 5 GeV, M_φ = 1400 GeV models for all cuts before entering the Search region (ABCD plane) and then for each of the ABCD regions separately.

Cut-Flow efficiencies for the m_{π_d} = 5 GeV, M_φ = 1000 GeV models for all cuts before entering the Search region (ABCD plane) and then for each of the ABCD regions separately.

Cut-Flow efficiencies for the m_{π_d} = 20 GeV, M_φ = 2200 GeV models for all cuts before entering the Search region (ABCD plane) and then for each of the ABCD regions separately.

Cut-Flow efficiencies for the m_{π_d} = 20 GeV, M_φ = 2000 GeV models for all cuts before entering the Search region (ABCD plane) and then for each of the ABCD regions separately.

Cut-Flow efficiencies for the m_{π_d} = 20 GeV, M_φ = 1800 GeV models for all cuts before entering the Search region (ABCD plane) and then for each of the ABCD regions separately.

Cut-Flow efficiencies for the m_{π_d} = 20 GeV, M_φ = 1600 GeV models for all cuts before entering the Search region (ABCD plane) and then for each of the ABCD regions separately.

Cut-Flow efficiencies for the m_{π_d} = 20 GeV, M_φ = 1400 GeV models for all cuts before entering the Search region (ABCD plane) and then for each of the ABCD regions separately.

Cut-Flow efficiencies for the m_{π_d} = 20 GeV, M_φ = 1000 GeV models for all cuts before entering the Search region (ABCD plane) and then for each of the ABCD regions separately.

Cut-Flow efficiencies for the m_{π_d} = 10 GeV, M_φ = 2200 GeV models for all cuts before entering the Search region (ABCD plane) and then for each of the ABCD regions separately.

Cut-Flow efficiencies for the m_{π_d} = 10 GeV, M_φ = 2000 GeV models for all cuts before entering the Search region (ABCD plane) and then for each of the ABCD regions separately.

Cut-Flow efficiencies for the m_{π_d} = 10 GeV, M_φ = 1800 GeV models for all cuts before entering the Search region (ABCD plane) and then for each of the ABCD regions separately.

The correlation matrix corresponding to the statistical uncertainties on the differential cross-section ($d\sigma/dp_T$) fit results for $W^-$. To combine with $W^+$ results (Fig8a), use the rows and columns ordered as $W^+$ and then $W^-$. Assume no correlation in the statistical uncertainties between $W^+$ and $W^-$ (zero entries in the off-diagonal blocks).

The correlation matrix corresponding to all of the systematic uncertainties on the differential cross-section ($d\sigma/dp_T$) fit results for $W^+$ and $W^-$ combined together, with rows and columns ordered as $W^+$ and then $W^-$.

Observed 95% $\text{CL}_\text{S}$ upper limits on the production cross-section times acceptance times branching ratio to jets, $\sigma \cdot A \cdot \text{BR}$, of Gaussian-shaped signals of 5%, 10%, and 15% width relative to their peak mass, $m_G$. Also included are the corresponding expected upper limits predicted for the case the $m_{jj}$ distribution is observed to be identical to the background prediction in each bin and the $1\sigma$ and $2\sigma$ envelopes of outcomes expected for Poisson fluctuations around the background expectation. Limits are derived from the J100 signal region.

Observed 95% $\text{CL}_\text{S}$ upper limits on the the value of the coupling to quarks, $g_q$, of the $Z^\prime$ model as a function of the resonance mass $m_{Z^\prime}$. Also included are the corresponding expected upper limits predicted for the case the $m_{jj}$ distribution is observed to be identical to the background prediction in each bin and the $1\sigma$ and $2\sigma$ envelopes of outcomes expected for Poisson fluctuations around the background expectation. Limits are derived from the J50 signal region.

Observed 95% $\text{CL}_\text{S}$ upper limits on the the value of the coupling to quarks, $g_q$, of the $Z^\prime$ model as a function of the resonance mass $m_{Z^\prime}$. Also included are the corresponding expected upper limits predicted for the case the $m_{jj}$ distribution is observed to be identical to the background prediction in each bin and the $1\sigma$ and $2\sigma$ envelopes of outcomes expected for Poisson fluctuations around the background expectation. Limits are derived from the J100 signal region.

Acceptance of simulated $Z^\prime$ signal events given the analysis event selection as a function of $m_{Z^\prime}$. The solid black line corresponds to the acceptance without a lower $m_{jj}$ requirement applied, the solid blue line includes the $m_{jj} > 344$ GeV requirement of the J50 signal region, and the solid red line includes the $m_{jj} > 481$ GeV requirement of the J100 signal region.

Numbers of events in each of the two considered datasets after consecutively applying the analysis selections.

Unfolded $R(\rho_{s})$ observable in the 2-to-3 measurement (normalized and divided by bin width). The parton level is defined with two stable top-quarks and a jet with $p_{T}>50$ GeV and $|\eta|<2.5$.

