Transverse dilepton-$p_{T}^{miss}$ mass pre-fit distribution for selected events in SR2 of the di-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Dilepton mass pre-fit distribution for selected events in SR3 of the di-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Dilepton $p_T$ pre-fit distribution for selected events in SR3 of the di-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Dijet $p_T$ pre-fit distribution for selected events in the semi-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Lepton-dijet $p_T$ pre-fit distribution for selected events in the semi-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Maximum $p_T$ of the visible particles divided by the missing $p_T$, for selected events in the semi-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Pre-fit distribution of the $\Delta \phi$ angle between jets, for selected events in the semi-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Pre-fit distribution of the $\Delta \phi$ angle between the lepton and missing $p_T$, for selected events in the semi-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Pre-fit distribution of the $\Delta \phi$ angle between the lepton and the dijet system, for selected events in the semi-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Pre-fit distribution of the $\Delta R$ distance between the leptons, for selected events in the non-prompt validation region of the di-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Pre-fit distribution of the $\Delta \phi$ angle between the di-lepton system and the missing $p_T$, for selected events in the non-prompt validation region of the di-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Pre-fit distribution of the $\Delta \phi$ angle between the lepton and the di-jet system, for selected events in the non-prompt validation region of the semi-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Pre-fit distribution of the $\Delta \phi$ angle between the lepton-dijet system and the missing $p_T$, for selected events in the non-prompt validation region of the semi-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Leading lepton $p_T$ pre-fit distribution for selected events in the top control region of the di-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Trailing lepton $p_T$ pre-fit distribution for selected events in the top control region of the di-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Dilepton mass pre-fit distribution for selected events in the Drell-Yan control region of the di-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Missing $p_T$ pre-fit distribution for selected events in the Drell-Yan control region of the di-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Missing $p_T$ pre-fit distribution for selected events in the $WW$ control region of the di-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Dilepton $p_T$ pre-fit distribution for selected events in the $WW$ control region of the di-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Minimum $p_T$ of the visible particles divided by the missing $p_T$, for selected events in the top control region of the semi-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Pre-fit distribution of the $\Delta \phi$ angle between jets, for selected events in the top control region of the semi-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Pre-fit distribution of the $\Delta \phi$ angle between the lepton and missing $p_T$, for selected events in the $W$+jets control region of the semi-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Pre-fit distribution of the $\Delta \phi$ angle between the lepton and the dijet system, for selected events in the $W$+jets control region of the semi-leptonic channel for the full dataset. The error bars on the data points represent the statistical uncertainty of the data, and the error bars on the predicted yields represent the combined systematic and statistical uncertainty in each bin. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$. The last bin includes the overflow.

Unrolled $m_{ll}-m_{T}^{l min, p_{T}^{miss}}$ post-fit distributions in the di-leptonic channel in SR1 for the full data set. The histogram bins are spaced uniformly. Each group of five bins (from left to right) corresponds to $m_{T}^{l min, p_{T}^{miss}}$ distribution in a $m_{ll}$ region, placed in ascending order. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$.

Unrolled $m_{ll}-m_{T}^{l min, p_{T}^{miss}}$ post-fit distributions in the di-leptonic channel in SR2 for the full data set. The histogram bins are spaced uniformly. Each group of five bins (from left to right) corresponds to $m_{T}^{l min, p_{T}^{miss}}$ distribution in a $m_{ll}$ region, placed in ascending order. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$.

Unrolled $m_{ll}-m_{T}^{l min, p_{T}^{miss}}$ post-fit distributions in the di-leptonic channel in SR3 for the full data set. The histogram bins are spaced uniformly. Each group of five bins (from left to right) corresponds to $m_{T}^{l min, p_{T}^{miss}}$ distribution in a $m_{ll}$ region, placed in ascending order. The signal prediction represents the mass point: $m_s = 160 GeV, m_{\chi} = 100 GeV, m_{Z'} = 500 GeV$.

Post-fit BDT distributions in the semi-leptonic channel for the full data set in the top control region. The signal prediction represents the mass point: $m_{s} = 160$ GeV, $m_{\chi} = 100$ GeV, $m_{Z'} = 500$ GeV

Post-fit BDT distributions in the semi-leptonic channel for the full data set in the $W$+jets control region. The signal prediction represents the mass point: $m_{s} = 160$ GeV, $m_{\chi} = 100$ GeV, $m_{Z'} = 500$ GeV

Post-fit BDT distributions in the semi-leptonic channel in the 2016 signal region. The signal prediction represents the mass point: $m_{s} = 160$ GeV, $m_{\chi} = 100$ GeV, $m_{Z'} = 500$ GeV

Post-fit BDT distributions in the semi-leptonic channel in the 2017+2018 signal region. The signal prediction represents the mass point: $m_{s} = 160$ GeV, $m_{\chi} = 100$ GeV, $m_{Z'} = 500$ GeV

Contour of the 95% CL observed upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 100 GeV$.

Contour of the 95% CL expected + 2 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 100 GeV$.

Contour of the 95% CL expected + 1 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 100 GeV$.

Contour of the 95% CL expected upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 100 GeV$.

Contour of the 95% CL expected - 1 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 100 GeV$.

Contour of the 95% CL expected - 2 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 100 GeV$.

Contour of the 95% CL observed upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 150 GeV$.

Contour of the 95% CL expected + 2 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 150 GeV$.

Contour of the 95% CL expected + 1 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 150 GeV$.

Contour of the 95% CL expected upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 150 GeV$.

Contour of the 95% CL expected - 1 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 150 GeV$.

Contour of the 95% CL expected - 2 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 150 GeV$.

Contour of the 95% CL observed upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 200 GeV$.

Contour of the 95% CL expected + 2 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 200 GeV$.

Contour of the 95% CL expected + 1 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 200 GeV$.

Contour of the 95% CL expected upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 200 GeV$.

Contour of the 95% CL expected - 1 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 200 GeV$.

