Observed (solid line) and expected (dashed line) 95\% CL limits on the product of the production cross section times the branching ratio of a narrow width spin-0 resonance $X$ produced via gluon-gluon initial states decaying to a $Z$ boson and a photon, $\sigma(pp\to X)\cdot\mathcal{B}(X\to Z\gamma)$, as a function of the resonance mass $m_{X}$. Observed (expected) results are derived from ensemble tests for $m_{X}>1850 (900)$~\GeV. The green and yellow solid bands correspond to the $\pm1\sigma$ and $\pm2\sigma$ intervals for the expected upper limits. The limits in the $m_{X}$ ranges from 220 GeV to 3400 GeV and are obtained from the combined $ee\gamma$ and $\mu\mu\gamma$ channels.

Observed (solid line) and expected (dashed line) 95\% CL limits on the product of the production cross section times the branching ratio of a narrow width spin-2 resonance $X$ produced via gluon-gluon initial states decaying to a $Z$ boson and a photon, $\sigma(pp\to X)\cdot\mathcal{B}(X\to Z\gamma)$, as a function of the resonance mass $m_{X}$. Observed (expected) results are derived from ensemble tests for $m_{X}>1850 (900)$~\GeV. The green and yellow solid bands correspond to the $\pm1\sigma$ and $\pm2\sigma$ intervals for the expected upper limit respectively. The limits in the $m_{X}$ ranges from 220 GeV to 3400 GeV and are obtained from the combined $ee\gamma$ and $\mu\mu\gamma$ channels..

Observed (solid line) and expected (dashed line) 95\% CL limits on the product of the production cross section times the branching ratio of a narrow width spin-2 resonance $X$ produced via $q\bar{q}$ initial states decaying to a $Z$ boson and a photon, $\sigma(pp\to X)\cdot\mathcal{B}(X\to Z\gamma)$, as a function of the resonance mass $m_{X}$. Observed (expected) results are derived from ensemble tests for $m_{X}>1850 (900)$~\GeV. The green and yellow solid bands correspond to the $\pm1\sigma$ and $\pm2\sigma$ intervals for the expected upper limit respectively. The limits in the $m_{X}$ ranges from 220 GeV to 3400 GeV and are obtained from the combined $ee\gamma$ and $\mu\mu\gamma$ channels.

Probability of finding at least one TAR jet, where the p_T-leading TAR jet passes the m_Wcand and D₂^β=1 requirements, as a function of m_s. The probability is determined in a sample of signal events with m_Z'=2100 GeV, with the preselections applied.

Probability of finding a W_had candidate reconstructed as a pair of R=0.4 PFlow jets, as a function of m_s. The probability is determined in a sample of signal events with m_Z'=500 GeV, with the preselections applied that do not pass the requirements of the merged category.

Probability of finding a W_had candidate reconstructed as a pair of R=0.4 PFlow jets, as a function of m_s. The probability is determined in a sample of signal events with m_Z'=1000 GeV, with the preselections applied that do not pass the requirements of the merged category.

Probability of finding a W_had candidate reconstructed as a pair of R=0.4 PFlow jets, as a function of m_s. The probability is determined in a sample of signal events with m_Z'=1700 GeV, with the preselections applied that do not pass the requirements of the merged category.

Probability of finding a W_had candidate reconstructed as a pair of R=0.4 PFlow jets, as a function of m_s. The probability is determined in a sample of signal events with m_Z'=2100 GeV, with the preselections applied that do not pass the requirements of the merged category.

Observed exclusion contour at 95% C.L. for the dark Higgs model in the (m_Z', m_s) plane for g_q=0.25, g_χ=1, m_χ=200 GeV, and sinθ=0.01.

Expected exclusion contour at 95% C.L. for the dark Higgs model in the (m_Z', m_s) plane for g_q=0.25, g_χ=1, m_χ=200 GeV, and sinθ=0.01.

Expected+1σ exclusion contour at 95% C.L. for the dark Higgs model in the (m_Z', m_s) plane for g_q=0.25, g_χ=1, m_χ=200 GeV, and sinθ=0.01.

Expected-1σ exclusion contour at 95% C.L. for the dark Higgs model in the (m_Z', m_s) plane for g_q=0.25, g_χ=1, m_χ=200 GeV, and sinθ=0.01.

Expected+2σ exclusion contour at 95% C.L. for the dark Higgs model in the (m_Z', m_s) plane for g_q=0.25, g_χ=1, m_χ=200 GeV, and sinθ=0.01.