Covariance matrix for statistical effects of the measured $R(\rho_{s})$ observable after unfolding, for the 2-to-3 measurement (normalized)

Covariance matrix for statistical and systematic effects of the measured $R(\rho_{s})$ observable after unfolding, for the 2-to-3 measurement (normalized)

Impact of systematic uncertainties on the 2-to-3 unfolded observable. Values are given in percentage of bin content.

Central value and breakdown of the uncertainties affecting the top-quark pole mass extraction from the 2-to-3 unfolded observable.

Unfolded number of events in the 2-to-7measurement (not normalized). The parton level is defined with two neutrinos, one electron and one muon of opposite electric charges, two $b$-jets and an additional jet (extrajet). The four-momentum of the sum of neutrinos has transverse component larger than 30 GeV. The $p_{T}$-leading lepton has $p_{T}>28$ GeV, while the sub-leading has $p_{T}>20$ GeV. The two $b$-jets with have $p_{T}>30$ GeV and the extrajet has $p^\text{extrajet}_{T}>60$ GeV. All the leptons and jets are separated by $\Delta R >0.4$ and have $|\eta|<2.5$.

Covariance matrix for statistical effects of the measured number of events after unfolding, for the 2-to-7 measurement (not normalized)

Covariance matrix for statistical and systematic effects of the measured number of events after unfolding, for the 2-to-7 measurement (not normalized)

Unfolded $R(\rho_{s})$ observable in the 2-to-7 measurement (normalized and divided by bin width). The parton level is defined with two neutrinos, one electron and one muon of opposite electric charges, two $b$-jets and an additional jet (extrajet). The four-momentum of the sum of neutrinos has transverse component larger than 30 GeV. The $p_{T}$-leading lepton has $p_{T}>28$ GeV, while the sub-leading has $p_{T}>20$ GeV. The two $b$-jets with have $p_{T}>30$ GeV and the extrajet has $p^\text{extrajet}_{T}>60$ GeV. All the leptons and jets are separated by $\Delta R >0.4$ and have $|\eta|<2.5$.

Covariance matrix for statistical effects of the measured $R(\rho_{s})$ observable after unfolding, for the 2-to-7 measurement (normalized)

Covariance matrix for statistical and systematic effects of the measured $R(\rho_{s})$ observable after unfolding, for the 2-to-7 measurement (normalized)

Impact of systematic uncertainties on the 2-to-7 unfolded observable. Values are given in percentage of bin content.