Contour of the 95% CL expected - 2 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 200 GeV$.

Contour of the 95% CL observed upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 300 GeV$.

Contour of the 95% CL expected + 2 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 300 GeV$.

Contour of the 95% CL expected + 1 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 300 GeV$.

Contour of the 95% CL expected upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 300 GeV$.

Contour of the 95% CL expected - 1 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 300 GeV$.

Contour of the 95% CL expected - 2 std. upper limits representing $\sigma / \sigma_{theory} = 1$ for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 300 GeV$.

The $\sigma / \sigma_{theory}$ 95% CL upper limit values for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 100 GeV$.

The $\sigma / \sigma_{theory}$ 95% CL upper limit values for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 150 GeV$.

The $\sigma / \sigma_{theory}$ 95% CL upper limit values for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 200 GeV$.

The $\sigma / \sigma_{theory}$ 95% CL upper limit values for the dark Higgs model in the ($m_{s}$, $m_{Z'}$) plane for $m_{\chi} = 300 GeV$.

The number of events in data and simulations after the fit to data in the Top$\gamma$ CR, SS$WW\gamma$ CR, and signal region.

The distributions of the invariant mass of the dilepton-photon system after the signal region selection before the fit to data.The shaded band represents the Monte Carlo statistical unc

Upper limits on the cross section and derived limits in terms of Yukawa coupling at 95% CL for Hγ production initiated by light quarks.

The distributions of the invariant mass of the transverse mass of the WW system after the signal region selection before the fit to data.The shaded band represents the Monte Carlo statistical unc

The distributions of the invariant mass of the dilepton-photon system after the signal region selection before the fit to data.The shaded band represents the Monte Carlo statistical unc

The unrolled two-dimensional mTWW-mll$\gamma$ distributions with category 0 jet after the fit to data. The data are compared to the sum of the signal and expected background. The black points with error bars represent the data and their statistical uncertainties, whereas the hatched bands represent the total uncertainties in the predictions.

The distributions of the invariant mass of the transverse mass of the WW system after the signal region selection before the fit to data.The shaded band represents the Monte Carlo statistical unc

The unrolled two-dimensional mTWW-mll$\gamma$ distributions with category 1more jets after the fit to data. The data are compared to the sum of the signal and expected background. The black points with error bars represent the data and their statistical uncertainties, whereas the hatched bands represent the total uncertainties in the predictions.

The unrolled two-dimensional mTWW-mll$\gamma$ distributions with category 0 jet after the fit to data. The data are compared to the sum of the signal and expected background. The black points with error bars represent the data and their statistical uncertainties, whereas the hatched bands represent the total uncertainties in the predictions.

The unrolled two-dimensional mTWW-mll$\gamma$ distributions with category 1more jets after the fit to data. The data are compared to the sum of the signal and expected background. The black points with error bars represent the data and their statistical uncertainties, whereas the hatched bands represent the total uncertainties in the predictions.

Covariance matrix of the two parameters $A$ and $m$ of the linear 2-to-5-jets-bin adjustment in the background Monte Carlo. Please see the text of the paper for an explanation of $A$ and $m$. Best fit values of $A$ and m are available as a separate table in this HEPData record.

Best fit values of the two parameters $A$ and $m$ of the linear 2-to-6-jets-bin adjustment in the background Monte Carlo. Please see the text of the paper for an explanation of $A$ and $m$. Uncertainties on $A$ and $m$ can be obtained from the covariance matrix of the fit, available as a separate table in this HEPData Record.

Covariance matrix of the two parameters $A$ and $m$ of the linear 2-to-6-jets-bin adjustment in the background Monte Carlo. Please see the text of the paper for an explanation of $A$ and $m$. Best fit values of $A$ and m are available as a separate table in this HEPData record.

This table contains the pre-fit background model (i.e. setting all nuisance parameters to 0), the post-fit background model (i.e. setting all nuisance parameters to their best fit values given the observed data), and the observed data in the 4 Jets bin. Uncertainties are provided, but per-bin uncertainties do not capture the correlations between bins with nuisance parameter variations. For a full analysis, the full covariance matrix between the search regions, also present in this HEPData record, should be used.

This table contains the pre-fit background model (i.e. setting all nuisance parameters to 0), the post-fit background model (i.e. setting all nuisance parameters to their best fit values given the observed data), and the observed data in the 5 Jets bin. Uncertainties are provided, but per-bin uncertainties do not capture the correlations between bins with nuisance parameter variations. For a full analysis, the full covariance matrix between the search regions, also present in this HEPData record, should be used.

This table contains the pre-fit background model (i.e. setting all nuisance parameters to 0), the post-fit background model (i.e. setting all nuisance parameters to their best fit values given the observed data), and the observed data in the $\geq 6$ Jets bin. Uncertainties are provided, but per-bin uncertainties do not capture the correlations between bins with nuisance parameter variations. For a full analysis, the full covariance matrix between the search regions, also present in this HEPData record, should be used.

Covariance matrix between search regions, estimated by toy MC runs, varying the nuisance parameters according to their covariance matrix before performing any fit. Note that the two columns ($S_T$ Bin (axis 1)) and ($N_{jets}$ Bin (axis 1)) together define the x-axis of the covariance, and the two columns ($S_T$ Bin (axis 2)) and ($N_{jets}$ Bin (axis 2)) together define the y-axis of the covariance.

Covariance matrix between search regions, estimated by toy MC runs, varying the nuisance parameters according to their covariance matrix in the background-only fit. Note that the two columns ($S_T$ Bin (axis 1)) and (NJets Bin (axis 1)) together define the x-axis of the covariance, and the two columns ($S_T$ Bin (axis 2)) and (NJets Bin (axis 2)) together define the y-axis of the covariance.

