Systematic covariance matrix for the differential cross-section distribution.

Distribution of $E_{\text{T}}^{\text{miss}}$ in SROS-on-b-$e\mu\mu$. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by a black arrow. The last bin includes the overflow. The `Others' category contains the production of Higgs boson, 3-top, 4-top, and single-top processes. Distributions for SBH signals are overlaid. The bottom panels show the ratio of the observed data to the predicted total background yields. The hatched band includes all statistical and systematic uncertainties.

Distribution of $m_{\text{T}}^{\text{min}}$ in SROS-on-b-$e\mu\mu$. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by a black arrow. The last bin includes the overflow. The `Others' category contains the production of Higgs boson, 3-top, 4-top, and single-top processes. Distributions for SBH signals are overlaid. The bottom panels show the ratio of the observed data to the predicted total background yields. The hatched band includes all statistical and systematic uncertainties.

Distribution of $E_{\text{T}}^{\text{miss}}$ in SRSS-$2\mu$. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by a black arrow. The last bin includes the overflow. The `Others' category contains the production of Higgs boson, 3-top, 4-top, and single-top processes. Distributions for SBH signals are overlaid. The bottom panels show the ratio of the observed data to the predicted total background yields. The hatched band includes all statistical and systematic uncertainties.

Observed ($N_{\text{obs}}$) and expected ($N_{\text{exp}}$) yields after the background-only fit for the flavor-merged inclusive SRs. The third and fourth columns list the 95\% CL upper limits on the visible cross-section ($\sigma_{\text{vis}}^{95}$) and on the number of signal events ($S_\text{obs}^{95}$). The fifth column ($S_\text{exp}^{95}$) shows the 95\% CL upper limit on the number of signal events, given the expected number of background events and its $\pm 1\sigma$ variations. The last two columns indicate the CL$_{\text{b}}$ value, i.e. the confidence level observed for the background-only hypothesis, and the discovery $p$-value ($p(s = 0)$) with its associated statistical significance $Z$. If the observed yield is below the expected yield, the $p$-value is capped at 0.5.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{e}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{e}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{e}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{e}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{e}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{e}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{\mu}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{\mu}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{\mu}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{\mu}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{\mu}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{\mu}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Distribution of $E_{\text{T}}^{\text{miss}}$ in SROS-off-b-$e\mu\mu$. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by a black arrow. The last bin includes the overflow. The `Others' category contains the production of Higgs boson, 3-top, 4-top, and single-top processes. Distributions for SBH signals are overlaid. The bottom panels show the ratio of the observed data to the predicted total background yields. Ratio values outside the graph range are indicated by brown arrows. The hatched band includes all statistical and systematic uncertainties.

Distribution of $m_{\text{T}}^{\text{min}}$ in SROS-off-b-$e\mu\mu$. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by a black arrow. The last bin includes the overflow. The `Others' category contains the production of Higgs boson, 3-top, 4-top, and single-top processes. Distributions for SBH signals are overlaid. The bottom panels show the ratio of the observed data to the predicted total background yields. Ratio values outside the graph range are indicated by brown arrows. The hatched band includes all statistical and systematic uncertainties.

Distribution of $E_{\text{T}}^{\text{miss}}$ in SRSS-$eee$. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by a black arrow. The last bin includes the overflow. The `Others' category contains the production of Higgs boson, 3-top, 4-top, and single-top processes. Distributions for SBH signals are overlaid. The bottom panels show the ratio of the observed data to the predicted total background yields. Ratio values outside the graph range are indicated by brown arrows. The hatched band includes all statistical and systematic uncertainties.

Distribution of $E_{\text{T}}^{\text{miss}}$ in SRSS-$ee\mu$. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by a black arrow. The last bin includes the overflow. The `Others' category contains the production of Higgs boson, 3-top, 4-top, and single-top processes. Distributions for SBH signals are overlaid. The bottom panels show the ratio of the observed data to the predicted total background yields. Ratio values outside the graph range are indicated by brown arrows. The hatched band includes all statistical and systematic uncertainties.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 150 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 150 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 150 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 150 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 150 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 150 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $\Delta m(\tilde{\chi}^0_3, \tilde{\chi}^0_1)$ vs $\Delta m(\tilde{\ell}_{\text{L}}, \tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $\Delta m(\tilde{\chi}^0_3, \tilde{\chi}^0_1)$ vs $\Delta m(\tilde{\ell}_{\text{L}}, \tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $\Delta m(\tilde{\chi}^0_3, \tilde{\chi}^0_1)$ vs $\Delta m(\tilde{\ell}_{\text{L}}, \tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $\Delta m(\tilde{\chi}^0_3, \tilde{\chi}^0_1)$ vs $\Delta m(\tilde{\ell}_{\text{L}}, \tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $\Delta m(\tilde{\chi}^0_3, \tilde{\chi}^0_1)$ vs $\Delta m(\tilde{\ell}_{\text{L}}, \tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $\Delta m(\tilde{\chi}^0_3, \tilde{\chi}^0_1)$ vs $\Delta m(\tilde{\ell}_{\text{L}}, \tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100 GeV.

The expected upper limits on the cross-section for each signal point. The gray numbers represent the values. The expected (dashed) and observed (solid) 95% CL exclusion limits are overlaid. An asymptotic approximation is employed in the CL$_{\text{s}}$ calculation instead of the full calculation using pseudo-experiments.

The observed upper limits on the cross-section for each signal point. The gray numbers represent the values. The expected (dashed) and observed (solid) 95% CL exclusion limits are overlaid. An asymptotic approximation is employed in the CL$_{\text{s}}$ calculation instead of the full calculation using pseudo-experiments.

Acceptance for signals with $m(\tilde{\chi}^0_1)=100$ GeV in flavored-merged SRs. The acceptance is given by the ratio of weighted selected events in the SR to the weighted total number of generated events. The selection is based on generator-level particle information.

Acceptance for signals with $m(\tilde{\chi}^0_1)=100$ GeV in flavored-merged SRs. The acceptance is given by the ratio of weighted selected events in the SR to the weighted total number of generated events. The selection is based on generator-level particle information.

Acceptance for signals with $m(\tilde{\chi}^0_1)=100$ GeV in flavored-merged SRs. The acceptance is given by the ratio of weighted selected events in the SR to the weighted total number of generated events. The selection is based on generator-level particle information.

Acceptance for signals with $m(\tilde{\chi}^0_1)=100$ GeV in flavored-merged SRs. The acceptance is given by the ratio of weighted selected events in the SR to the weighted total number of generated events. The selection is based on generator-level particle information.

Acceptance for signals with $m(\tilde{\chi}^0_1)=100$ GeV in flavored-merged SRs. The acceptance is given by the ratio of weighted selected events in the SR to the weighted total number of generated events. The selection is based on generator-level particle information.

Acceptance for signals with $m(\tilde{\chi}^0_1)=100$ GeV in flavored-merged SRs. The acceptance is given by the ratio of weighted selected events in the SR to the weighted total number of generated events. The selection is based on generator-level particle information.

Acceptance for signals with $m(\tilde{\chi}^0_1)=100$ GeV in flavored-merged SRs. The acceptance is given by the ratio of weighted selected events in the SR to the weighted total number of generated events. The selection is based on generator-level particle information.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Summary of the number of events passing each selection for the $m(\tilde{\ell}_{\text{L}}^{\pm},\tilde{\chi}^0_3,\tilde{\chi}^0_1)=(300, 200, 100)$, $(550, 300, 100)$, $(450, 180, 100)$ GeV signal points, including all production processes. After the initial selections, the table is split into row blocks per inclusive region, and then further for each SR channel. Flavor-binned SRs are shown for SROS-on-b for reference. The generator level selections require to have two or more leptons.

Summary of the number of events passing each selection for the $m(\tilde{\ell}_{\text{L}}^{\pm},\tilde{\chi}^0_3,\tilde{\chi}^0_1)=(300, 200, 100)$, $(550, 300, 100)$, $(450, 180, 100)$ GeV signal points, including all production processes. After the initial selections, the table is split into row blocks per inclusive region, and then further for each SR channel. Flavor-binned SRs are shown for SROS-off-b for reference. The generator level selections require to have two or more leptons.