Central value and breakdown of the uncertainties affecting the top-quark pole mass extraction from the 2-to-7 unfolded observable.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data, without any WTA flavour requirement. Normalization is set to unity. $20 < p_{\textrm{T,jet}} < 30$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data, without any WTA flavour requirement. Normalization is set to unity. $30 < p_{\textrm{T,jet}} < 50$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data, without any WTA flavour requirement. Normalization is set to unity. $50 < p_{\textrm{T,jet}} < 100$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data, without any WTA flavour requirement. Normalization is set to the soft drop tagging fraction, given by the number of groomed jets (without any WTA flavour requirement) to number of ungroomed jets (without any WTA flavour requirement). $10 < p_{\textrm{T,jet}} < 12$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data, without any WTA flavour requirement. Normalization is set to the soft drop tagging fraction, given by the number of groomed jets (without any WTA flavour requirement) to number of ungroomed jets (without any WTA flavour requirement). $12 < p_{\textrm{T,jet}} < 15$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data, without any WTA flavour requirement. Normalization is set to the soft drop tagging fraction, given by the number of groomed jets (without any WTA flavour requirement) to number of ungroomed jets (without any WTA flavour requirement). $15 < p_{\textrm{T,jet}} < 20$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data, without any WTA flavour requirement. Normalization is set to the soft drop tagging fraction, given by the number of groomed jets (without any WTA flavour requirement) to number of ungroomed jets (without any WTA flavour requirement). $20 < p_{\textrm{T,jet}} < 30$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data, without any WTA flavour requirement. Normalization is set to the soft drop tagging fraction, given by the number of groomed jets (without any WTA flavour requirement) to number of ungroomed jets (without any WTA flavour requirement). $30 < p_{\textrm{T,jet}} < 50$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data, without any WTA flavour requirement. Normalization is set to the soft drop tagging fraction, given by the number of groomed jets (without any WTA flavour requirement) to number of ungroomed jets (without any WTA flavour requirement). $50 < p_{\textrm{T,jet}} < 100$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data, without any WTA flavour requirement. Normalization is set to unity. $10 < p_{\textrm{T,jet}} < 12$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data, without any WTA flavour requirement. Normalization is set to unity. $12 < p_{\textrm{T,jet}} < 15$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data, without any WTA flavour requirement. Normalization is set to unity. $15 < p_{\textrm{T,jet}} < 20$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data, without any WTA flavour requirement. Normalization is set to unity. $20 < p_{\textrm{T,jet}} < 30$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data, without any WTA flavour requirement. Normalization is set to unity. $30 < p_{\textrm{T,jet}} < 50$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data, without any WTA flavour requirement. Normalization is set to unity. $50 < p_{\textrm{T,jet}} < 100$ GeV.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the WTA tagging fraction, given by the number of (groomed) jets tagged with WTA flavour to number of (groomed) jets without WTA flavour tagging. $10 < p_{\textrm{T,jet}} < 12$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the WTA tagging fraction, given by the number of (groomed) jets tagged with WTA flavour to number of (groomed) jets without WTA flavour tagging. $12 < p_{\textrm{T,jet}} < 15$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the WTA tagging fraction, given by the number of (groomed) jets tagged with WTA flavour to number of (groomed) jets without WTA flavour tagging. $15 < p_{\textrm{T,jet}} < 20$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the WTA tagging fraction, given by the number of (groomed) jets tagged with WTA flavour to number of (groomed) jets without WTA flavour tagging. $20 < p_{\textrm{T,jet}} < 30$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the WTA tagging fraction, given by the number of (groomed) jets tagged with WTA flavour to number of (groomed) jets without WTA flavour tagging. $30 < p_{\textrm{T,jet}} < 50$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the WTA tagging fraction, given by the number of (groomed) jets tagged with WTA flavour to number of (groomed) jets without WTA flavour tagging. $50 < p_{\textrm{T,jet}} < 100$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the soft drop tagging fraction, given by the number of groomed jets (tagged with WTA flavour) to number of ungroomed jets (tagged with WTA flavour). $10 < p_{\textrm{T,jet}} < 12$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the soft drop tagging fraction, given by the number of groomed jets (tagged with WTA flavour) to number of ungroomed jets (tagged with WTA flavour). $12 < p_{\textrm{T,jet}} < 15$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the soft drop tagging fraction, given by the number of groomed jets (tagged with WTA flavour) to number of ungroomed jets (tagged with WTA flavour). $15 < p_{\textrm{T,jet}} < 20$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the soft drop tagging fraction, given by the number of groomed jets (tagged with WTA flavour) to number of ungroomed jets (tagged with WTA flavour). $20 < p_{\textrm{T,jet}} < 30$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the soft drop tagging fraction, given by the number of groomed jets (tagged with WTA flavour) to number of ungroomed jets (tagged with WTA flavour). $30 < p_{\textrm{T,jet}} < 50$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Groomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet,gr}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the soft drop tagging fraction, given by the number of groomed jets (tagged with WTA flavour) to number of ungroomed jets (tagged with WTA flavour). $50 < p_{\textrm{T,jet}} < 100$ GeV, soft drop $z_{\textrm{cut}}=0.1, \beta=0$.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the WTA tagging fraction, given by the number of (ungroomed) jets tagged with WTA flavour to number of (ungroomed) jets without WTA flavour tagging. $10 < p_{\textrm{T,jet}} < 12$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the WTA tagging fraction, given by the number of (ungroomed) jets tagged with WTA flavour to number of (ungroomed) jets without WTA flavour tagging. $12 < p_{\textrm{T,jet}} < 15$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the WTA tagging fraction, given by the number of (ungroomed) jets tagged with WTA flavour to number of (ungroomed) jets without WTA flavour tagging. $15 < p_{\textrm{T,jet}} < 20$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the WTA tagging fraction, given by the number of (ungroomed) jets tagged with WTA flavour to number of (ungroomed) jets without WTA flavour tagging. $20 < p_{\textrm{T,jet}} < 30$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the WTA tagging fraction, given by the number of (ungroomed) jets tagged with WTA flavour to number of (ungroomed) jets without WTA flavour tagging. $30 < p_{\textrm{T,jet}} < 50$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to the WTA tagging fraction, given by the number of (ungroomed) jets tagged with WTA flavour to number of (ungroomed) jets without WTA flavour tagging. $50 < p_{\textrm{T,jet}} < 100$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to unity. $10 < p_{\textrm{T,jet}} < 12$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to unity. $12 < p_{\textrm{T,jet}} < 15$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to unity. $15 < p_{\textrm{T,jet}} < 20$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to unity. $20 < p_{\textrm{T,jet}} < 30$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to unity. $30 < p_{\textrm{T,jet}} < 50$ GeV.

Ungroomed $B^\pm$-tagged jet invariant mass $m_{\textrm{jet}}/p_{\textrm{T,jet}}$ for $R=0.5$ jets reconstructed in pp data tagged with WTA flavour. Normalization is set to unity. $50 < p_{\textrm{T,jet}} < 100$ GeV.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T}}^{\mathrm{lead.\,lep.}}$.