Expected-2σ exclusion contour at 95% C.L. for the dark Higgs model in the (m_Z', m_s) plane for g_q=0.25, g_χ=1, m_χ=200 GeV, and sinθ=0.01.

Observed upper limits at 95% C.L. on σ(pp → s χχ) × B(s → W^± W^∓) for m_Z'=0.5 TeV as a function of m_s. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the σ(pp → s χχ) × B(s → W^± W^∓) process for m_Z'=0.5 TeV, shown in dashed blue.

Observed upper limits at 95% C.L. on σ(pp → s χχ) × B(s → W^± W^∓) for m_Z'=1 TeV as a function of m_s. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the σ(pp → s χχ) × B(s → W^± W^∓) process for m_Z'=1 TeV, shown in dashed blue.

Observed upper limits at 95% C.L. on σ(pp → s χχ) × B(s → W^± W^∓) for m_Z'=1.7 TeV as a function of m_s. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the σ(pp → s χχ) × B(s → W^± W^∓) process for m_Z'=1.7 TeV, shown in dashed blue.

Observed upper limits at 95% C.L. on σ(pp → s χχ) × B(s → W^± W^∓) for m_Z'=2.1 TeV as a function of m_s. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the σ(pp → s χχ) × B(s → W^± W^∓) process for m_Z'=2.1 TeV, shown in dashed blue.

Data overlaid on SM background yields stacked in each SR and CR category after the fit to data ('Post-fit'). The yields in the SR are broken down into their contributions to the individual bins. The maximum-likelihood estimators are set to the conditional values of the CR-only fit, and propagated to SR and CRs.

Dominant sources of uncertainty for three dark Higgs scenarios after the fit to data. The uncertainties are quantified in terms of their contribution to the fitted signal uncertainty that is expressed relative to the theory prediction. Three representative dark Higgs signal scenarios with g_q=0.25, g_χ=1.0, sinθ=0.01 and m_χ=200 GeV are considered, which are indicated using the (m_Z', m_s) format in units of GeV in the table columns.

Cumulative efficiencies in the merged category for three representative dark Higgs signal scenarios with g_q=0.25, g_χ=1.0, sinθ=0.01, m_Z' = 1 TeV, and m_χ=200 GeV considering s→W(ℓν)W(qq) decays only.

Cumulative efficiencies in the resolved category for three representative dark Higgs signal scenarios with g_q=0.25, g_χ=1.0, sinθ=0.01, m_Z' = 1 TeV, and m_χ=200 GeV considering s→W(ℓν)W(qq) decays only.

Theoretical cross section for &sigma;(pp &rarr; s&chi;&chi;) &times; B(s &rarr; W^&plusmn;W^&#8723;) for each of the dark Higgs signal points at m_Z′ ={300, 350, 400, 500, 750} GeV, with g_q = 0.25, g<sub>&chi; = 1.0, sin&theta; = 0.01, m_Z′ = 1 TeV , and m_&chi; = 200 GeV. Also shown are experimentally excluded cross sections of &sigma;(pp &rarr; s&chi;&chi;) &times; B(s &rarr; W^&plusmn;W^&#8723;) (Obs.) together with the expectations (Exp.) varied up and down by one standard deviation (&plusmn;1&sigma;).

Theoretical cross section for &sigma;(pp &rarr; s&chi;&chi;) &times; B(s &rarr; W^&plusmn;W^&#8723;) for each of the dark Higgs signal points at m_Z′ ={1000, 1700} GeV, with g_q = 0.25, g<sub>&chi; = 1.0, sin&theta; = 0.01, m_Z′ = 1 TeV , and m_&chi; = 200 GeV. Also shown are experimentally excluded cross sections of &sigma;(pp &rarr; s&chi;&chi;) &times; B(s &rarr; W^&plusmn;W^&#8723;) (Obs.) together with the expectations (Exp.) varied up and down by one standard deviation (&plusmn;1&sigma;).

Theoretical cross section for &sigma;(pp &rarr; s&chi;&chi;) &times; B(s &rarr; W^&plusmn;W^&#8723;) for each of the dark Higgs signal points at m_Z′ ={2100, 2500, 2900, 3300} GeV, with g_q = 0.25, g<sub>&chi; = 1.0, sin&theta; = 0.01, m_Z′ = 1 TeV , and m_&chi; = 200 GeV. Also shown are experimentally excluded cross sections of &sigma;(pp &rarr; s&chi;&chi;) &times; B(s &rarr; W^&plusmn;W^&#8723;) (Obs.) together with the expectations (Exp.) varied up and down by one standard deviation (&plusmn;1&sigma;).