Scan through (gluino mass, neutralino mass) parameter-space. This table has the gluino and neutralino mass as the independent parameters, and the following as dependent parameters: 1. Expected upper limits (95% $CL_s$) on signal strength, with $\pm 1\sigma$ and $\pm 2\sigma$ uncertainty terms from limited statistics. 2. Observed upper limits (95% $CL_s$) on signal strength, with a $\pm 1\sigma$ uncertainty from the theoretical prediction of the gluino production cross section. 3. Observed upper limits (95% $CL_s$) on gluino production cross section.

Scan through (squark mass, neutralino mass) parameter-space. This table has the squark and neutralino mass as the independent parameters, and the following as dependent parameters: 1. Expected upper limits (95% $CL_s$) on signal strength, with $\pm 1\sigma$ and $\pm 2\sigma$ uncertainty terms from limited statistics. 2. Observed upper limits (95% $CL_s$) on signal strength, with a $\pm 1\sigma$ uncertainty from the theoretical prediction of the squark production cross section. 3. Observed upper limits (95% $CL_s$) on squark production cross section.

Comparison between the data and SM background predictions for the number of jets in the long track final state.

Comparison between the data and SM background predictions for the hard missing transverse momentum in the long track final state.

Comparison between the data and SM background predictions for the hard missing transverse momentum in the long track final state.

Comparison between the data and SM background predictions for the number of muons in the long track final state.

Comparison between the data and SM background predictions for the number of muons in the long track final state.

Comparison between the data and SM background predictions for the m_{DTk; stopping power} in the long track final state.

Comparison between the data and SM background predictions for the m_{DTk; stopping power} in the long track final state.

Comparison between the data and SM background predictions for the number of electrons in the long track final state.

Comparison between the data and SM background predictions for the number of electrons in the long track final state.

Comparison between the data and SM background predictions for the number of b-tagged jets in the short track final state.

Comparison between the data and SM background predictions for the number of b-tagged jets in the short track final state.

Comparison between the data and SM background predictions for the number of jets in the short track final state.

Comparison between the data and SM background predictions for the number of jets in the short track final state.

Comparison between the data and SM background predictions for the hard missing transverse momentum in the short track final state.

Comparison between the data and SM background predictions for the hard missing transverse momentum in the short track final state.

Comparison between the data and SM background predictions for the number of muons in the short track final state.

Comparison between the data and SM background predictions for the number of muons in the short track final state.

Comparison between the data and SM background predictions for the m_{DTk; stopping power} in the short track final state.

Comparison between the data and SM background predictions for the m_{DTk; stopping power} in the short track final state.

Comparison between the data and SM background predictions for the number of electrons in the short track final state.

Comparison between the data and SM background predictions for the number of electrons in the short track final state.

Comparison between the data and post-fit SM background predictions for the 49 search regions in the global search region.

Comparison between the data and post-fit SM background predictions for the 49 search regions in the global search region.

95% CL upper limit on the cross section in pb for the T6bt 10 cm model.

Expected 95% CL upper limit on the cross section in pb for the T6bt 10 cm model.

Limit in the mass plane of the T6bt 10 cm model

Observed cross 95% CL upper limit on the cross section in pb for the T6bt 10 cm model.

95% CL upper limit on the cross section in pb for the T6bt 200 cm model.

Limit in the mass plane of the T6bt 10 cm model

Limit in the mass plane of the T6bt 200 cm model

Expected 95% CL upper limit on the cross section in pb for the T6bt 200 cm model.

95% CL upper limit on the cross section in pb for the T6tb 10 cm model.

Observed cross 95% CL upper limit on the cross section in pb for the T6bt 200 cm model.

Limit in the mass plane of the T6tb 10 cm model

Limit in the mass plane of the T6bt 200 cm model

95% CL upper limit on the cross section in pb for the T6tb 200 cm model.

Expected 95% CL upper limit on the cross section in pb for the T6tb 10 cm model.

Limit in the mass plane of the T6tb 200 cm model

Observed cross 95% CL upper limit on the cross section in pb for the T6tb 10 cm model.

95% CL upper limit on the cross section in pb for the T5btbt 10 cm model.

Limit in the mass plane of the T6tb 10 cm model

Limit in the mass plane of the T5btbt 10 cm model

Expected 95% CL upper limit on the cross section in pb for the T6tb 200 cm model.

95% CL upper limit on the cross section in pb for the T5btbt 200 cm model.

Observed cross 95% CL upper limit on the cross section in pb for the T6tb 200 cm model.

Limit in the mass plane of the T5btbt 200 cm model

Limit in the mass plane of the T6tb 200 cm model

95% CL upper limit on the cross section in pb for the pure Wino model.

Expected 95% CL upper limit on the cross section in pb for the T5btbt 10 cm model.

Limit in the mass plane of the pure Wino model

Observed cross 95% CL upper limit on the cross section in pb for the T5btbt 10 cm model.

95% CL upper limit on the cross section in pb for the pure Higgsino model.

Limit in the mass plane of the T5btbt 10 cm model

Limit in the mass plane of the pure Higgsino model

Expected 95% CL upper limit on the cross section in pb for the T5btbt 200 cm model.

Cut flow table showing object-level efficiency at each stage of the track selection. The denominator of the efficiency is the number of chargino-matched tracks that have been reconstructed and satisfy the pT requirements, for which the chargino decays within the pixel detector volume; the numerator is the number of such tracks which also satisfy all requirements up to and including the associated criterion.

Observed cross 95% CL upper limit on the cross section in pb for the T5btbt 200 cm model.

Cut flow table showing object-level efficiency at each stage of the track selection. The denominator of the efficiency is the number of chargino-matched tracks that have been reconstructed and satisfy the pT requirements, for which the chargino decays within the strip detector volume; the numerator is the number of such tracks which also satisfy all requirements up to and including the associated criterion.

Limit in the mass plane of the T5btbt 200 cm model

Percent efficiencies for sum of all SR bins, each SR bin, SR bin groups:

Expected 95% CL upper limit on the cross section in pb for the pure Wino model.