Fiducial differential cross-sections as a function of $p_{\mathrm{T}}^{\mathrm{sub-lead.\,lep.}}$. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The right-hand-side axis indicates the integrated cross-section of the rightmost bin. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T}}^{\mathrm{sub-lead.\,lep.}}$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T}}^{\mathrm{sub-lead.\,lep.}}$.

Fiducial differential cross-sections as a function of $p_{\mathrm{T},e\mu}$. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The right-hand-side axis indicates the integrated cross-section of the rightmost bin. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T},e\mu}$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T},e\mu}$.

Fiducial differential cross-sections as a function of $|y_{e\mu}|$. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $|y_{e\mu}|$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $|y_{e\mu}|$.

Fiducial differential cross-sections as a function of $m_{e\mu}$. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The right-hand-side axis indicates the integrated cross-section of the rightmost bin. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $m_{e\mu}$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $m_{e\mu}$.

Fiducial differential cross-sections as a function of $|\Delta\phi_{e\mu}|$. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $|\Delta\phi_{e\mu}|$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $|\Delta\phi_{e\mu}|$.

Fiducial differential cross-sections as a function of $\cos(\theta^{*})$. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $\cos(\theta^{*})$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $\cos(\theta^{*})$.

Fiducial differential cross-sections as a function of $E_{\mathrm{T}}^{\mathrm{miss}}$. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The right-hand-side axis indicates the integrated cross-section of the rightmost bin. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $E_{\mathrm{T}}^{\mathrm{miss}}$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $E_{\mathrm{T}}^{\mathrm{miss}}$.

Fiducial differential cross-sections as a function of $H_{\mathrm{T}}^{\mathrm{lep}+\mathrm{MET}}$. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The right-hand-side axis indicates the integrated cross-section of the rightmost bin. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $H_{\mathrm{T}}^{\mathrm{lep}+\mathrm{MET}}$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $H_{\mathrm{T}}^{\mathrm{lep}+\mathrm{MET}}$.

Fiducial differential cross-sections as a function of $m_{\mathrm{T},e\mu}$. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The right-hand-side axis indicates the integrated cross-section of the rightmost bin. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $m_{\mathrm{T},e\mu}$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $m_{\mathrm{T},e\mu}$.

Fiducial differential cross-sections as a function of the number of jets. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable Number of jets ($p_{\mathrm{T}} > $ 30 GeV).

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable Number of jets ($p_{\mathrm{T}} > $ 30 GeV).

Fiducial differential cross-sections as a function of $S_{\mathrm{T}}$. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The right-hand-side axis indicates the integrated cross-section of the rightmost bin. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $S_{\mathrm{T}}$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $S_{\mathrm{T}}$.

Fiducial differential cross-sections for $p_{\mathrm{T},e\mu}$ in the region with 85 $<m_{e\mu}<$ 150, for the nNNLO MATRIX prediction and various four flavour PDF sets. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The right-hand-side axis indicates the integrated cross-section of the rightmost bin. The measurement is compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1 using four different four-flavour NNLO PDF sets: NNPDF3.0, NNPDF3.1, CT18, and MSHT20.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T},e\mu}$ (85 $<m_{e\mu}<$ 150).

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T},e\mu}$ (85 $<m_{e\mu}<$ 150).

Fiducial differential cross-sections for $|y_{e\mu}|$ in the region with 85 $<m_{e\mu}<$ 150, for the nNNLO MATRIX prediction and various four flavour PDF sets. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The measurement is compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1 using four different four-flavour NNLO PDF sets: NNPDF3.0, NNPDF3.1, CT18, and MSHT20.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $|y_{e\mu}|$ (85 $<m_{e\mu}<$ 150).

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $|y_{e\mu}|$ (85 $<m_{e\mu}<$ 150).

Fiducial differential cross-sections for $p_{\mathrm{T},e\mu}$ in the region with 150 $<m_{e\mu}<$ 250, for the nNNLO MATRIX prediction and various four flavour PDF sets. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The right-hand-side axis indicates the integrated cross-section of the rightmost bin. The measurement is compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1 using four different four-flavour NNLO PDF sets: NNPDF3.0, NNPDF3.1, CT18, and MSHT20.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T},e\mu}$ (150 $<m_{e\mu}<$ 250).

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T},e\mu}$ (150 $<m_{e\mu}<$ 250).

Fiducial differential cross-sections for $|y_{e\mu}|$ in the region with 150 $<m_{e\mu}<$ 250, for the nNNLO MATRIX prediction and various four flavour PDF sets. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The measurement is compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1 using four different four-flavour NNLO PDF sets: NNPDF3.0, NNPDF3.1, CT18, and MSHT20.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $|y_{e\mu}|$ (150 $<m_{e\mu}<$ 250).

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $|y_{e\mu}|$ (150 $<m_{e\mu}<$ 250).