Summary of the number of events passing each selection for the $m(\tilde{\ell}_{\text{L}}^{\pm},\tilde{\chi}^0_3,\tilde{\chi}^0_1)=(300, 200, 100)$, $(550, 300, 100)$, $(450, 180, 100)$ GeV signal points, including all production processes. After the initial selections, the table is split into row blocks per inclusive region, and then further for each SR channel. Flavor-binned SRs are shown. The generator level selections require to have two or more leptons.

Born-level double-differential cross section $\frac{d^2\sigma (W^+\to e^+\nu) }{d m_{\text{T}}^{W} d |\eta| } $ for $m_T^W$ = [200-300] GeV including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level double-differential cross section $\frac{d^2\sigma (W^+\to e^+\nu) }{d m_{\text{T}}^{W} d |\eta| } $ for $m_T^W$ = [300-425] GeV including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level double-differential cross section $\frac{d^2\sigma (W^+\to e^+\nu) }{d m_{\text{T}}^{W} d |\eta| } $ for $m_T^W$ = [425-600] GeV including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level double-differential cross section $\frac{d^2\sigma (W^+\to e^+\nu) }{d m_{\text{T}}^{W} d |\eta| } $ for $m_T^W$ = [600-900] GeV including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level double-differential cross section $\frac{d^2\sigma (W^+\to e^+\nu) }{d m_{\text{T}}^{W} d |\eta| } $ for $m_T^W$ = [900-2000] GeV including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level double-differential cross section $\frac{d^2\sigma (W^-\to e^-\bar{\nu}) }{d m_{\text{T}}^{W} d |\eta| } $ for $m_T^W$ = [200-300] GeV including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level double-differential cross section $\frac{d^2\sigma (W^-\to e^-\bar{\nu}) }{d m_{\text{T}}^{W} d |\eta| } $ for $m_T^W$ = [300-425] GeV including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level double-differential cross section $\frac{d^2\sigma (W^-\to e^-\bar{\nu}) }{d m_{\text{T}}^{W} d |\eta| } $ for $m_T^W$ = [425-600] GeV including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level double-differential cross section $\frac{d^2\sigma (W^-\to e^-\bar{\nu}) }{d m_{\text{T}}^{W} d |\eta| } $ for $m_T^W$ = [600-900] GeV including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level double-differential cross section $\frac{d^2\sigma (W^-\to e^-\bar{\nu}) }{d m_{\text{T}}^{W} d |\eta| } $ for $m_T^W$ = [900-2000] GeV including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level double-differential cross section $\frac{d^2\sigma (W\to e\nu) }{d m_{\text{T}}^{W} d |\eta| } $ for $m_T^W$ = [200-300] GeV including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level double-differential cross section $\frac{d^2\sigma (W\to e\nu) }{d m_{\text{T}}^{W} d |\eta| } $ for $m_T^W$ = [300-425] GeV including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level double-differential cross section $\frac{d^2\sigma (W\to e\nu) }{d m_{\text{T}}^{W} d |\eta| } $ for $m_T^W$ = [425-600] GeV including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level double-differential cross section $\frac{d^2\sigma (W\to e\nu) }{d m_{\text{T}}^{W} d |\eta| } $ for $m_T^W$ = [600-900] GeV including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level double-differential cross section $\frac{d^2\sigma (W\to e\nu) }{d m_{\text{T}}^{W} d |\eta| } $ for $m_T^W$ = [900-2000] GeV including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level single-differential cross-section $\frac{d\sigma (W^+\to\mu^+\nu) }{d m_{\text{T}}^{W} } $ including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level single-differential cross-section $\frac{d\sigma (W^-\to\mu^-\bar{\nu}) }{d m_{\text{T}}^{W} } $ including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level single-differential cross-section $\frac{d\sigma (W\to\mu\nu) }{d m_{\text{T}}^{W} } $ including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level double-differential cross-section $\frac{d^2\sigma (W^+\to\mu^+\nu) }{d m_{\text{T}}^{W} d |\eta| } $ for $m_T^W$ = [200-300] GeV including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level double-differential cross-section $\frac{d^2\sigma (W^+\to\mu^+\nu) }{d m_{\text{T}}^{W} d |\eta| } $ for $m_T^W$ = [300-425] GeV including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level double-differential cross-section $\frac{d^2\sigma (W^+\to\mu^+\nu) }{d m_{\text{T}}^{W} d |\eta| } $ for $m_T^W$ = [425-600] GeV including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level double-differential cross-section $\frac{d^2\sigma (W^+\to\mu^+\nu) }{d m_{\text{T}}^{W} d |\eta| } $ for $m_T^W$ = [600-900] GeV including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level double-differential cross-section $\frac{d^2\sigma (W^+\to\mu^+\nu) }{d m_{\text{T}}^{W} d |\eta| } $ for $m_T^W$ = [900-2000] GeV including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level double-differential cross-section $\frac{d^2\sigma (W^-\to\mu^-\bar{\nu}) }{d m_{\text{T}}^{W} d |\eta| } $ for $m_T^W$ = [200-300] GeV including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level double-differential cross-section $\frac{d^2\sigma (W^-\to\mu^-\bar{\nu}) }{d m_{\text{T}}^{W} d |\eta| } $ for $m_T^W$ = [300-425] GeV including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level double-differential cross-section $\frac{d^2\sigma (W^-\to\mu^-\bar{\nu}) }{d m_{\text{T}}^{W} d |\eta| } $ for $m_T^W$ = [425-600] GeV including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level double-differential cross-section $\frac{d^2\sigma (W^-\to\mu^-\bar{\nu}) }{d m_{\text{T}}^{W} d |\eta| } $ for $m_T^W$ = [600-900] GeV including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level double-differential cross-section $\frac{d^2\sigma (W^-\to\mu^-\bar{\nu}) }{d m_{\text{T}}^{W} d |\eta| } $ for $m_T^W$ = [900-2000] GeV including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level double-differential cross-section $\frac{d^2\sigma (W\to\mu\nu) }{d m_{\text{T}}^{W} d |\eta| } $ for $m_T^W$ = [200-300] GeV including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level double-differential cross-section $\frac{d^2\sigma (W\to\mu\nu) }{d m_{\text{T}}^{W} d |\eta| } $ for $m_T^W$ = [300-425] GeV including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level double-differential cross-section $\frac{d^2\sigma (W\to\mu\nu) }{d m_{\text{T}}^{W} d |\eta| } $ for $m_T^W$ = [425-600] GeV including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level double-differential cross-section $\frac{d^2\sigma (W\to\mu\nu) }{d m_{\text{T}}^{W} d |\eta| } $ for $m_T^W$ = [600-900] GeV including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Born-level double-differential cross-section $\frac{d^2\sigma (W\to\mu\nu) }{d m_{\text{T}}^{W} d |\eta| } $ for $m_T^W$ = [900-2000] GeV including the absolute statistical and systematic uncertainties. Symmetric uncertainties are denoted by $\pm$ or $\mp$, where the upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level single-differential cross-section including the absolute statistical and systematic uncertainties in the $\ell^+$-channel. Physical sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level single-differential cross-section including the absolute statistical and systematic uncertainties in the $\ell^-$-channel. Physical sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level single-differential cross-section including the absolute statistical and systematic uncertainties in the $\ell^\pm$-channel. Physical sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level single-differential cross-section including the absolute statistical and systematic uncertainties in the $\ell^+$-channel. Orthogonal sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level single-differential cross-section including the absolute statistical and systematic uncertainties in the $\ell^-$-channel. Orthogonal sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level single-differential cross-section including the absolute statistical and systematic uncertainties in the $\ell^\pm$-channel. Orthogonal sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level double-differential cross-section including the absolute statistical and systematic uncertainties for $m_T^W=[200,300]\,\mathrm{GeV}$ in the $\ell^\pm$-channel. Physical sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level double-differential cross-section including the absolute statistical and systematic uncertainties for $m_T^W=[300,425]\,\mathrm{GeV}$ in the $\ell^\pm$-channel. Physical sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level double-differential cross-section including the absolute statistical and systematic uncertainties for $m_T^W=[425,600]\,\mathrm{GeV}$ in the $\ell^\pm$-channel. Physical sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level double-differential cross-section including the absolute statistical and systematic uncertainties for $m_T^W=[600,900]\,\mathrm{GeV}$ in the $\ell^\pm$-channel. Physical sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level double-differential cross-section including the absolute statistical and systematic uncertainties for $m_T^W=[900,2000]\,\mathrm{GeV}$ in the $\ell^\pm$-channel. Physical sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level double-differential cross-section including the absolute statistical and systematic uncertainties for $m_T^W=[200,300]\,\mathrm{GeV}$ in the $\ell^\pm$-channel. Physical sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level double-differential cross-section including the absolute statistical and systematic uncertainties for $m_T^W=[300,425]\,\mathrm{GeV}$ in the $\ell^\pm$-channel. Physical sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level double-differential cross-section including the absolute statistical and systematic uncertainties for $m_T^W=[425,600]\,\mathrm{GeV}$ in the $\ell^\pm$-channel. Physical sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level double-differential cross-section including the absolute statistical and systematic uncertainties for $m_T^W=[600,900]\,\mathrm{GeV}$ in the $\ell^\pm$-channel. Physical sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level double-differential cross-section including the absolute statistical and systematic uncertainties for $m_T^W=[900,2000]\,\mathrm{GeV}$ in the $\ell^\pm$-channel. Physical sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level double-differential cross-section including the absolute statistical and systematic uncertainties for $m_T^W=[200,300]\,\mathrm{GeV}$ in the $\ell^\pm$-channel. Physical sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level double-differential cross-section including the absolute statistical and systematic uncertainties for $m_T^W=[300,425]\,\mathrm{GeV}$ in the $\ell^\pm$-channel. Physical sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level double-differential cross-section including the absolute statistical and systematic uncertainties for $m_T^W=[425,600]\,\mathrm{GeV}$ in the $\ell^\pm$-channel. Physical sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level double-differential cross-section including the absolute statistical and systematic uncertainties for $m_T^W=[600,900]\,\mathrm{GeV}$ in the $\ell^\pm$-channel. Physical sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level double-differential cross-section including the absolute statistical and systematic uncertainties for $m_T^W=[900,2000]\,\mathrm{GeV}$ in the $\ell^\pm$-channel. Physical sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The systematic uncertainties are related to the unfolding procedure (``unf.''), the jet energy scale/resolution (``JER/JES''), the \met scale and resolution, the electron and muon scale, resolution and efficiency (``Eff.''), the multijet and $t\bar{t}$ (where $t\bar{t}$ RW refers to a reweighting to NNLO) background estimates and normalization of small background processes (``Norm.''). The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level double-differential cross-section including the absolute statistical and systematic uncertainties for $m_T^W=[200,300]\,\mathrm{GeV}$ in the $\ell^\pm$-channel. Orthogonal sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level double-differential cross-section including the absolute statistical and systematic uncertainties for $m_T^W=[300,425]\,\mathrm{GeV}$ in the $\ell^\pm$-channel. Orthogonal sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level double-differential cross-section including the absolute statistical and systematic uncertainties for $m_T^W=[425,600]\,\mathrm{GeV}$ in the $\ell^\pm$-channel. Orthogonal sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level double-differential cross-section including the absolute statistical and systematic uncertainties for $m_T^W=[600,900]\,\mathrm{GeV}$ in the $\ell^\pm$-channel. Orthogonal sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level double-differential cross-section including the absolute statistical and systematic uncertainties for $m_T^W=[900,2000]\,\mathrm{GeV}$ in the $\ell^\pm$-channel. Orthogonal sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level double-differential cross-section including the absolute statistical and systematic uncertainties for $m_T^W=[200,300]\,\mathrm{GeV}$ in the $\ell^\pm$-channel. Orthogonal sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level double-differential cross-section including the absolute statistical and systematic uncertainties for $m_T^W=[300,425]\,\mathrm{GeV}$ in the $\ell^\pm$-channel. Orthogonal sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level double-differential cross-section including the absolute statistical and systematic uncertainties for $m_T^W=[425,600]\,\mathrm{GeV}$ in the $\ell^\pm$-channel. Orthogonal sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level double-differential cross-section including the absolute statistical and systematic uncertainties for $m_T^W=[600,900]\,\mathrm{GeV}$ in the $\ell^\pm$-channel. Orthogonal sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level double-differential cross-section including the absolute statistical and systematic uncertainties for $m_T^W=[900,2000]\,\mathrm{GeV}$ in the $\ell^\pm$-channel. Orthogonal sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level double-differential cross-section including the absolute statistical and systematic uncertainties for $m_T^W=[200,300]\,\mathrm{GeV}$ in the $\ell^\pm$-channel. Orthogonal sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level double-differential cross-section including the absolute statistical and systematic uncertainties for $m_T^W=[300,425]\,\mathrm{GeV}$ in the $\ell^\pm$-channel. Orthogonal sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level double-differential cross-section including the absolute statistical and systematic uncertainties for $m_T^W=[425,600]\,\mathrm{GeV}$ in the $\ell^\pm$-channel. Orthogonal sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level double-differential cross-section including the absolute statistical and systematic uncertainties for $m_T^W=[600,900]\,\mathrm{GeV}$ in the $\ell^\pm$-channel. Orthogonal sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The luminosity uncertainty of $0.83\%$ is not included.