Expected 95% CL exclusion contours in the $(m(W_{R}), m(N_{R}))$ plane in the muon channel for boosted.

Observed 95% CL exclusion contours for the assumption of Dirac type in the $(m(W_{R}), m(N_{R}))$ plane in the electron channel for boosted.

Expected 95% CL exclusion contours for the assumption of Dirac type in the $(m(W_{R}), m(N_{R}))$ plane in the electron channel for boosted.

Observed 95% CL exclusion contours for the assumpition of Dirac type in the $(m(W_{R}), m(N_{R}))$ plane in the muon channel for boosted.

Expected 95% CL exclusion contours for the assumption of Dirac type in the $(m(W_{R}), m(N_{R}))$ plane in the muon channel for boosted.

Observed 95% CL exclusion contours for the assumption of Majorana type in the $(m(W_{R}), m(N_{R}))$ plane in the electron channel for resolved.

Expected 95% CL exclusion contours for the assumption of Majorana type in the $(m(W_{R}), m(N_{R}))$ plane in the electron channel for resolved.

Observed 95% CL exclusion contours for the assumption of Majorana type in the $(m(W_{R}), m(N_{R}))$ plane in the muon channel for resolved.

Expected 95% CL exclusion contours for the assumption of Majorana type in the $(m(W_{R}), m(N_{R}))$ plane in the muon channel for resolved.

Observed 95% CL exclusion contours for the assumption of Dirac type in the $(m(W_{R}), m(N_{R}))$ plane in the electron channel for resolved.

Expected 95% CL exclusion contours for the assumption of Dirac type in the $(m(W_{R}), m(N_{R}))$ plane in the electron channel for resolved.

Observed 95% CL exclusion contours for the assumption of Dirac type in the $(m(W_{R}), m(N_{R}))$ plane in the muon channel for resolved.

Expected 95% CL exclusion contours for the assumption of Dirac type in the $(m(W_{R}), m(N_{R}))$ plane in the muon channel for resolved.

The $m_{eJ}$ distribution in the boosted one electron channel.

The $m_{eeJ}$ distribution in the boosted two electron channel.

The $m_{\mu\mu J}$ distribution in the boosted two muon channel.

The $m_{jj}$ distribution in the resolved electron channel.

The $m_{jj}$ distribution in the resolved muon channel.

The $m_{eejj}$ distribution in the resolved electron channel.

The $m_{\mu\mu jj}$ distribution in the resolved muon channel.

The $h_{T}$ distribution in the resolved electron channel.

The $h_{T}$ distribution in the resolved muon channel.

Acceptance $\times$ efficiency for bSR1e.

Acceptance $\times$ efficiency for bSR2e.

Acceptance $\times$ efficiency for bSR2mu.

Acceptance $\times$ efficiency for rSROS2e.

Acceptance $\times$ efficiency for rSROS2mu.

Acceptance $\times$ efficiency for rSRSS2e.

Acceptance $\times$ efficiency for rSRSS2mu.

Expected and observed 95% CL upper limits for $\sigma(pp\to W_{R})\times B(W_{R}\to eeqq)$ as a function of $m(W_{R})$ for the special case of $m(W_{R}) = 2\times m(N_{R})$. The theoretical cross section corresponds to either the Dirac or Majorana neutrino interpretation by ignoring the charge of the leptons.

Expected and observed 95% CL upper limits for $\sigma(pp\to W_{R})\times B(W_{R} \to \mu\mu qq)$ as a function of $m(W_{R})$ for the special case of $m(W_{R}) = 2\times m(N_{R})$. The theoretical cross section corresponds to either the Dirac or Majorana neutrino interpretation by ignoring the charge of the leptons.

Expected and observed 95% CL upper limits for $\sigma(pp\to W_{R})\times B(W_{R} \to eeqq)$ as a function of $m(W_{R})$ for the special case of $m(N_{R})=200$ GeV. The theoretical cross section corresponds to either the Dirac or Majorana neutrino interpretation by ignoring the charge of the leptons.

Expected and observed 95% CL upper limits for $\sigma(pp\to W_{R})\times B(W_{R} \to \mu \mu qq)$ as a function of $m(W_{R})$ for the special case of $m(N_{R})=200$ GeV. The theoretical cross section corresponds to either the Dirac or Majorana neutrino interpretation by ignoring the charge of the leptons.