Percent efficiencies for sum of all SR bins, each SR bin, SR bin groups:

Observed cross 95% CL upper limit on the cross section in pb for the pure Wino model.

Percent efficiencies for sum of all SR bins, each SR bin, SR bin groups:

Limit in the mass plane of the pure Wino model

Percent efficiencies for sum of all SR bins, each SR bin, SR bin groups:

Expected 95% CL upper limit on the cross section in pb for the pure Higgsino model.

Percent efficiencies for sum of all SR bins, each SR bin, SR bin groups:

Observed cross 95% CL upper limit on the cross section in pb for the pure Higgsino model.

Percent efficiencies for sum of all SR bins, each SR bin, SR bin groups:

Limit in the mass plane of the pure Higgsino model

Cut flow table showing object-level efficiency at each stage of the track selection. The denominator of the efficiency is the number of chargino-matched tracks that have been reconstructed and satisfy the pT requirements, for which the chargino decays within the pixel detector volume; the numerator is the number of such tracks which also satisfy all requirements up to and including the associated criterion.

Cut flow table showing object-level efficiency at each stage of the track selection. The denominator of the efficiency is the number of chargino-matched tracks that have been reconstructed and satisfy the pT requirements, for which the chargino decays within the strip detector volume; the numerator is the number of such tracks which also satisfy all requirements up to and including the associated criterion.

Percent efficiencies for sum of all SR bins, each SR bin, SR bin groups:

Percent efficiencies for sum of all SR bins, each SR bin, SR bin groups:pp -> chi1p-chi1m / chi10-chi1pmHiggsino model: ctau calculated as eq. 12 in arXiv:1703.09675.Individual events weighted according to the resulting decay lengths.

Percent efficiencies for sum of all SR bins, each SR bin, SR bin groups:

Percent efficiencies for sum of all SR bins, each SR bin, SR bin groups:

Percent efficiencies for sum of all SR bins, each SR bin, SR bin groups:pp -> chi1p-chi1m / chi10-chi1pmPure Wino model: ctau calculated as eq. 61 in arXiv:1410.4549.Individual events weighted according to the resulting decay lengths.

Percent efficiencies for sum of all SR bins, each SR bin, SR bin groups:

Percent efficiencies for sum of all SR bins, each SR bin, SR bin groups:pp -> chi20-chi1pm / chi1p-chi1m / chi10-chi1pm; dm(chi20 - chi10) = 2dm(chi1pm - chi10)Higgsino model: ctau calculated as eq. 12 in arXiv:1703.09675.Individual events weighted according to the resulting decay lengths.

Percent efficiencies for sum of all SR bins, each SR bin, SR bin groups:

Percent efficiencies for sum of all SR bins, each SR bin, SR bin groups:pp -> chi20-chi1pm / chi1p-chi1m / chi10-chi1pm; dm(chi20 - chi10) = 2dm(chi1pm - chi10)Pure Higgsino model: ctau calculated as eq. 12 in arXiv:1703.09675.Individual events weighted according to the resulting decay lengths.

Percent efficiencies for sum of all SR bins, each SR bin, SR bin groups:

Efficiency as a function of transverse (x-y) decay length of the chargino for short track selection in Run 2.

Efficiency as a function of transverse (x-y) decay length of the chargino for long track selection in Run 2.

Efficiency as a function of transverse (x-y) decay length of the chargino for combined track selection in Run 2.

Cut flow for model T2tb (m(~b)=1 TeV, m(~chi10)=900 GeV, c#tau=10 cm), showing events passing each cut stage.

Cut flow for model T1btbt (m(~g)=1.5 TeV, m(~chi10)=1.1 TeV, c#tau=200 cm), showing events passing each cut stage.

Cut flow for model T2tb (m(~b)=1 TeV, m(~chi10)=900 GeV, c#tau=200 cm), showing events passing each cut stage.

Cut flow for model T2tb (m(~b)=1 TeV, m(~chi10)=900 GeV, c#tau=200 cm), showing events passing each cut stage.

Cut flow for model T1btbt (m(~g)=1.5 TeV, m(~chi10)=1.1 TeV, c#tau=200 cm), showing events passing each cut stage.

Cut flow for model T1btbt (m(~g)=1.5 TeV, m(~chi10)=1.1 TeV, c#tau=10 cm), showing events passing each cut stage.

Cut flow for model T2tb (m(~b)=1 TeV, m(~chi10)=900 GeV, c#tau=10 cm), showing events passing each cut stage.

Cut flow for model T1btbt (m(~g)=1.5 TeV, m(~chi10)=1.1 TeV, c#tau=10 cm), showing events passing each cut stage.

Observed upper limits at 90% CL on the square of the kinetic mixing coefficient $\epsilon$ in the minimal model of a dark photon

Observed upper limits at 90% CL on the mixing angle $\theta_H$ for the type IV 2HDM+S scenario with fixed $tan\beta=0.5$

The combined efficiency of the dimuon scouting trigger and the MVA muon selection, averaged between 2017 and 2018, weighted by the integrated luminosity of each year. The trigger and selection efficiencies are also included in the table.

Theory cross-section times branching fraction to muons times acceptance for the dark photon and 2HDM+S models.

Normalized differential cross section of $p_{\mathrm{T}}(\mathrm{b}^{\mathrm{add.}}_{1})$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $|\eta(\mathrm{b}^{\mathrm{add.}}_{2})|$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $p_{\mathrm{T}}(\mathrm{b}^{\mathrm{add.}}_{2})$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $|\eta(\mathrm{b}\mathrm{b}^{\mathrm{add.}})|$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $\Delta\mathrm{R}(\mathrm{b}\mathrm{b}^{\mathrm{add.}})$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $\mathrm{m}(\mathrm{b}\mathrm{b}^{\mathrm{add.}})$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $p_{\mathrm{T}}(\mathrm{b}\mathrm{b}^{\mathrm{add.}})$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $\Delta\mathrm{R}_{\mathrm{b}\mathrm{b}}^{\mathrm{avg}}$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $|\eta(\mathrm{b}_{3})|$ in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space.