Combined Born-level double-differential cross-section including the absolute statistical and systematic uncertainties for $m_T^W=[900,2000]\,\mathrm{GeV}$ in the $\ell^\pm$-channel. Orthogonal sources of systematic uncertainties are shown. The upper sign corresponds to the one standard deviation upward shift of the uncertainty source. The luminosity uncertainty of $0.83\%$ is not included.

Ratio of the $e^\pm$- and $\mu^\pm$-channel single-differential cross sections including the absolute data statistical, $e$-$\mu$-uncorrelated (including signal and background statistical) and $e$-$\mu$-correlated systematic uncertainties and the total uncertainty.

Ratio of the $e^\pm$- and $\mu^\pm$-channel double-differential cross sections including the absolute data statistical, $e$-$\mu$-uncorrelated (including signal and background statistical) and $e$-$\mu$-correlated systematic uncertainties and the total uncertainty.

Asymmetry of the $\ell^+$- and $\ell^-$-channel single-differential cross-sections including the absolute total statistical and $\ell^+$-$\ell^-$-correlated systematic uncertainties and the total uncertainty.

Asymmetry of the $\ell^+$- and $\ell^-$-channel double-differential cross sections including the absolute total statistical and $\ell^+$-$\ell^-$-correlated systematic uncertainties and the total uncertainty.

Differential cross-section in bins of subleading muon $p_\mathrm{T]$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of leading muon $\eta$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of subleading muon $\eta$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of leading muon $\phi$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of subleading muon $\phi$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of leading charged particle jet $p_\mathrm{T]$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of subleading charged particle jet $p_\mathrm{T]$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of leading charged particle jet rapidity. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of subleading charged particle jet rapidity. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of leading charged particle jet azimuth. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of subleading charged particle jet azimuth. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of leading charged particle jet mass. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of subleading charged particle jet mass. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of leading charged particle jet constituent multiplicity. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of subleading charged particle jet constituent multiplicity. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of leading charged particle jet $\tau_1$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of subleading charged particle jet $\tau_1$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of leading charged particle jet $\tau_2$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of subleading charged particle jet $\tau_2$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of leading charged particle jet $\tau_3$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of subleading charged particle jet $\tau_3$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of leading charged particle jet $\tau_{21}$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of $\Delta R$ between the leading charged particle jet and the dilepton system. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

The Charged-hadron yields as a function of pT in different y selections in p+Pb collisions.

The K^{0}_{S} yields as a function of pT in different y selections in Pb+Pb photo-nuclear collisions.

The #Lambda yields as a function of pT in different y selections in Pb+Pb photo-nuclear collisions.

The #Xi^{-} yields as a function of pT in different y selections in Pb+Pb photo-nuclear collisions.

The K^{0}_{S} yields as a function of pT in different y selections in p+Pb collisions.

The #Lambda yields as a function of pT in different y selections in p+Pb collisions.

The #Xi^{-} yields as a function of pT in different y selections in p+Pb collisions.