Fiducial differential cross-sections for $p_{\mathrm{T},e\mu}$ in the region with $m_{e\mu}>$ 250, for the nNNLO MATRIX prediction and various four flavour PDF sets. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The right-hand-side axis indicates the integrated cross-section of the rightmost bin. The measurement is compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1 using four different four-flavour NNLO PDF sets: NNPDF3.0, NNPDF3.1, CT18, and MSHT20.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T},e\mu}$ ($m_{e\mu}>$ 250).

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T},e\mu}$ ($m_{e\mu}>$ 250).

Fiducial differential cross-sections for $|y_{e\mu}|$ in the region with $m_{e\mu}>$ 250, for the nNNLO MATRIX prediction and various four flavour PDF sets. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The measurement is compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1 using four different four-flavour NNLO PDF sets: NNPDF3.0, NNPDF3.1, CT18, and MSHT20.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $|y_{e\mu}|$ ($m_{e\mu}>$ 250).

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $|y_{e\mu}|$ ($m_{e\mu}>$ 250).

Measured value of the charge asymmetry, $A_{C}$.

Charge asymmetry $A_C$ measured as a function of the absolute difference of the absolute lepton rapidities $||\eta_{l+}|-|\eta_{l-}||$. The measured values are shown as points, whose error bars represent the statistical uncertainty, while the solid bands indicate the size of the total uncertainty. In the bottom panel, the central value of the charge asymmetry divided by the total uncertainty of the $A_C$ measurement is shown. The measurement is compared with the NNLO+PS predictions from Powheg MiNNLO+Pythia8 with vertical lines denoting PDF uncertainties.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $A_{C}$ vs. $||\eta_{l+}|-|\eta_{l-}||$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $A_{C}$ vs. $||\eta_{l+}|-|\eta_{l-}||$.

Charge asymmetry $A_C$ measured as a function of the invariant mass of the dilepton system $m_{e\mu}$. The measured values are shown as points, whose error bars represent the statistical uncertainty, while the solid bands indicate the size of the total uncertainty. In the bottom panel, the central value of the charge asymmetry divided by the total uncertainty of the $A_C$ measurement is shown. The measurement is compared with the NNLO+PS predictions from Powheg MiNNLO+Pythia8 with vertical lines denoting PDF uncertainties.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $A_{C}$ vs. $m_{e\mu}$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $A_{C}$ vs. $m_{e\mu}$.

Measured value of the asymmetry in the CP-odd observable $O_{z}$, $A_{CP}$.

The 95% CL limits on the cross-section $\sigma(pp \rightarrow Z' \rightarrow \chi \chi$) times branching ratio B in fb with all statistical and systematic uncertainties, for the $R_{\text{inv}}=$0.6 signal points.

Data yield in the PFN signal region.

Yield of data in the ANTELOPE signal region in the binning used for BumpHunter fitting.

Observed correlations between the production cross-sections multiplied by the $H \to WW^{\ast}$ branching ratio measured in data for each of the STXS categories.

Values of the negative log likelihood of 2-dimensional $\sigma_{VBF} \times B{H \to WW^{\ast}}$ versus $\sigma_{ggF} \times B_{H \to WW^{\ast}}$ scans.

Observed correlations between the production cross-sections multiplied by the $H \to WW^{\ast}$ branching ratio measured in data for each of the $\textrm{STXS}_\textrm{CP}$ categories.

Expected correlations between the production cross-sections multiplied by the $H \to WW^{\ast}$ branching ratio for each of the $\textrm{STXS}_\textrm{CP}$ categories.

Expected values and uncertainties for the signal strengths measured in each of the $\textrm{STXS}_\textrm{CP}$ categories, normalised to the corresponding SM predictions, for ggH and EW qqH production.

Best-fit values and uncertainties for the signal strengths measured in each of the $\textrm{STXS}_\textrm{CP}$ categories, normalised to the corresponding SM predictions, for ggH and EW qqH production.

The composition of the (orthonormal) eigenvectors defining the rotated basis in terms of operators in the Warsaw basis, labelled in terms of their corresponding Wilson coefficients.

Post-fit DNN distribution for the ggF different flavour 0-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 10\ \textrm{GeV}$ signal region; the post-fit results are obtained from the 15-POI fit.

Post-fit DNN distribution for the ggF different flavour 0-jet $p_{T}^{\ell\ell, \textrm{miss}} \geq 10\ \textrm{GeV}$ signal region; the post-fit results are obtained from the 15-POI fit.

Post-fit DNN distribution for the ggF different flavour 1-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 60\ \textrm{GeV}$ signal region; the post-fit results are obtained from the 15-POI fit.

Post-fit DNN distribution for the ggF different flavour 1-jet $60 \leq p_{T}^{\ell\ell, \textrm{miss}} < 120\ \textrm{GeV}$ signal region; the post-fit results are obtained from the 15-POI fit.

Post-fit DNN distribution for the ggF different flavour 1-jet $120 \leq p_{T}^{\ell\ell, \textrm{miss}} < 200\ \textrm{GeV}$ signal region; the post-fit results are obtained from the 15-POI fit.