Expected and observed 95% CL upper limits for $\sigma(pp \to W_{R}) \times B(W_{R} \to eeqq)$ as a function of $m(W_{R})$ for the Majorana neutrino interpretations for the special case of $m(W_{R}) = 2\times m(N_{R})$.

Expected and observed 95% CL upper limits for $\sigma(pp \to W_{R}) \times B(W_{R} \to \mu\mu qq)$ as a function of $m(W_{R})$ for the Majorana neutrino interpretations for the special case of $m(W_{R}) = 2 \times m(N_{R})$.

Expected and observed 95% CL upper limits for $\sigma(pp \to W_{R}) \times B(W_{R} \to eeqq)$ as a function of $m(W_{R})$ for the Dirac neutrino interpretations for the special case of $m(W_{R}) = 2 \times m(N_{R})$.

Expected and observed 95% CL upper limits for $\sigma(pp \to W_{R}) \times B(W_{R} \to \mu \mu qq)$ as a function of $m(W_{R})$ for the Dirac neutrino interpretations for the special case of $m(W_{R}) = 2 \times m(N_{R})$.

Expected CLs values in the High mA SR, mA vs ma signal grid.

Observed CLs values in the High mA SR, mA vs ma signal grid.

Expected CLs values in the Low mA SR, mA vs ma signal grid.

Observed CLs values in the High mA SR, mA vs ma signal grid.

CLs+b values in the Low mA SR, mA vs tanB signal grid.

CLs+b values in the High mA SR, mA vs ma signal grid.

CLs+b values in the Low mA SR, mA vs ma signal grid.

Cut flow of the 2HDM+a signal points, gluon–gluon fusion production, Low mA SR. tanB = 1, $sin\theta$ = 0.35. The first two entries in the tables are number of raw MC events, third entry is theoretical prediction, and all other lines include the correct weights. Note that during the generation Higgs boson’s branching ratio to taus has been set to 1. An additional factor of 0.0627 is used to account for that, starting from the ‘Initial’ entry.

Cut flow of the 2HDM+a signal points, gluon–gluon fusion production, High mA SR. tanB = 1, $sin\theta$ = 0.35. The first two entries in the tables are number of raw MC events, third entry is theoretical prediction, and all other lines include the correct weights. Note that during the generation Higgs boson’s branching ratio to taus has been set to 1. An additional factor of 0.0627 is used to account for that, starting from the ‘Initial’ entry.

Cut flow of the 2HDM+a signal points, bb annihilation production, Low mA SR. tanB = 1, $sin\theta$ = 0.35. The first two entries in the tables are number of raw MC events, third entry is theoretical prediction, and all other lines include the correct weights. Note that during the generation Higgs boson’s branching ratio to taus has been set to 1. An additional factor of 0.0627 is used to account for that, starting from the ‘Initial’ entry.

Cut flow of the 2HDM+a signal points, bb annihilation production, High mA SR. tanB = 1, $sin\theta$ = 0.35. The first two entries in the tables are number of raw MC events, third entry is theoretical prediction, and all other lines include the correct weights. Note that during the generation Higgs boson’s branching ratio to taus has been set to 1. An additional factor of 0.0627 is used to account for that, starting from the ‘Initial’ entry.

A comparison of the observed and expected yields in the four bins of the Low mA SR.

A comparison of the observed and expected yields in the two bins of the High mA SR.

Expected exclusion contours at 95% CL as a function of mA and ma.

Observed exclusion contours at 95% CL as a function of mA and ma.

Expected +- 1sigma exclusion contours at 95% CL as a function of mA and ma.

Expected exclusion contours at 95% CL as a function of mA and ma.

Observed exclusion contours at 95% CL as a function of mA and ma.

Expected +- 1sigma exclusion contours at 95% CL as a function of mA and ma.