The Charged-hadron and identified-hadron yields as a function of y in Pb+Pb photo-nuclear collisions.

The Charged-hadron and identified-hadron yields as a function of y in Pb+Pb photo-nuclear collisions.

The Charged-hadron and identified-hadron yields as a function of y in p+Pb collisions.

The Charged-hadron and identified-hadron yields as a function of y in p+Pb collisions.

The meanpT of charged hadrons and identified hadrons as a function of Nchrec in Pb+Pb photo-nuclear collisions.

The meanpT of charged hadrons and identified hadrons as a function of Nchrec in Pb+Pb photo-nuclear collisions.

The meanpT of charged hadrons and identified hadrons as a function of Nchrec in Pb+Pb photo-nuclear collisions.

The meanpT of charged hadrons and identified hadrons as a function of Nchrec in p+Pb collisions.

The meanpT of charged hadrons and identified hadrons as a function of Nchrec in p+Pb collisions.

The baryon to meson ratio as a function of pT in Pb+Pb photo-nuclear collisions.

The baryon to meson ratio as a function of pT in Pb+Pb photo-nuclear collisions.

The baryon to meson ratio as a function of pT in p+Pb collisions.

The baryon to meson ratio as a function of pT in p+Pb collisions.

The ratios of identified-strange-hadron yield to charged-hadron yields as a function of Nchrec in Pb+Pb photo-nuclear collisions.

The ratios of identified-strange-hadron yield to charged-hadron yields as a function of Nchrec in Pb+Pb photo-nuclear collisions.

The ratios of identified-strange-hadron yield to charged-hadron yields as a function of Nchrec in Pb+Pb photo-nuclear collisions.

The ratios of identified-strange-hadron yield to charged-hadron yields as a function of Nchrec in p+Pb collisions.

The ratios of identified-strange-hadron yield to charged-hadron yields as a function of Nchrec in p+Pb collisions.

IRing2 for HT2>=500 GeV, NJets>=5

IRing2 for HT2>=1000 GeV, NJets>=2

IRing2 for HT2>=1000 GeV, NJets>=3

IRing2 for HT2>=1000 GeV, NJets>=4

IRing2 for HT2>=1000 GeV, NJets>=5

IRing2 for HT2>=1500 GeV, NJets>=2

IRing2 for HT2>=1500 GeV, NJets>=3

IRing2 for HT2>=1500 GeV, NJets>=4

IRing2 for HT2>=1500 GeV, NJets>=5

IRing128 for HT2>=500 GeV, NJets>=2

IRing128 for HT2>=500 GeV, NJets>=3

IRing128 for HT2>=500 GeV, NJets>=4

IRing128 for HT2>=500 GeV, NJets>=5

IRing128 for HT2>=1000 GeV, NJets>=2

IRing128 for HT2>=1000 GeV, NJets>=3

IRing128 for HT2>=1000 GeV, NJets>=4

IRing128 for HT2>=1000 GeV, NJets>=5

IRing128 for HT2>=1500 GeV, NJets>=2

IRing128 for HT2>=1500 GeV, NJets>=3

IRing128 for HT2>=1500 GeV, NJets>=4

IRing128 for HT2>=1500 GeV, NJets>=5

ICyl16 for HT2>=500 GeV, NJets>=2

ICyl16 for HT2>=500 GeV, NJets>=3

ICyl16 for HT2>=500 GeV, NJets>=4

ICyl16 for HT2>=500 GeV, NJets>=5

ICyl16 for HT2>=1000 GeV, NJets>=2

ICyl16 for HT2>=1000 GeV, NJets>=3

ICyl16 for HT2>=1000 GeV, NJets>=4

ICyl16 for HT2>=1000 GeV, NJets>=5

ICyl16 for HT2>=1500 GeV, NJets>=2

ICyl16 for HT2>=1500 GeV, NJets>=3

ICyl16 for HT2>=1500 GeV, NJets>=4

ICyl16 for HT2>=1500 GeV, NJets>=5

IRing2 covariance for HT2>=500 GeV, NJets>=2 (Table 1)

IRing2 covariance for HT2>=500 GeV, NJets>=3 (Table 2)

IRing2 covariance for HT2>=500 GeV, NJets>=4 (Table 3)

IRing2 covariance for HT2>=500 GeV, NJets>=5 (Table 4)

IRing2 covariance for HT2>=1000 GeV, NJets>=2 (Table 5)

IRing2 covariance for HT2>=1000 GeV, NJets>=3 (Table 6)

IRing2 covariance for HT2>=1000 GeV, NJets>=4 (Table 7)

IRing2 covariance for HT2>=1000 GeV, NJets>=5 (Table 8)

IRing2 covariance for HT2>=1500 GeV, NJets>=2 (Table 9)

IRing2 covariance for HT2>=1500 GeV, NJets>=3 (Table 10)

IRing2 covariance for HT2>=1500 GeV, NJets>=4 (Table 11)

IRing2 covariance for HT2>=1500 GeV, NJets>=5 (Table 12)

IRing128 covariance for HT2>=500 GeV, NJets>=2 (Table 13)

IRing128 covariance for HT2>=500 GeV, NJets>=3 (Table 14)

IRing128 covariance for HT2>=500 GeV, NJets>=4 (Table 15)

IRing128 covariance for HT2>=500 GeV, NJets>=5 (Table 16)

IRing128 covariance for HT2>=1000 GeV, NJets>=2 (Table 17)

IRing128 covariance for HT2>=1000 GeV, NJets>=3 (Table 18)

IRing128 covariance for HT2>=1000 GeV, NJets>=4 (Table 19)

IRing128 covariance for HT2>=1000 GeV, NJets>=5 (Table 20)

IRing128 covariance for HT2>=1500 GeV, NJets>=2 (Table 21)

IRing128 covariance for HT2>=1500 GeV, NJets>=3 (Table 22)

IRing128 covariance for HT2>=1500 GeV, NJets>=4 (Table 23)

IRing128 covariance for HT2>=1500 GeV, NJets>=5 (Table 24)

ICyl16 covariance for HT2>=500 GeV, NJets>=2 (Table 25)

ICyl16 covariance for HT2>=500 GeV, NJets>=3 (Table 26)

ICyl16 covariance for HT2>=500 GeV, NJets>=4 (Table 27)

ICyl16 covariance for HT2>=500 GeV, NJets>=5 (Table 28)

ICyl16 covariance for HT2>=1000 GeV, NJets>=2 (Table 29)

ICyl16 covariance for HT2>=1000 GeV, NJets>=3 (Table 30)

ICyl16 covariance for HT2>=1000 GeV, NJets>=4 (Table 31)

ICyl16 covariance for HT2>=1000 GeV, NJets>=5 (Table 32)

ICyl16 covariance for HT2>=1500 GeV, NJets>=2 (Table 33)

ICyl16 covariance for HT2>=1500 GeV, NJets>=3 (Table 34)

ICyl16 covariance for HT2>=1500 GeV, NJets>=4 (Table 35)

ICyl16 covariance for HT2>=1500 GeV, NJets>=5 (Table 36)