Post-fit DNN distribution for the ggF different flavour 2-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 200\ \textrm{GeV}$ signal region; the post-fit results are obtained from the 15-POI fit.

Post-fit DNN distribution for the ggF different flavour 1-jet $200 \leq p_{T}^{\ell\ell, \textrm{miss}} < 300\ \textrm{GeV}$ signal region; the post-fit results are obtained from the 15-POI fit.

Post-fit DNN distribution for the ggF different flavour 1-jet $p_{T}^{\ell\ell, \textrm{miss}} \geq 300\ \textrm{GeV}$ signal region; the post-fit results are obtained from the 15-POI fit.

Post-fit DNN distribution for the ggF different flavour 2-jet $200 \leq p_{T}^{\ell\ell, \textrm{miss}} < 300\ \textrm{GeV}$ signal region; the post-fit results are obtained from the 15-POI fit.

Post-fit DNN distribution for the ggF different flavour 2-jet $p_{T}^{\ell\ell, \textrm{miss}} \geq 300\ \textrm{GeV}$ signal region; the post-fit results are obtained from the 15-POI fit.

Post-fit DNN distribution for the ggF same flavour 2-jet $200 \leq p_{T}^{\ell\ell, \textrm{miss}} < 300\ \textrm{GeV}$ signal region; the post-fit results are obtained from the 15-POI fit.

Post-fit DNN distribution for the ggF same flavour 2-jet $p_{T}^{\ell\ell, \textrm{miss}} \geq 300\ \textrm{GeV}$ signal region; the post-fit results are obtained from the 15-POI fit.

Post-fit DNN distribution for the VBF different flavour 1-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 60\ \textrm{GeV}$ signal region; the post-fit results are obtained from the 15-POI fit.

Post-fit DNN distribution for the VBF different flavour 1-jet $60 \leq p_{T}^{\ell\ell, \textrm{miss}} < 120\ \textrm{GeV}$ signal region; the post-fit results are obtained from the 15-POI fit.

Post-fit DNN distribution for the VBF different flavour 1-jet $p_{T}^{\ell\ell, \textrm{miss}} \geq 120\ \textrm{GeV}$ signal region; the post-fit results are obtained from the 15-POI fit.

Post-fit DNN distribution for the VBF different flavour 2-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 200\ \textrm{GeV}$, $350 \leq m_{jj} < 700\ \textrm{GeV}$ signal region; the post-fit results are obtained from the 15-POI fit.

Post-fit DNN distribution for the VBF different flavour 2-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 200\ \textrm{GeV}$, $700 \leq m_{jj} < 1000\ \textrm{GeV}$ signal region; the post-fit results are obtained from the 15-POI fit.

Post-fit DNN distribution for the VBF different flavour 2-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 200\ \textrm{GeV}$, $1000 \leq m_{jj} < 1500\ \textrm{GeV}$ signal region; the post-fit results are obtained from the 15-POI fit.

Post-fit DNN distribution for the VBF different flavour 2-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 200\ \textrm{GeV}$, $m_{jj} \geq 1500\ \textrm{GeV}$ signal region; the post-fit results are obtained from the 15-POI fit.

Post-fit DNN distribution for the VBF same flavour 2-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 200\ \textrm{GeV}$, $350 \leq m_{jj} < 700\ \textrm{GeV}$ signal region; the post-fit results are obtained from the 15-POI fit.

Post-fit DNN distribution for the VBF same flavour 2-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 200\ \textrm{GeV}$, $700 \leq m_{jj} < 1000\ \textrm{GeV}$ signal region; the post-fit results are obtained from the 15-POI fit.

Post-fit DNN distribution for the VBF same flavour 2-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 200\ \textrm{GeV}$, $1000 \leq m_{jj} < 1500\ \textrm{GeV}$ signal region; the post-fit results are obtained from the 15-POI fit.

Post-fit DNN distribution for the VBF same flavour 2-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 200\ \textrm{GeV}$, $m_{jj} \geq 1500\ \textrm{GeV}$ signal region; the post-fit results are obtained from the 15-POI fit.

Post-fit DNN distribution for the VBF different flavour 2-jet $p_{T}^{\ell\ell, \textrm{miss}} \geq 200\ \textrm{GeV}$, $350 \leq m_{jj} < 1000\ \textrm{GeV}$ signal region; the post-fit results are obtained from the 15-POI fit.

Post-fit DNN distribution for the VBF different flavour 2-jet $p_{T}^{\ell\ell, \textrm{miss}} \geq 200\ \textrm{GeV}$, $1000 \leq m_{jj} < 1500\ \textrm{GeV}$ signal region; the post-fit results are obtained from the 15-POI fit.

Post-fit DNN distribution for the VBF different flavour 2-jet $p_{T}^{\ell\ell, \textrm{miss}} \geq 200\ \textrm{GeV}$, $m_{jj} \geq 1500\ \textrm{GeV}$ signal region; the post-fit results are obtained from the 15-POI fit.