Normalized differential cross section of $|\eta(\mathrm{b}_{3})|$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $p_{\mathrm{T}}(\mathrm{b}_{3})$ in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space.

Normalized differential cross section of $p_{\mathrm{T}}(\mathrm{b}_{3})$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $|\eta(\mathrm{b}_{4})|$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $p_{\mathrm{T}}(\mathrm{b}_{4})$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $H^{\mathrm{b}}_{\mathrm{T}}$ in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space.

Normalized differential cross section of $H^{\mathrm{b}}_{\mathrm{T}}$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $|\Delta\phi(\mathrm{lj}^{\mathrm{extra}}_{1},\mathrm{b}_{\mathrm{soft}})|$ in $\geq 6$ jets: $\geq 3 \mathrm{b}$, $\geq 3$ light phase space.

Normalized differential cross section of $|\Delta\phi(\mathrm{lj}^{\mathrm{extra}}_{1},\mathrm{b}_{\mathrm{soft}})|$ in $\geq 7$ jets: $\geq 4 \mathrm{b}$, $\geq 3$ light phase space.

Normalized differential cross section of $|\eta(\mathrm{b}^{\mathrm{extra}}_{1})|$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $p_{\mathrm{T}}(\mathrm{b}^{\mathrm{extra}}_{1})$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $|\eta(\mathrm{b}^{\mathrm{extra}}_{2})|$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $p_{\mathrm{T}}(\mathrm{b}^{\mathrm{extra}}_{2})$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $|\eta(\mathrm{b}\mathrm{b}^{\mathrm{extra}})|$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $\Delta\mathrm{R}(\mathrm{b}\mathrm{b}^{\mathrm{extra}})$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $\mathrm{m}(\mathrm{b}\mathrm{b}^{\mathrm{extra}})$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $p_{\mathrm{T}}(\mathrm{b}\mathrm{b}^{\mathrm{extra}})$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $p_{\mathrm{T}}(\mathrm{lj}^{\mathrm{extra}}_{1})$ in $\geq 6$ jets: $\geq 3 \mathrm{b}$, $\geq 3$ light phase space.

Normalized differential cross section of $p_{\mathrm{T}}(\mathrm{lj}^{\mathrm{extra}}_{1})$ in $\geq 7$ jets: $\geq 4 \mathrm{b}$, $\geq 3$ light phase space.

Normalized differential cross section of $H^{\mathrm{j}}_{\mathrm{T}}$ in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space.

Normalized differential cross section of $H^{\mathrm{j}}_{\mathrm{T}}$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $\mathrm{m}_{\mathrm{b}\mathrm{b}}^{\mathrm{max}}$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $H^{\mathrm{light}}_{\mathrm{T}}$ in $\geq 6$ jets: $\geq 3 \mathrm{b}$, $\geq 3$ light phase space.

Normalized differential cross section of $H^{\mathrm{light}}_{\mathrm{T}}$ in $\geq 7$ jets: $\geq 4 \mathrm{b}$, $\geq 3$ light phase space.

Normalized differential cross section of $N_{\mathrm{jets}}$ in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space.

Normalized differential cross section of $N_{\mathrm{jets}}$ in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space.

Normalized differential cross section of $N_{\mathrm{b}}$ in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space.

Correlation of parameters of interest in fit of $|\eta(\mathrm{b}^{\mathrm{add.}}_{1})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $p_{\mathrm{T}}(\mathrm{b}^{\mathrm{add.}}_{1})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $|\eta(\mathrm{b}^{\mathrm{add.}}_{2})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $p_{\mathrm{T}}(\mathrm{b}^{\mathrm{add.}}_{2})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $|\eta(\mathrm{b}\mathrm{b}^{\mathrm{add.}})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $\Delta\mathrm{R}(\mathrm{b}\mathrm{b}^{\mathrm{add.}})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $\mathrm{m}(\mathrm{b}\mathrm{b}^{\mathrm{add.}})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $p_{\mathrm{T}}(\mathrm{b}\mathrm{b}^{\mathrm{add.}})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $\Delta\mathrm{R}_{\mathrm{b}\mathrm{b}}^{\mathrm{avg}}$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $|\eta(\mathrm{b}_{3})|$ observable in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $|\eta(\mathrm{b}_{3})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $p_{\mathrm{T}}(\mathrm{b}_{3})$ observable in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $p_{\mathrm{T}}(\mathrm{b}_{3})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $|\eta(\mathrm{b}_{4})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $p_{\mathrm{T}}(\mathrm{b}_{4})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $H^{\mathrm{b}}_{\mathrm{T}}$ observable in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $H^{\mathrm{b}}_{\mathrm{T}}$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $|\Delta\phi(\mathrm{lj}^{\mathrm{extra}}_{1},\mathrm{b}_{\mathrm{soft}})|$ observable in $\geq 6$ jets: $\geq 3 \mathrm{b}$, $\geq 3$ light phase space

Correlation of parameters of interest in fit of $|\Delta\phi(\mathrm{lj}^{\mathrm{extra}}_{1},\mathrm{b}_{\mathrm{soft}})|$ observable in $\geq 7$ jets: $\geq 4 \mathrm{b}$, $\geq 3$ light phase space

Correlation of parameters of interest in fit of $|\eta(\mathrm{b}^{\mathrm{extra}}_{1})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $p_{\mathrm{T}}(\mathrm{b}^{\mathrm{extra}}_{1})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $|\eta(\mathrm{b}^{\mathrm{extra}}_{2})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $p_{\mathrm{T}}(\mathrm{b}^{\mathrm{extra}}_{2})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $|\eta(\mathrm{b}\mathrm{b}^{\mathrm{extra}})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $\Delta\mathrm{R}(\mathrm{b}\mathrm{b}^{\mathrm{extra}})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $\mathrm{m}(\mathrm{b}\mathrm{b}^{\mathrm{extra}})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $p_{\mathrm{T}}(\mathrm{b}\mathrm{b}^{\mathrm{extra}})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $p_{\mathrm{T}}(\mathrm{lj}^{\mathrm{extra}}_{1})$ observable in $\geq 6$ jets: $\geq 3 \mathrm{b}$, $\geq 3$ light phase space