IRing2 covariance, complete

1-IRing128 covariance, complete

1-ICyl16 covariance, complete

Data from Fig 6d. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from Fig 6e. The unfolded $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from Fig 6f. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from Fig 7a. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from Fig 7b. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from Fig 7c. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from Fig 7d. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from Fig 7e. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from Fig 7f. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from Fig 8a. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from Fig 8b. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from Fig 8c. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from Fig 8d. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from Fig 8e. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from Fig 8f. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from Fig 14a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from Fig 14b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 4b. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 21b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 5a. The unfolded $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 5b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from Fig 14c. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from Fig 14d. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 4c. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 4d. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 5c. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 5d. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from Fig 14e. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from Fig 14f. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 4e. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 4f. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 5e. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 5f. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from Fig 14a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from Fig 14b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 4a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 4b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 5a. The unfolded $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 5b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from Fig 14c. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from Fig 14d. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 4c. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 4d. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 5c. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 5d. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from Fig 14e. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from Fig 14f. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 4e. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 4f. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 5e. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 5f. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from Fig 36-40a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from Fig 81-85a. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from Fig 36-40b. The unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from Fig 81-85b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from Fig 36-40c. The unfolded $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from Fig 81-85c. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from Fig 51-55a. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from Fig 101-105a. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from Fig 51-55b. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from Fig 101-105b. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from Fig 51-55c. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from Fig 101-105c. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from Fig 66-70a. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from Fig 106-110a. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from Fig 66-70b. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from Fig 106-110b. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from Fig 66-70c. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from Fig 106-110c. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from Fig 26-30a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from Fig 71-75a. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from Fig 26-30b. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from Fig 71-75b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from Fig 26-30c. The unfolded $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from Fig 71-75c. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from Fig 41-45a. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from Fig 86-90a. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from Fig 41-45b. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from Fig 86-90b. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from Fig 41-45c. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from Fig 86-90c. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from Fig 56-60a. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from Fig 101-105a. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from Fig 56-60b. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from Fig 101-105b. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from Fig 56-60c. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from Fig 101-105c. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from Fig 31-35a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from Fig 76-80a. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from Fig 31-35b. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from Fig 76-80b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from Fig 31-35c. The unfolded $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from Fig 76-80c. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from Fig 46-50a. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from Fig 91-95a. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from Fig 46-50b. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from Fig 91-95b. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from Fig 46-50c. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from Fig 91-95c. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from Fig 61-65a. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from Fig 106-110a. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from Fig 61-65b. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from Fig 106-110b. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from Fig 61-65c. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from Fig 106-110c. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from FigAux 6a. The extracted quark-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from Fig 15a. Theextracted quark-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 6b. The extracted quark-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from Fig 15b. The extracted quark-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 6c. The extracted quark-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from Fig 15c. The extracted quark-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 7a. The extracted quark-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from Fig 16a. The extracted quark-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 7b. The extracted quark-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from Fig 16b. The extracted quark-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 7c. The extracted quark-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from Fig 16c. The extracted quark-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 8a. The extracted quark-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from Fig 17a. The extracted quark-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 8b. The extracted quark-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from Fig 17b. The extracted quark-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 8c. The extracted quark-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from Fig 17c. The extracted quark-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 6a. The extracted gluon-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from Fig 15a. Theextracted gluon-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 6b. The extracted gluon-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from Fig 15b. The extracted gluon-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 6c. The extracted gluon-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from Fig 15c. The extracted gluon-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 7a. The extracted gluon-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from Fig 16a. The extracted gluon-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 7b. The extracted gluon-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from Fig 16b. The extracted gluon-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 7c. The extracted gluon-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from Fig 16c. The extracted gluon-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 8a. The extracted gluon-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from Fig 17a. The extracted gluon-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 8b. The extracted gluon-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from Fig 17b. The extracted gluon-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 8c. The extracted gluon-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from Fig 17c. The extracted gluon-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 99a. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 100a. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 99b. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 100b. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 99c. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 100c. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 101a. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 102a. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 101b. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 102b. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 101c. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 102c. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 103a. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 104a. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 103b. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 104b. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 103c. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 104c. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 105a. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 106a. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 105b. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 106b. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 105c. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 106c. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 107a. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 108a. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 107b. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 108b. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 107c. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 108c. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 109a. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 110a. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 109b. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 110b. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 109c. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 110c. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 111a. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 112a. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 111b. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 112b. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 111c. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 112c. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 113a. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 114a. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 113b. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 114b. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 113c. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 114c. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 115a. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 116a. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 115b. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 116b. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 115c. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 116c. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.

Data from FigAux 99d. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from FigAux 100d. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from FigAux 99e. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from FigAux 100e. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from FigAux 99f. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from FigAux 100f. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from FigAux 101d. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from FigAux 102d. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from FigAux 101e. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from FigAux 102e. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from FigAux 101f. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from FigAux 102f. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from FigAux 103d. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from FigAux 104d. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from FigAux 103e. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from FigAux 104e. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from FigAux 103f. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from FigAux 104f. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from FigAux 105d. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from FigAux 106d. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from FigAux 105e. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from FigAux 106e. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from FigAux 105f. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from FigAux 106f. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from FigAux 107d. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from FigAux 108d. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from FigAux 107e. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from FigAux 108e. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from FigAux 107f. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from FigAux 108f. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from FigAux 109d. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from FigAux 110d. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from FigAux 109e. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from FigAux 110e. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from FigAux 109f. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from FigAux 110f. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from FigAux 111d. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 112d. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 111e. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.

Data from FigAux 112e. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from FigAux 111f. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from FigAux 112f. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.

Data from FigAux 113d. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from FigAux 114d. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from FigAux 113e. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from FigAux 114e. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from FigAux 113f. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from FigAux 114f. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.

Data from FigAux 115d. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from FigAux 116d. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from FigAux 115e. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from FigAux 116e. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from FigAux 115f. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Data from FigAux 116f. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).

Distribution of exclusive jet multiplicity.

Breakdown of systematic uncertainties in percent in exclusive jet multiplicity in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in exclusive jet multiplicity in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of pT (leading jet) [GeV] with at least one jet in the event.

Breakdown of systematic uncertainties in percent in pT (leading jet) [GeV] with at least one jet in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in pT (leading jet) [GeV] with at least one jet in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of pT (leading jet) [GeV] with exactly one jet in the event.

Breakdown of systematic uncertainties in percent in pT (leading jet) [GeV] with exactly one jet in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in pT (leading jet) [GeV] with exactly one jet in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of pT (leading jet) [GeV] with at least two jets in the event.

Breakdown of systematic uncertainties in percent in pT (leading jet) [GeV] with at least two jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in pT (leading jet) [GeV] with at least two jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of pT (leading jet) [GeV] with at least three jets in the event.

Breakdown of systematic uncertainties in percent in pT (leading jet) [GeV] with at least three jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in pT (leading jet) [GeV] with at least three jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of pT (2nd jet) [GeV] with at least two jets in the event.

Breakdown of systematic uncertainties in percent in pT (2nd jet) [GeV] with at least two jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in pT (2nd jet) [GeV] with at least two jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of pT (3rd jet) [GeV] with at least three jets in the event.

Breakdown of systematic uncertainties in percent in pT (3rd jet) [GeV] with at least three jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in pT (3rd jet) [GeV] with at least three jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of pT (4th jet) [GeV] with at least four jets in the event.

Breakdown of systematic uncertainties in percent in pT (4th jet) [GeV] with at least four jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in pT (4th jet) [GeV] with at least four jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of pT (5th jet) [GeV] with at least five jets in the event.

Breakdown of systematic uncertainties in percent in pT (5th jet) [GeV] with at least five jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in pT (5th jet) [GeV] with at least five jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of leading jet rapidity with at least one jet in the event.

Breakdown of systematic uncertainties in percent in leading jet rapidity with at least one jet in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in leading jet rapidity with at least one jet in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of 2nd jet rapidity with at least two jets in the event.

Breakdown of systematic uncertainties in percent in 2nd jet rapidity with at least two jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in 2nd jet rapidity with at least two jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of HT [GeV] with at least one jet in the event.

Breakdown of systematic uncertainties in percent in HT [GeV] with at least one jet in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in HT [GeV] with at least one jet in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of HT [GeV] with exactly one jet in the event.

Breakdown of systematic uncertainties in percent in HT [GeV] with exactly one jet in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in HT [GeV] with exactly one jet in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of HT [GeV] with at least two jets in the event.

Breakdown of systematic uncertainties in percent in HT [GeV] with at least two jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in HT [GeV] with at least two jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of HT [GeV] with exactly two jets in the event.

Breakdown of systematic uncertainties in percent in HT [GeV] with exactly two jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in HT [GeV] with exactly two jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of HT [GeV] with at least three jets in the event.

Breakdown of systematic uncertainties in percent in HT [GeV] with at least three jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in HT [GeV] with at least three jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of HT [GeV] with exactly three jets in the event.

Breakdown of systematic uncertainties in percent in HT [GeV] with exactly three jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in HT [GeV] with exactly three jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of HT [GeV] with at least four jets in the event.

Breakdown of systematic uncertainties in percent in HT [GeV] with at least four jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in HT [GeV] with at least four jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of HT [GeV] with at least five jets in the event.