Acceptance, High mA SR, mA vs tanB grid, 400-750 GeV, bb prod

Acceptance, High mA SR, mA vs tanB grid, >750 GeV, bb prod

Acceptance, Low mA SR, mA vs tanB grid, 100-250 GeV, bb prod

Acceptance, Low mA SR, mA vs tanB grid, 250-400 GeV, bb prod

Acceptance, Low mA SR, mA vs tanB grid, 400-550 GeV, bb prod

Acceptance, Low mA SR, mA vs tanB grid, >550 GeV, bb prod

Acceptance, High mA SR, mA vs ma grid, 400-750 GeV, bb prod

Acceptance, High mA SR, mA vs ma grid, >750 GeV, bb prod

Acceptance, Low mA SR, mA vs ma grid, 100-250 GeV, bb prod

Acceptance, Low mA SR, mA vs ma grid, 250-400 GeV, bb prod

Acceptance, Low mA SR, mA vs ma grid, 400-550 GeV, bb prod

Acceptance, Low mA SR, mA vs ma grid, >550 GeV, bb prod

Acceptance, High mA SR, mA vs tanB grid, 400-750 GeV, ggF prod

Acceptance, High mA SR, mA vs tanB grid, >750 GeV, ggF prod

Acceptance, Low mA SR, mA vs tanB grid, 100-250 GeV, ggF prod

Acceptance, Low mA SR, mA vs tanB grid, 250-400 GeV, ggF prod

Acceptance, Low mA SR, mA vs tanB grid, 400-550 GeV, ggF prod

Acceptance, Low mA SR, mA vs tanB grid, >550 GeV, ggF prod

Acceptance, High mA SR, mA vs ma grid, 400-750 GeV, ggF prod

Acceptance, High mA SR, mA vs ma grid, >750 GeV, ggF prod

Acceptance, Low mA SR, mA vs ma grid, 100-250 GeV, ggF prod

Acceptance, Low mA SR, mA vs ma grid, 250-400 GeV, ggF prod

Acceptance, Low mA SR, mA vs ma grid, 400-550 GeV, ggF prod

Acceptance, Low mA SR, mA vs ma grid, >550 GeV, ggF prod

Efficiency, High mA SR, mA vs tanB grid, 400-750 GeV, bb prod

Efficiency, High mA SR, mA vs tanB grid, >750 GeV, bb prod

Efficiency, Low mA SR, mA vs tanB grid, 100-250 GeV, bb prod

Efficiency, Low mA SR, mA vs tanB grid, 250-400 GeV, bb prod

Efficiency, Low mA SR, mA vs tanB grid, 400-550 GeV, bb prod

Efficiency, Low mA SR, mA vs tanB grid, >550 GeV, bb prod

Efficiency, High mA SR, mA vs ma grid, 400-750 GeV, bb prod

Efficiency, High mA SR, mA vs ma grid, >750 GeV, bb prod

Efficiency, Low mA SR, mA vs ma grid, 100-250 GeV, bb prod

Efficiency, Low mA SR, mA vs ma grid, 250-400 GeV, bb prod

Efficiency, Low mA SR, mA vs ma grid, 400-550 GeV, bb prod

Efficiency, Low mA SR, mA vs ma grid, >550 GeV, bb prod

Efficiency, High mA SR, mA vs tanB grid, 400-750 GeV, ggF prod

Efficiency, High mA SR, mA vs tanB grid, >750 GeV, ggF prod

Efficiency, Low mA SR, mA vs tanB grid, 100-250 GeV, ggF prod

Efficiency, Low mA SR, mA vs tanB grid, 250-400 GeV, ggF prod

Efficiency, Low mA SR, mA vs tanB grid, 400-550 GeV, ggF prod

Efficiency, Low mA SR, mA vs tanB grid, >550 GeV, ggF prod

Efficiency, High mA SR, mA vs ma grid, 400-750 GeV, ggF prod

Efficiency, High mA SR, mA vs ma grid, >750 GeV, ggF prod

Efficiency, Low mA SR, mA vs ma grid, 100-250 GeV, ggF prod

Efficiency, Low mA SR, mA vs ma grid, 250-400 GeV, ggF prod

Efficiency, Low mA SR, mA vs ma grid, 400-550 GeV, ggF prod

Efficiency, Low mA SR, mA vs ma grid, >550 GeV, ggF prod

Observed excluded cross-section at 95% CL for the WZ-mediated simplified model of wino $\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2}$ production from Fig 8(aux).

Expected exclusion limits at 95% CL for the WZ-mediated simplified model of wino $\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2}$ production.

Observed exclusion limits at 95% CL for the Wh-mediated simplified model of wino $\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2}$ production from from Fig 13(a) and from Fig 7 and Fig 10(aux).

Observed excluded cross-section at 95% CL for the Wh-mediated simplified model of wino $\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2}$ production from Fig 7(aux) and Fig 10(aux).

positive one $\sigma$ observed exclusion limits at 95% CL for the Wh-mediated simplified model of wino $\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2}$ production from from Fig 13(a) and from Fig 7 and Fig 10(aux).

negative one $\sigma$ observed exclusion limits at 95% CL for the Wh-mediated simplified model of wino $\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2}$ production from from Fig 13(a) and from Fig 7 and Fig 10(aux).