Correlation of parameters of interest in fit of $p_{\mathrm{T}}(\mathrm{lj}^{\mathrm{extra}}_{1})$ observable in $\geq 7$ jets: $\geq 4 \mathrm{b}$, $\geq 3$ light phase space

Correlation of parameters of interest in fit of $H^{\mathrm{j}}_{\mathrm{T}}$ observable in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $H^{\mathrm{j}}_{\mathrm{T}}$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $\mathrm{m}_{\mathrm{b}\mathrm{b}}^{\mathrm{max}}$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $H^{\mathrm{light}}_{\mathrm{T}}$ observable in $\geq 6$ jets: $\geq 3 \mathrm{b}$, $\geq 3$ light phase space

Correlation of parameters of interest in fit of $H^{\mathrm{light}}_{\mathrm{T}}$ observable in $\geq 7$ jets: $\geq 4 \mathrm{b}$, $\geq 3$ light phase space

Correlation of parameters of interest in fit of $N_{\mathrm{jets}}$ observable in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $N_{\mathrm{jets}}$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Correlation of parameters of interest in fit of $N_{\mathrm{b}}$ observable in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $|\eta(\mathrm{b}^{\mathrm{add.}}_{1})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $p_{\mathrm{T}}(\mathrm{b}^{\mathrm{add.}}_{1})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $|\eta(\mathrm{b}^{\mathrm{add.}}_{2})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $p_{\mathrm{T}}(\mathrm{b}^{\mathrm{add.}}_{2})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $|\eta(\mathrm{b}\mathrm{b}^{\mathrm{add.}})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $\Delta\mathrm{R}(\mathrm{b}\mathrm{b}^{\mathrm{add.}})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $\mathrm{m}(\mathrm{b}\mathrm{b}^{\mathrm{add.}})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $p_{\mathrm{T}}(\mathrm{b}\mathrm{b}^{\mathrm{add.}})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $\Delta\mathrm{R}_{\mathrm{b}\mathrm{b}}^{\mathrm{avg}}$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $|\eta(\mathrm{b}_{3})|$ observable in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $|\eta(\mathrm{b}_{3})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $p_{\mathrm{T}}(\mathrm{b}_{3})$ observable in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $p_{\mathrm{T}}(\mathrm{b}_{3})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $|\eta(\mathrm{b}_{4})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $p_{\mathrm{T}}(\mathrm{b}_{4})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $H^{\mathrm{b}}_{\mathrm{T}}$ observable in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $H^{\mathrm{b}}_{\mathrm{T}}$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $|\Delta\phi(\mathrm{lj}^{\mathrm{extra}}_{1},\mathrm{b}_{\mathrm{soft}})|$ observable in $\geq 6$ jets: $\geq 3 \mathrm{b}$, $\geq 3$ light phase space

Covariances of all nuisance parameters and POIs in fit of $|\Delta\phi(\mathrm{lj}^{\mathrm{extra}}_{1},\mathrm{b}_{\mathrm{soft}})|$ observable in $\geq 7$ jets: $\geq 4 \mathrm{b}$, $\geq 3$ light phase space

Covariances of all nuisance parameters and POIs in fit of $|\eta(\mathrm{b}^{\mathrm{extra}}_{1})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $p_{\mathrm{T}}(\mathrm{b}^{\mathrm{extra}}_{1})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $|\eta(\mathrm{b}^{\mathrm{extra}}_{2})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $p_{\mathrm{T}}(\mathrm{b}^{\mathrm{extra}}_{2})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $|\eta(\mathrm{b}\mathrm{b}^{\mathrm{extra}})|$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $\Delta\mathrm{R}(\mathrm{b}\mathrm{b}^{\mathrm{extra}})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $\mathrm{m}(\mathrm{b}\mathrm{b}^{\mathrm{extra}})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $p_{\mathrm{T}}(\mathrm{b}\mathrm{b}^{\mathrm{extra}})$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $p_{\mathrm{T}}(\mathrm{lj}^{\mathrm{extra}}_{1})$ observable in $\geq 6$ jets: $\geq 3 \mathrm{b}$, $\geq 3$ light phase space

Covariances of all nuisance parameters and POIs in fit of $p_{\mathrm{T}}(\mathrm{lj}^{\mathrm{extra}}_{1})$ observable in $\geq 7$ jets: $\geq 4 \mathrm{b}$, $\geq 3$ light phase space

Covariances of all nuisance parameters and POIs in fit of $H^{\mathrm{j}}_{\mathrm{T}}$ observable in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $H^{\mathrm{j}}_{\mathrm{T}}$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $\mathrm{m}_{\mathrm{b}\mathrm{b}}^{\mathrm{max}}$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $H^{\mathrm{light}}_{\mathrm{T}}$ observable in $\geq 6$ jets: $\geq 3 \mathrm{b}$, $\geq 3$ light phase space

Covariances of all nuisance parameters and POIs in fit of $H^{\mathrm{light}}_{\mathrm{T}}$ observable in $\geq 7$ jets: $\geq 4 \mathrm{b}$, $\geq 3$ light phase space

Covariances of all nuisance parameters and POIs in fit of $N_{\mathrm{jets}}$ observable in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $N_{\mathrm{jets}}$ observable in $\geq 6$ jets: $\geq 4 \mathrm{b}$ phase space

Covariances of all nuisance parameters and POIs in fit of $N_{\mathrm{b}}$ observable in $\geq 5$ jets: $\geq 3 \mathrm{b}$ phase space

Fiducial cross sections from the measurements of all observables, compared to predictions from different ttbb simulation approaches. For each of the normalized differential measurements the fiducial cross section in the respective phase space is also determined. In the paper only one representative observable is quoted for each fiducial phase space, while here the measured cross section with the uncertainties from the fit to the respective observable is summarized.