Breakdown of systematic uncertainties in percent in HT [GeV] with at least five jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in HT [GeV] with at least five jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of DPhi(jj) [GeV] with at least two jets in the event.

Breakdown of systematic uncertainties in percent in DPhi(jj) [GeV] with at least two jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in DPhi(jj) [GeV] with at least two jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of Dy(jj) [GeV] with at least two jets in the event.

Breakdown of systematic uncertainties in percent in Dy(jj) [GeV] with at least two jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in Dy(jj) [GeV] with at least two jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of DR(jj) [GeV] with at least two jets in the event.

Breakdown of systematic uncertainties in percent in DR(jj) [GeV] with at least two jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in DR(jj) [GeV] with at least two jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of m(jj) [GeV] with at least two jets in the event.

Breakdown of systematic uncertainties in percent in m(jj) [GeV] with at least two jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in m(jj) [GeV] with at least two jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of 3rd jet rapidity with at least three jets in the event.

Breakdown of systematic uncertainties in percent in 3rd jet rapidity with at least three jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in 3rd jet rapidity with at least three jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of 4th jet rapidity with at least four jets in the event.

Breakdown of systematic uncertainties in percent in 4th jet rapidity with at least four jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in 4th jet rapidity with at least four jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of 5th jet rapidity with at least five jets in the event.

Breakdown of systematic uncertainties in percent in 5th jet rapidity with at least five jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in 5th jet rapidity with at least five jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of ST [GeV] with at least one jet in the event.

Breakdown of systematic uncertainties in percent in ST [GeV] with at least one jet in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in ST [GeV] with at least one jet in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of ST [GeV] with at least two jets in the event.

Breakdown of systematic uncertainties in percent in ST [GeV] with at least two jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in ST [GeV] with at least two jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of ST [GeV] with exactly two jets in the event.

Breakdown of systematic uncertainties in percent in ST [GeV] with exactly two jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in ST [GeV] with exactly two jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of ST [GeV] with at least three jets in the event.

Breakdown of systematic uncertainties in percent in ST [GeV] with at least three jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in ST [GeV] with at least three jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of ST [GeV] with exactly three jets in the event.

Breakdown of systematic uncertainties in percent in ST [GeV] with exactly three jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in ST [GeV] with exactly three jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of ST [GeV] with at least four jets in the event.

Breakdown of systematic uncertainties in percent in ST [GeV] with at least four jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in ST [GeV] with at least four jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Distribution of ST [GeV] with at least five jets in the event.

Breakdown of systematic uncertainties in percent in ST [GeV] with at least five jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Breakdown of systematic uncertainties in percent in ST [GeV] with at least five jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of the number of $l/c$-jets compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $H_{\text{T}}^{\text{had}}$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $\Delta R_{\text{avg}}^{bb}$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $p_{\text{T}}(b_{1})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $p_{\text{T}}(b_{2})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $p_{\text{T}}(b_{1}^{\text{top}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $p_{\text{T}}(b_{2}^{\text{top}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $p_{\text{T}}(b_{3})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $p_{\text{T}}(b_{1}^{\text{add}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $m(b_{1}b_{2})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $p_{\text{T}}(b_{1}b_{2})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $m(bb^{\text{top}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $p_{\text{T}}(bb^{\text{top}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $\Delta R(e\mu bb^{\text{top}}, b_{1}^{\text{add}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets and at least one $l/c$-jet as a function of $\Delta R(e\mu bb^{\text{top}}, l/c\text{-jet}_{1})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets and at least one $l/c$-jet as a function of $p_{\text{T}}(l/c\text{-jet}_{1})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets and at least one $l/c$-jet as a function of $p_{\text{T}}(l/c\text{-jet}_{1}) - p_{\text{T}}(b_{1}^{\text{add}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $m(bb^{\text{min}\Delta R})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(bb^{\text{min}\Delta R})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $m(bb^{\text{add}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(bb^{\text{add}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $|\eta(b_{3})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $|\eta(b_{1}^{\text{add}})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $\Delta R(b_{1}b_{2})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $m(e\mu bb^{\text{top}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $|\eta(l/c\text{-jet}_{1})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $\Delta\eta_{\text{max}}^{jj}$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $H_{\text{T}}^{\text{all}}$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $m(e\mu b_{1}b_{2})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $|\eta(b_{1})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $|\eta(b_{2})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $|\eta(b_{1}^{\text{top}})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $|\eta(b_{2}^{\text{top}})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(b_{1})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(b_{2})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(b_{1}^{\text{top}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(b_{2}^{\text{top}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(b_{3})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(b_{4})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(b_{1}^{\text{add}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(b_{2}^{\text{add}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $m(b_{1}b_{2})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(b_{1}b_{2})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $m(bb^{\text{top}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(bb^{\text{top}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $H_{\text{T}}^{\text{all}}$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $m(e\mu b_{1}b_{2})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $m(e\mu bb^{\text{top}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $H_{\text{T}}^{\text{had}}$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $\text{min}\Delta R(bb)$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $\Delta R(e\mu bb^{\text{top}}, b_{1}^{\text{add}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $\Delta R_{\text{avg}}^{bb}$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $\Delta\eta_{\text{max}}^{jj}$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of the number of $l/c$-jets compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets and at least one $l/c$-jet as a function of $p_{\text{T}}(l/c\text{-jet}_{1})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets and at least one $l/c$-jet as a function of $|\eta(l/c\text{-jet}_{1})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets and at least one $l/c$-jet as a function of $\Delta R(e\mu bb^{\text{top}}, l/c\text{-jet}_{1})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets and at least one $l/c$-jet as a function of $p_{\text{T}}(l/c\text{-jet}_{1}) - p_{\text{T}}(b_{1}^{\text{add}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $|\eta(b_{1})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $|\eta(b_{2})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $|\eta(b_{1}^{\text{top}})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at leastfour $b$-jets as a function of $|\eta(b_{2}^{\text{top}})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $|\eta(b_{3})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $|\eta(b_{4})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $|\eta(b_{1}^{\text{add}})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $|\eta(b_{2}^{\text{add}})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