Post-fit DNN distribution for the VBF same flavour 2-jet $p_{T}^{\ell\ell, \textrm{miss}} \geq 200\ \textrm{GeV}$, $350 \leq m_{jj} < 1000\ \textrm{GeV}$ signal region; the post-fit results are obtained from the 15-POI fit.

Post-fit DNN distribution for the VBF same flavour 2-jet $p_{T}^{\ell\ell, \textrm{miss}} \geq 200\ \textrm{GeV}$, $1000 \leq m_{jj} < 1500\ \textrm{GeV}$ signal region; the post-fit results are obtained from the 15-POI fit.

Post-fit DNN distribution for the VBF same flavour 2-jet $p_{T}^{\ell\ell, \textrm{miss}} \geq 200\ \textrm{GeV}$, $m_{jj} \geq 1500\ \textrm{GeV}$ signal region; the post-fit results are obtained from the 15-POI fit.

Post-fit DNN distribution for the ggF different flavour 2-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 200\ \textrm{GeV}$, $-\pi \leq \Delta \phi_{jj}^\pm < - \frac{\pi}{2}$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the ggF different flavour 2-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 200\ \textrm{GeV}$, $- \frac{\pi}{2} \leq \Delta \phi_{jj}^\pm < 0$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the ggF different flavour 2-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 200\ \textrm{GeV}$, $0 \leq \Delta \phi_{jj}^\pm < \frac{\pi}{2}$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the ggF different flavour 2-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 200\ \textrm{GeV}$, $\frac{\pi}{2} \leq \Delta \phi_{jj}^\pm < \pi$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the ggF different flavour 2-jet $p_{T}^{\ell\ell, \textrm{miss}} \geq 200\ \textrm{GeV}$, $-\pi \leq \Delta \phi_{jj}^\pm < - \frac{\pi}{2}$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the ggF different flavour 2-jet $p_{T}^{\ell\ell, \textrm{miss}} \geq 200\ \textrm{GeV}$, $- \frac{\pi}{2} \leq \Delta \phi_{jj}^\pm < 0$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the ggF different flavour 2-jet $p_{T}^{\ell\ell, \textrm{miss}} \geq 200\ \textrm{GeV}$, $0 \leq \Delta \phi_{jj}^\pm < \frac{\pi}{2}$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the ggF different flavour 2-jet $p_{T}^{\ell\ell, \textrm{miss}} \geq 200\ \textrm{GeV}$, $\frac{\pi}{2} \leq \Delta \phi_{jj}^\pm < \pi$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the ggF same flavour 2-jet $p_{T}^{\ell\ell, \textrm{miss}} \geq 200\ \textrm{GeV}$, $-\pi \leq \Delta \phi_{jj}^\pm < - \frac{\pi}{2}$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the ggF same flavour 2-jet $p_{T}^{\ell\ell, \textrm{miss}} \geq 200\ \textrm{GeV}$, $- \frac{\pi}{2} \leq \Delta \phi_{jj}^\pm < 0$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the ggF same flavour 2-jet $p_{T}^{\ell\ell, \textrm{miss}} \geq 200\ \textrm{GeV}$, $0 \leq \Delta \phi_{jj}^\pm < \frac{\pi}{2}$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the ggF same flavour 2-jet $p_{T}^{\ell\ell, \textrm{miss}} \geq 200\ \textrm{GeV}$, $\frac{\pi}{2} \leq \Delta \phi_{jj}^\pm < \pi$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the VBF different flavour 2-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 200\ \textrm{GeV}$, $350 \leq m_{jj} < 700\ \textrm{GeV}$, $-\pi \leq \Delta \phi_{jj}^\pm < - \frac{\pi}{2}$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the VBF different flavour 2-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 200\ \textrm{GeV}$, $350 \leq m_{jj} < 700\ \textrm{GeV}$, $- \frac{\pi}{2} \leq \Delta \phi_{jj}^\pm < 0$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the VBF different flavour 2-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 200\ \textrm{GeV}$, $350 \leq m_{jj} < 700\ \textrm{GeV}$, $0 \leq \Delta \phi_{jj}^\pm < \frac{\pi}{2}$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the VBF different flavour 2-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 200\ \textrm{GeV}$, $350 \leq m_{jj} < 700\ \textrm{GeV}$, $\frac{\pi}{2} \leq \Delta \phi_{jj}^\pm < \pi$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the VBF same flavour 2-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 200\ \textrm{GeV}$, $350 \leq m_{jj} < 700\ \textrm{GeV}$, $-\pi \leq \Delta \phi_{jj}^\pm < - \frac{\pi}{2}$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the VBF same flavour 2-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 