Postfit distributions of $S_\mathrm{T}^\mathrm{MET}$ in the $\mathrm{e}\mu$ channel of the $\geq$1b category for the combined 2016-2018 data set after a simultaneous fit of the background and vector LQ signal to the data. The number of events in each bin are divided by the respective bin width. The last bin includes the overflow.

Postfit distributions of $S_\mathrm{T}^\mathrm{MET}$ in the $\ell\tau_\mathrm{h}$ channel of the 0b category for the combined 2016-2018 data set after a simultaneous fit of the background and vector LQ signal to the data. The number of events in each bin are divided by the respective bin width. The last bin includes the overflow.

Postfit distributions of $S_\mathrm{T}^\mathrm{MET}$ in the $\ell\tau_\mathrm{h}$ channel of the $\geq$1b category for the combined 2016-2018 data set after a simultaneous fit of the background and vector LQ signal to the data. The number of events in each bin are divided by the respective bin width. The last bin includes the overflow.

Postfit distributions of $S_\mathrm{T}^\mathrm{MET}$ in the $\tau_\mathrm{h}\tau_\mathrm{h}$ channel of the 0b category for the combined 2016-2018 data set after a simultaneous fit of the background and vector LQ signal to the data. The number of events in each bin are divided by the respective bin width. The last bin includes the overflow.

Postfit distributions of $S_\mathrm{T}^\mathrm{MET}$ in the $\tau_\mathrm{h}\tau_\mathrm{h}$ channel of the $\geq$1b category for the combined 2016-2018 data set after a simultaneous fit of the background and vector LQ signal to the data. The number of events in each bin are divided by the respective bin width. The last bin includes the overflow.

Postfit distributions of $\chi$ in the $\mathrm{e}\mu$ channel of the 0j, $400 < m_\mathrm{vis} < 600\,\mathrm{GeV}$ category for the combined 2016-2018 data set after a simultaneous fit of the background and vector LQ signal to the data. The number of events in each bin are divided by the respective bin width.

Postfit distributions of $\chi$ in the $\mathrm{e}\mu$ channel of the 0j, $m_\mathrm{vis} > 600\,\mathrm{GeV}$ category for the combined 2016-2018 data set after a simultaneous fit of the background and vector LQ signal to the data. The number of events in each bin are divided by the respective bin width.

Postfit distributions of $\chi$ in the $\ell\tau_\mathrm{h}$ channel of the 0j, $400 < m_\mathrm{vis} < 600\,\mathrm{GeV}$ category for the combined 2016-2018 data set after a simultaneous fit of the background and vector LQ signal to the data. The number of events in each bin are divided by the respective bin width.

Postfit distributions of $\chi$ in the $\ell\tau_\mathrm{h}$ channel of the 0j, $m_\mathrm{vis} > 600\,\mathrm{GeV}$ category for the combined 2016-2018 data set after a simultaneous fit of the background and vector LQ signal to the data. The number of events in each bin are divided by the respective bin width.

Postfit distributions of $\chi$ in the $\tau_\mathrm{h}\tau_\mathrm{h}$ channel of the 0j, $400 < m_\mathrm{vis} < 600\,\mathrm{GeV}$ category for the combined 2016-2018 data set after a simultaneous fit of the background and vector LQ signal to the data. The number of events in each bin are divided by the respective bin width.

Postfit distributions of $\chi$ in the $\tau_\mathrm{h}\tau_\mathrm{h}$ channel of the 0j, $m_\mathrm{vis} > 600\,\mathrm{GeV}$ category for the combined 2016-2018 data set after a simultaneous fit of the background and vector LQ signal to the data. The number of events in each bin are divided by the respective bin width.

Exclusion limits on the total cross section of a scalar LQ as a function of LQ mass under the assumption of exclusive LQ couplings to b quarks and $\tau$ leptons.

Exclusion limits on the total cross section of a vector LQ as a function of LQ mass under the assumption of exclusive LQ couplings to b quarks and $\tau$ leptons.

Exclusion limits on the mass of a scalar LQ as a function of the coupling strength $\lambda$ under the assumption of exclusive LQ couplings to b quarks and $\tau$ leptons.

Exclusion limits on the mass of a vector LQ as a function of the coupling strength $\lambda$ under the assumption of exclusive LQ couplings to b quarks and $\tau$ leptons.

Exclusion limits on the coupling strength $\lambda$ of a scalar LQ as a function of the LQ mass under the assumption of exclusive LQ couplings to b quarks and $\tau$ leptons.

Exclusion limits on the coupling strength $\lambda$ of a vector LQ as a function of the LQ mass under the assumption of exclusive LQ couplings to b quarks and $\tau$ leptons.

Observed and expected distributions of the collinear mass in the $\tau_\mathrm{h}$+jet no-btag category with the BDT requirements selecting the most signal-like events. The signal hypothesis corresponds to a scalar leptoquark coupled to u quarks and $\tau$ leptons with a coupling strength $\lambda$ equal to 1.5.

Observed and expected distributions of the collinear mass in the e+jet no-btag category with the BDT requirements selecting the most signal-like events. The signal hypothesis corresponds to a scalar leptoquark coupled to u quarks and $\tau$ leptons with a coupling strength $\lambda$ equal to 1.5.

Observed and expected distributions of the collinear mass in the $\mu$+jet no-btag category with the BDT requirements selecting the most signal-like events. The signal hypothesis corresponds to a scalar leptoquark coupled to u quarks and $\tau$ leptons with a coupling strength $\lambda$ equal to 1.5.

Expected and observed upper limits at 95% CL on the scalar lepton-induced LQ production cross section times branching fraction for a LQ coupled to b quarks and $\tau$ leptons, using $\lambda = 1.5$.