The measured normalised differential cross-section as a function of $N_{b-\text{jets}}$ in the $e\mu+\geq2b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $H_{\text{T}}^{\text{had}}$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $H_{\text{T}}^{\text{all}}$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $\Delta R_{\text{avg}}^{bb}$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $\Delta\eta_{\text{max}}^{jj}$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{1})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{1}^{\text{top}})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{2})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{2}^{\text{top}})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{3})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{1}^{\text{add}})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(b_{1})|$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(b_{1}^{\text{top}})|$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(b_{2})|$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(b_{2}^{\text{top}})|$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(b_{3})|$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(b_{1}^{\text{add}})|$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $m(b_{1}b_{2})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{1}b_{2})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $m(bb^{\text{top}})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(bb^{\text{top}})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $m(e\mu b_{1}b_{2})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $m(e\mu bb^{\text{top}})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $\Delta R(b_{1}b_{2})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $N_{l/c-\text{jets}}$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $\Delta R(e\mu b_{1}b_{2},b_{3})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $\Delta R(e\mu bb^{\text{top}}, b_{1}^{\text{add}})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $\Delta R(e\mu bb^{\text{top}},l/c-\text{jet})$ in the $e\mu+\geq3b+\geq1l/c-\text{jet}$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(l/c\text{-jet}_{1}) - p_{\text{T}}(b_{1}^{\text{add}})$ in the $e\mu+\geq3b+\geq1l/c-\text{jet}$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(l/c\text{-jet}_{1})|$ in the $e\mu+\geq3b+\geq1l/c-\text{jet}$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(l/c\text{-jet}_{1})$ in the $e\mu+\geq3b+\geq1l/c-\text{jet}$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $H_{\text{T}}^{\text{had}}$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $H_{\text{T}}^{\text{all}}$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $\Delta R_{\text{avg}}^{bb}$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $\Delta\eta_{\text{max}}^{jj}$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{1})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{1}^{\text{top}})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{2})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{2}^{\text{top}})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{3})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{1}^{\text{add}})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{4})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{2}^{\text{add}})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(b_{1})|$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(b_{1}^{\text{top}})|$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(b_{2})|$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(b_{2}^{\text{top}})|$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(b_{3})|$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(b_{1}^{\text{add}})|$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(b_{4})|$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(b_{2}^{\text{add}})|$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $m(b_{1}b_{2})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{1}b_{2})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $m(bb^{\text{top}})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(bb^{\text{top}})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $m(e\mu b_{1}b_{2})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $m(e\mu bb^{\text{top}})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $m(bb^{\text{min}\Delta R})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(bb^{\text{min}\Delta R})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $m(bb^{\text{add}})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(bb^{\text{add}})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $\text{min}\Delta R(bb)$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $\Delta R(b_{1}b_{2})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $N_{l/c-\text{jets}}$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $\Delta R(e\mu b_{1}b_{2},b_{3})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $\Delta R(e\mu bb^{\text{top}}, b_{1}^{\text{add}})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $\Delta R(e\mu bb^{\text{top}}, l/c\text{-jet}_{1})$ in the $e\mu+\geq4b+\geq1l/c-\text{jet}$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(l/c\text{-jet}_{1}) - p_{\text{T}}(b_{1}^{\text{add}})$ in the $e\mu+\geq4b+\geq1l/c-\text{jet}$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(l/c\text{-jet}_{1})|$ in the $e\mu+\geq4b+\geq1l/c-\text{jet}$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(l/c\text{-jet}_{1})$ in the $e\mu+\geq4b+\geq1l/c-\text{jet}$ phase space. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $N_{b-\text{jets}}$ in the phase space with at least two b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $N_{b-\text{jets}}$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $H_{\text{T}}^{\text{had}}$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $H_{\text{T}}^{\text{all}}$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $\Delta R_{\text{avg}}^{bb}$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $\Delta\eta_{\text{max}}^{jj}$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{1})$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{1}^{\text{top}})$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{2})$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{2}^{\text{top}})$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{3})$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{1}^{\text{add}})$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{1})|$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{1}^{\text{top}})|$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{2}^{\text{top}})|$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{2}^{\text{top}})|$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{3})|$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{1}^{\text{add}})|$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $m(b_{1}b_{2})$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{1}b_{2})$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $m(bb^{\text{top}})$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(bb^{\text{top}})$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $m(e\mu b_{1}b_{2})$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $m(e\mu bb^{\text{top}})$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $\Delta R(b_{1}b_{2})$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $N_{l/c-\text{jets}}$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $\Delta R(e\mu b_{1}b_{2},b_{3})$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $\Delta R(e\mu bb^{\text{top}}, b_{1}^{\text{add}})$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $\Delta R(e\mu bb^{\text{top}},l/c-\text{jet})$ in the phase space with at least three b-jets and at least one $l/c$-jet. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(l/c\text{-jet}_{1}) - p_{\text{T}}(b_{1}^{\text{add}})$ in the phase space with at least three b-jets and at least one $l/c$-jet. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(l/c\text{-jet}_{1})|$ in the phase space with at least three b-jets and at least one $l/c$-jet. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(l/c\text{-jet}_{1})$ in the phase space with at least three b-jets and at least one $l/c$-jet. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $H_{\text{T}}^{\text{had}}$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $H_{\text{T}}^{\text{all}}$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $\Delta R_{\text{avg}}^{bb}$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $\Delta\eta_{\text{max}}^{jj}$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{1})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{1}^{\text{top}})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{2})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{2}^{\text{top}})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{3})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{1}^{\text{add}})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{4})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{2}^{\text{add}})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{1})|$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{1}^{\text{top}})|$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{2})|$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{2}^{\text{top}})|$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{3})|$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{1}^{\text{add}})|$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{4})|$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{2}^{\text{add}})|$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $m(b_{1}b_{2})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{1}b_{2})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $m(bb^{\text{top}})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(bb^{\text{top}})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $m(e\mu b_{1}b_{2})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $m(e\mu bb^{\text{top}})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $m(bb^{\text{min}\Delta R})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(bb^{\text{min}\Delta R})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $m(bb^{\text{add}})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(bb^{\text{add}})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $\text{min}\Delta R(bb)$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $\Delta R(b_{1}b_{2})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $N_{l/c-\text{jets}}$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $\Delta R(e\mu b_{1}b_{2},b_{3})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $\Delta R(e\mu bb^{\text{top}}, b_{1}^{\text{add}})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $\Delta R(e\mu bb^{\text{top}}, l/c\text{-jet}_{1})$ in the phase space with at least four b-jets and at least one $l/c$-jet. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(l/c\text{-jet}_{1}) - p_{\text{T}}(b_{1}^{\text{add}})$ in the phase space with at least four b-jets and at least one $l/c$-jet. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(l/c\text{-jet}_{1})|$ in the phase space with at least four b-jets and at least one $l/c$-jet. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(l/c\text{-jet}_{1})$ in the phase space with at least four b-jets and at least one $l/c$-jet. The overflow is included in the last bin.

Statistical correlation between bins in data for the differential cross sections for the production of W⁺ bosons as a function of the inclusive jet multiplicity.

Statistical correlation between bins in data for the differential cross sections for the production of W^- bosons as a function of the inclusive jet multiplicity.

Differential cross section for the production of W bosons as a function of H_T for events with N_jets &ge; 1.

Statistical correlation between bins in data for the differential cross section for the production of W bosons as a function of H_T for events with N_jets &ge; 1.

Differential cross sections for the production of W⁺ bosons, W^- bosons and the W⁺/W^- cross section ratio as a function of the H_T for events with N_jets &ge; 1.

Statistical correlation between bins in data for the differential cross sections for the production of W⁺ bosons as a function of the H_T for events with N_jets &ge; 1.

Statistical correlation between bins in data for the differential cross sections for the production of W^- bosons as a function of the H_T for events with N_jets &ge; 1.

Differential cross section for the production of W bosons as a function of the W p_T for events with N_jets &ge; 1.

Statistical correlation between bins in data for the differential cross section for the production of W bosons as a function of the W p_T for events with N_jets &ge; 1.

Differential cross sections for the production of W⁺ bosons, W^- bosons and the W⁺/W^- cross section ratio as a function of the W p_T for events with N_jets &ge; 1.

Statistical correlation between bins in data for the differential cross sections for the production of W⁺ bosons as a function of the W p_T for events with N_jets &ge; 1.

Statistical correlation between bins in data for the differential cross sections for the production of W^- bosons as a function of the W p_T for events with N_jets &ge; 1.

Differential cross section for the production of W bosons as a function of the leading jet p_T for events with N_jets &ge; 1.

Statistical correlation between bins in data for the differential cross section for the production of W bosons as a function of the leading jet p_T for events with N_jets &ge; 1.

Differential cross sections for the production of W⁺ bosons, W^- bosons and the W⁺/W^- cross section ratio as a function of the leading jet p_T for events with N_jets &ge; 1.

Statistical correlation between bins in data for the differential cross sections for the production of W⁺ bosons as a function of the leading jet p_T for events with N_jets &ge; 1.

Statistical correlation between bins in data for the differential cross sections for the production of W^- bosons as a function of the leading jet p_T for events with N_jets &ge; 1.

Differential cross section for the production of W bosons as a function of the leading jet rapidity for events with N_jets &ge; 1.

Statistical correlation between bins in data for the differential cross section for the production of W bosons as a function of the leading jet rapidity for events with N_jets &ge; 1.

Differential cross sections for the production of W⁺ bosons, W^- bosons and the W⁺/W^- cross section ratio as a function of the leading jet rapidity for events with N_jets &ge; 1.

Statistical correlation between bins in data for the differential cross sections for the production of W⁺ bosons as a function of the leading jet rapidity for events with N_jets &ge; 1.

Statistical correlation between bins in data for the differential cross sections for the production of W^- bosons as a function of the leading jet rapidity for events with N_jets &ge; 1.

Differential cross section for the production of W bosons as a function of second leading jet p_T for events with N_jets &ge; 2.

Statistical correlation between bins in data for the differential cross section for the production of W bosons as a function of second leading jet p_T for events with N_jets &ge; 2.

Differential cross section for the production of W bosons as a function of second leading jet rapidity for events with N_jets &ge; 2.

Statistical correlation between bins in data for the differential cross section for the production of W bosons as a function of second leading jet rapidity for events with N_jets &ge; 2.