200\ \textrm{GeV}$, $350 \leq m_{jj} < 700\ \textrm{GeV}$, $- \frac{\pi}{2} \leq \Delta \phi_{jj}^\pm < 0$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the VBF same flavour 2-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 200\ \textrm{GeV}$, $350 \leq m_{jj} < 700\ \textrm{GeV}$, $0 \leq \Delta \phi_{jj}^\pm < \frac{\pi}{2}$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the VBF same flavour 2-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 200\ \textrm{GeV}$, $350 \leq m_{jj} < 700\ \textrm{GeV}$, $\frac{\pi}{2} \leq \Delta \phi_{jj}^\pm < \pi$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the VBF different flavour 2-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 200\ \textrm{GeV}$, $m_{jj} \geq 700\ \textrm{GeV}$, $-\pi \leq \Delta \phi_{jj}^\pm < - \frac{\pi}{2}$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the VBF different flavour 2-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 200\ \textrm{GeV}$, $m_{jj} \geq 700\ \textrm{GeV}$, $- \frac{\pi}{2} \leq \Delta \phi_{jj}^\pm < 0$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the VBF different flavour 2-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 200\ \textrm{GeV}$, $m_{jj} \geq 700\ \textrm{GeV}$, $0 \leq \Delta \phi_{jj}^\pm < \frac{\pi}{2}$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the VBF different flavour 2-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 200\ \textrm{GeV}$, $m_{jj} \geq 700\ \textrm{GeV}$, $\frac{\pi}{2} \leq \Delta \phi_{jj}^\pm < \pi$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the VBF same flavour 2-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 200\ \textrm{GeV}$, $m_{jj} \geq 700\ \textrm{GeV}$, $-\pi \leq \Delta \phi_{jj}^\pm < - \frac{\pi}{2}$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the VBF same flavour 2-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 200\ \textrm{GeV}$, $m_{jj} \geq 700\ \textrm{GeV}$, $- \frac{\pi}{2} \leq \Delta \phi_{jj}^\pm < 0$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the VBF same flavour 2-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 200\ \textrm{GeV}$, $m_{jj} \geq 700\ \textrm{GeV}$, $0 \leq \Delta \phi_{jj}^\pm < \frac{\pi}{2}$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the VBF same flavour 2-jet $0 \leq p_{T}^{\ell\ell, \textrm{miss}} < 200\ \textrm{GeV}$, $m_{jj} \geq 700\ \textrm{GeV}$, $\frac{\pi}{2} \leq \Delta \phi_{jj}^\pm < \pi$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the VBF different flavour 2-jet $p_{T}^{\ell\ell, \textrm{miss}} \geq 200\ \textrm{GeV}$, $m_{jj} \geq 350\ \textrm{GeV}$, $-\pi \leq \Delta \phi_{jj}^\pm < - \frac{\pi}{2}$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the VBF different flavour 2-jet $p_{T}^{\ell\ell, \textrm{miss}} \geq 200\ \textrm{GeV}$, $m_{jj} \geq 350\ \textrm{GeV}$, $- \frac{\pi}{2} \leq \Delta \phi_{jj}^\pm < 0$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the VBF different flavour 2-jet $p_{T}^{\ell\ell, \textrm{miss}} \geq 200\ \textrm{GeV}$, $m_{jj} \geq 350\ \textrm{GeV}$, $0 \leq \Delta \phi_{jj}^\pm < \frac{\pi}{2}$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the VBF different flavour 2-jet $p_{T}^{\ell\ell, \textrm{miss}} \geq 200\ \textrm{GeV}$, $m_{jj} \geq 350\ \textrm{GeV}$, $\frac{\pi}{2} \leq \Delta \phi_{jj}^\pm < \pi$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the VBF same flavour 2-jet $p_{T}^{\ell\ell, \textrm{miss}} \geq 200\ \textrm{GeV}$, $m_{jj} \geq 350\ \textrm{GeV}$, $-\pi \leq \Delta \phi_{jj}^\pm < - \frac{\pi}{2}$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the VBF same flavour 2-jet $p_{T}^{\ell\ell, \textrm{miss}} \geq 200\ \textrm{GeV}$, $m_{jj} \geq 350\ \textrm{GeV}$, $- \frac{\pi}{2} \leq \Delta \phi_{jj}^\pm < 0$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the VBF same flavour 2-jet $p_{T}^{\ell\ell, \textrm{miss}} \geq 200\ \textrm{GeV}$, $m_{jj} \geq 350\ \textrm{GeV}$, $0 \leq \Delta \phi_{jj}^\pm < \frac{\pi}{2}$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.

Post-fit DNN distribution for the VBF same flavour 2-jet $p_{T}^{\ell\ell, \textrm{miss}} \geq 200\ \textrm{GeV}$, $m_{jj} \geq 350\ \textrm{GeV}$, $\frac{\pi}{2} \leq \Delta \phi_{jj}^\pm < \pi$ signal region used in the $\textrm{STXS}_\textrm{CP}$ measurement.