Expected and observed upper limits at 95% CL on the scalar lepton-induced LQ production cross section times branching fraction for a LQ coupled to light-flavor quarks and $\tau$ leptons, using $\lambda = 1.5$.

Expected upper limit at 95% CL on the coupling strength $\lambda$ of a scalar LQ to b quarks and $\tau$ leptons.

Expected upper limit at 95% CL on the coupling strength $\lambda$ of a scalar LQ to light-flavor quarks and $\tau$ leptons.

Observed and expected distributions of the collinear mass in the $\tau_\mathrm{h}$+jet btag category with the lowest BDT requirement. The signal hypothesis corresponds to a scalar leptoquark coupled to u quarks and $\tau$ leptons with a coupling strength $\lambda$ equal to 1.5.

Observed and expected distributions of the collinear mass in the e+jet btag category with the lowest BDT requirement. The signal hypothesis corresponds to a scalar leptoquark coupled to u quarks and $\tau$ leptons with a coupling strength $\lambda$ equal to 1.5.

Observed and expected distributions of the collinear mass in the $\mu$+jet btag category with the lowest BDT requirement. The signal hypothesis corresponds to a scalar leptoquark coupled to u quarks and $\tau$ leptons with a coupling strength $\lambda$ equal to 1.5.

Observed and expected distributions of the collinear mass in the $\tau_\mathrm{h}$+jet btag category with the intermediate BDT requirement. The signal hypothesis corresponds to a scalar leptoquark coupled to u quarks and $\tau$ leptons with a coupling strength $\lambda$ equal to 1.5.

Observed and expected distributions of the collinear mass in the e+jet btag category with intermediate BDT requirement. The signal hypothesis corresponds to a scalar leptoquark coupled to u quarks and $\tau$ leptons with a coupling strength $\lambda$ equal to 1.5.

Observed and expected distributions of the collinear mass in the $\mu$+jet btag category with intermediate BDT requirement. The signal hypothesis corresponds to a scalar leptoquark coupled to u quarks and $\tau$ leptons with a coupling strength $\lambda$ equal to 1.5.

Observed and expected distributions of the collinear mass in the $\tau_\mathrm{h}$+jet no-btag category with the lowest BDT requirement. The signal hypothesis corresponds to a scalar leptoquark coupled to u quarks and $\tau$ leptons with a coupling strength $\lambda$ equal to 1.5.

Observed and expected distributions of the collinear mass in the e+jet no-btag category with the lowest BDT requirement. The signal hypothesis corresponds to a scalar leptoquark coupled to u quarks and $\tau$ leptons with a coupling strength $\lambda$ equal to 1.5.

Observed and expected distributions of the collinear mass in the $\tau_\mathrm{h}$+jet btag category with the lowest BDT requirement. The signal hypothesis corresponds to a scalar leptoquark coupled to u quarks and $\tau$ leptons with a coupling strength $\lambda$ equal to 1.5.

Observed and expected distributions of the collinear mass in the $\tau_\mathrm{h}$+jet no-btag category with low BDT requirement. The signal hypothesis corresponds to a scalar leptoquark coupled to u quarks and $\tau$ leptons with a coupling strength $\lambda$ equal to 1.5.

Observed and expected distributions of the collinear mass in the e+jet no-btag category with low BDT requirement. The signal hypothesis corresponds to a scalar leptoquark coupled to u quarks and $\tau$ leptons with a coupling strength $\lambda$ equal to 1.5.

Observed and expected distributions of the collinear mass in the $\mu$+jet no-btag category with low BDT requirement. The signal hypothesis corresponds to a scalar leptoquark coupled to u quarks and $\tau$ leptons with a coupling strength $\lambda$ equal to 1.5.

Observed and expected distributions of the collinear mass in the $\tau_\mathrm{h}$+jet no-btag category with intermediate BDT requirement. The signal hypothesis corresponds to a scalar leptoquark coupled to u quarks and $\tau$ leptons with a coupling strength $\lambda$ equal to 1.5.

Observed and expected distributions of the collinear mass in the e+jet btag category with intermediate BDT requirement. The signal hypothesis corresponds to a scalar leptoquark coupled to u quarks and $\tau$ leptons with a coupling strength $\lambda$ equal to 1.5.

Observed and expected distributions of the collinear mass in the $\mu$+jet no-btag category with intermediate BDT requirement. The signal hypothesis corresponds to a scalar leptoquark coupled to u quarks and $\tau$ leptons with a coupling strength $\lambda$ equal to 1.5.

Expected and observed upper limits at 95% CL on the scalar lepton-induced LQ production cross section times branching fraction for a LQ coupled to b quarks and $\tau$ leptons, using $\lambda = 1.0$.

Expected and observed upper limits at 95% CL on the scalar lepton-induced LQ production cross section times branching fraction for a LQ coupled to b quarks and $\tau$ leptons, using $\lambda = 2.0$.

Expected and observed upper limits at 95% CL on the scalar lepton-induced LQ production cross section times branching fraction for a LQ coupled to b quarks and $\tau$ leptons, using $\lambda = 3.0$.

Expected and observed upper limits at 95% CL on the scalar lepton-induced LQ production cross section times branching fraction for a LQ coupled to light-flavor quarks and $\tau$ leptons, using $\lambda = 0.5$.

Expected and observed upper limits at 95% CL on the scalar lepton-induced LQ production cross section times branching fraction for a LQ coupled to light-flavor quarks and $\tau$ leptons, using $\lambda = 1.0$.

Expected and observed upper limits at 95% CL on the scalar lepton-induced LQ production cross section times branching fraction for a LQ coupled to light-flavor quarks and $\tau$ leptons, using $\lambda = 2.0$.

Observed and expected distributions of the jet multiplicity in the e+jet btag control region.

Observed and expected distributions of the jet multiplicity in the $\mu$+jet btag control region.