Differential cross section for the production of W bosons as a function of &Delta; R_jet1,jet2 for events with N_jets &ge; 2.

Statistical correlation between bins in data for the differential cross section for the production of W bosons as a function of &Delta; R_jet1,jet2 for events with N_jets &ge; 2.

Differential cross section for the production of W bosons as a function of dijet invariant mass for events with N_jets &ge; 2.

Statistical correlation between bins in data for the differential cross section for the production of W bosons as a function of dijet invariant mass for events with N_jets &ge; 2.

Cross section for the production of W bosons as a function of exclusive jet multiplicity.

Statistical correlation between bins in data for the cross section for the production of W bosons as a function of exclusive jet multiplicity.

Differential cross section for the production of W bosons as a function of the H_T for events with N_jets &ge; 2.

Statistical correlation between bins in data for the differential cross section for the production of W bosons as a function of the H_T for events with N_jets &ge; 2.

Differential cross sections for the production of W⁺ bosons, W^- bosons and the W⁺/W^- cross section ratio as a function of the H_T for events with N_jets &ge; 2.

Statistical correlation between bins in data for the differential cross sections for the production of W⁺ bosons as a function of the H_T for events with N_jets &ge; 2.

Statistical correlation between bins in data for the differential cross sections for the production of W^- bosons as a function of the H_T for events with N_jets &ge; 2.

Differential cross section for the production of W bosons as a function of the W p_T for events with N_jets &ge; 2.

Statistical correlation between bins in data for the differential cross section for the production of W bosons as a function of the W p_T for events with N_jets &ge; 2.

Differential cross sections for the production of W⁺ bosons, W^- bosons and the W⁺/W^- cross section ratio as a function of the W p_T for events with N_jets &ge; 2.

Statistical correlation between bins in data for the differential cross sections for the production of W⁺ bosons as a function of the W p_T for events with N_jets &ge; 2.

Statistical correlation between bins in data for the differential cross sections for the production of W^- bosons as a function of the W p_T for events with N_jets &ge; 2.

Differential cross section for the production of W bosons as a function of the leading jet p_T for events with N_jets &ge; 2.

Statistical correlation between bins in data for the differential cross section for the production of W bosons as a function of the leading jet p_T for events with N_jets &ge; 2.

Differential cross sections for the production of W⁺ bosons, W^- bosons and the W⁺/W^- cross section ratio as a function of the leading jet p_T for events with N_jets &ge; 2.

Statistical correlation between bins in data for the differential cross sections for the production of W⁺ bosons as a function of the leading jet p_T for events with N_jets &ge; 2.

Statistical correlation between bins in data for the differential cross sections for the production of W^- bosons as a function of the leading jet p_T for events with N_jets &ge; 2.

Differential cross section for the production of W bosons as a function of the electron &eta; for events with N_jets &ge; 0.

Statistical correlation between bins in data for the differential cross section for the production of W bosons as a function of the electron &eta; for events with N_jets &ge; 0.

Differential cross sections for the production of W⁺ bosons, W^- bosons and the W⁺/W^- cross section ratio as a function of the electron &eta; for events with N_jets &ge; 0.

Statistical correlation between bins in data for the differential cross sections for the production of W⁺ bosons as a function of the electron &eta; for events with N_jets &ge; 0.

Statistical correlation between bins in data for the differential cross sections for the production of W^- bosons as a function of the electron &eta; for events with N_jets &ge; 0.

Differential cross section for the production of W bosons as a function of the electron &eta; for events with N_jets &ge; 1.

Statistical correlation between bins in data for the differential cross section for the production of W bosons as a function of the electron &eta; for events with N_jets &ge; 1.

Differential cross sections for the production of W⁺ bosons, W^- bosons and the W⁺/W^- cross section ratio as a function of the electron &eta; for events with N_jets &ge; 1.

Statistical correlation between bins in data for the differential cross sections for the production of W⁺ bosons as a function of the electron &eta; for events with N_jets &ge; 1.

Statistical correlation between bins in data for the differential cross sections for the production of W^- bosons as a function of the electron &eta; for events with N_jets &ge; 1.

List of experimentally considered systematic uncertainties for the W+jets cross section measurement

Non-perturbative corrections for the cross section for the production of W bosons for different inclusive jet multiplicities.

Non-perturbative corrections for the differential cross sections for the production of W⁺ bosons and W^- bosons as a function of the inclusive jet multiplicity.

Non-perturbative corrections for the differential cross section for the production of W bosons as a function of H_T for events with N_jets &ge; 1.

Non-perturbative corrections for the differential cross sections for the production of W⁺ bosons and W^- bosons as a function of the H_T for events with N_jets &ge; 1.

Non-perturbative corrections for the differential cross section for the production of W bosons as a function of the W p_T for events with N_jets &ge; 1.

Non-perturbative corrections for the differential cross sections for the production of W⁺ bosons and W^- bosons as a function of the W p_T for events with N_jets &ge; 1.

Non-perturbative corrections for the differential cross section for the production of W bosons as a function of the leading jet p_T for events with N_jets &ge; 1.

Non-perturbative corrections for the differential cross sections for the production of W⁺ bosons and W^- bosons as a function of the leading jet p_T for events with N_jets &ge; 1.

Non-perturbative corrections for the differential cross section for the production of W bosons as a function of the leading jet rapidity for events with N_jets &ge; 1.

Non-perturbative corrections for the differential cross sections for the production of W⁺ bosons and W^- bosons as a function of the leading jet rapidity for events with N_jets &ge; 1.

Non-perturbative corrections for the differential cross section for the production of W bosons as a function of second leading jet p_T for events with N_jets &ge; 2.

Non-perturbative corrections for the differential cross section for the production of W bosons as a function of second leading jet rapidity for events with N_jets &ge; 2.

Non-perturbative corrections for the differential cross section for the production of W bosons as a function of &Delta; R_jet1,jet2 for events with N_jets &ge; 2.

Non-perturbative corrections for the differential cross section for the production of W bosons as a function of dijet invariant mass for events with N_jets &ge; 2.

Non-perturbative corrections for the cross section for the production of W bosons as a function of exclusive jet multiplicity.

Non-perturbative corrections for the differential cross section for the production of W bosons as a function of the H_T for events with N_jets &ge; 2.

Non-perturbative corrections for the differential cross sections for the production of W⁺ bosons and W^- bosons as a function of the H_T for events with N_jets &ge; 2.

Non-perturbative corrections for the differential cross section for the production of W bosons as a function of the W p_T for events with N_jets &ge; 2.

Non-perturbative corrections for the differential cross sections for the production of W⁺ bosons and W^- bosons as a function of the W p_T for events with N_jets &ge; 2.

Non-perturbative corrections for the differential cross section for the production of W bosons as a function of the leading jet p_T for events with N_jets &ge; 2.

Non-perturbative corrections for the differential cross sections for the production of W⁺ bosons and W^- bosons as a function of the leading jet p_T for events with N_jets &ge; 2.

NNLO/NLO k-factors determined with NNLO Njetti for the differential cross sections for the production of W⁺ bosons and W^- bosons as a function of the H_T for events with N_jets &ge; 1. These numbers were obtained with code described in Phys. Rev. Lett. 115 (2015) 062002 [arXiv:1504.02131].

NNLO/NLO k-factors determined with NNLO Njetti for the differential cross sections for the production of W⁺ bosons and W^- bosons as a function of the W p_T for events with N_jets &ge; 1. These numbers were obtained with code described in Phys. Rev. Lett. 115 (2015) 062002 [arXiv:1504.02131].

NNLO/NLO k-factors determined with NNLO Njetti for the differential cross sections for the production of W⁺ bosons and W^- bosons as a function of the leading jet p_T for events with N_jets &ge; 1. These numbers were obtained with code described in Phys. Rev. Lett. 115 (2015) 062002 [arXiv:1504.02131].

NNLO/NLO k-factors determined with NNLO Njetti for the differential cross sections for the production of W⁺ bosons and W^- bosons as a function of the leading jet rapidity for events with N_jets &ge; 1. These numbers were obtained with code described in Phys. Rev. Lett. 115 (2015) 062002 [arXiv:1504.02131].