Expected exclusion limits at 95% CL for the Wh-mediated simplified model of wino $\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2}$ production.

Expected exclusion limits at 95% CL for the Wh-mediated simplified model of wino $\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2}$ production.

Expected exclusion limits at 95% CL for the Wh-mediated simplified model of wino $\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2}$ production.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region $SR^{bRPV}_{2l-SS}$. in a susy scenario where $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are produced in pairs and decay to all possible allowed bRPV decays. The masses of the superpartners involved in the process are set to $m(\tilde{\chi}^{0} _{1}/\tilde{\chi}^{0} _{2})$ = 200 GeV, tan$\beta$=5. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region $SR^{bRPV}_{3l}$. in a susy scenario where $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are produced in pairs and decay to all possible allowed bRPV decays. The masses of the superpartners involved in the process are set to $m(\tilde{\chi}^{0} _{1}/\tilde{\chi}^{0} _{2})$ = 200 GeV, tan$\beta$=5. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region $SR^{WZ}_{high-m_{T2}}$. The wino-like doublet pair ($\tilde{\chi}^{\pm} _{1} and \tilde{\chi}^{0} _{2}$) were produced and then decays into $bino-like \tilde{\chi}^{0} _{1}$ which is the lightest SUSY particle (LSP) accompanied by mass on-shell or mass off-shell W and Z bosons. The masses of the superpartners involved in the process are set to $m(\tilde{\chi}^{\pm} _{1}/\tilde{\chi}^{0} _{2})$ = 150 GeV, $m(\tilde{\chi}^{0} _{1})$ = 50 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region $SR^{WZ}_{low-m_{T2}}$. The wino-like doublet pair ($\tilde{\chi}^{\pm} _{1} and \tilde{\chi}^{0} _{2}$) were produced and then decays into $bino-like \tilde{\chi}^{0} _{1}$ which is the lightest SUSY particle (LSP) accompanied by mass on-shell or mass off-shell W and Z bosons. The masses of the superpartners involved in the process are set to $m(\tilde{\chi}^{\pm} _{1}/\tilde{\chi}^{0} _{2})$ = 150 GeV, $m(\tilde{\chi}^{0} _{1})$ = 50 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the low mass $SR^{RPV}_{2l1b}$, where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays. The masses of the superpartners involved in the process are set to $m(\tilde{\chi}^{0} _{1}/\tilde{\chi}^{0} _{2})$ = 200 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the medium mass $SR^{RPV}_{2l1b}$, where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays. The masses of the superpartners involved in the process are set to $m(\tilde{\chi}^{0} _{1}/\tilde{\chi}^{0} _{2})$ = 200 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the low mass $SR^{RPV}_{2l2b}$, where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays. The masses of the superpartners involved in the process are set to $m(\tilde{\chi}^{0} _{1}/\tilde{\chi}^{0} _{2})$ = 200 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the medium mass $SR^{RPV}_{2l2b}$, where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays. The masses of the superpartners involved in the process are set to $m(\tilde{\chi}^{0} _{1}/\tilde{\chi}^{0} _{2})$ = 200 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the high mass $SR^{RPV}_{2l2b}$, where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays. The masses of the superpartners involved in the process are set to $m(\tilde{\chi}^{0} _{1}/\tilde{\chi}^{0} _{2})$ = 200 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the low mass $SR^{RPV}_{2l3b}$, where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays. The masses of the superpartners involved in the process are set to $m(\tilde{\chi}^{0} _{1}/\tilde{\chi}^{0} _{2})$ = 200 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the medium mass $SR^{RPV}_{2l3b}$, where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays. The masses of the superpartners involved in the process are set to $m(\tilde{\chi}^{0} _{1}/\tilde{\chi}^{0} _{2})$ = 200 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the high mass $SR^{RPV}_{2l3b}$, where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays. The masses of the superpartners involved in the process are set to $m(\tilde{\chi}^{0} _{1}/\tilde{\chi}^{0} _{2})$ = 200 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the $SR^{Wh}_{low-m_{T2} }$. The wino-like doublet pair ($\tilde{\chi}^{\pm} _{1} and \tilde{\chi}^{0} _{2}$) were produced and then decays into $bino-like \tilde{\chi}^{0} _{1}$ which is the lightest SUSY particle (LSP) accompanied by mass on-shell or mass off-shell W and Higgs bosons. The masses of the superpartners involved in the process are set to $m(\tilde{\chi}^{\pm} _{1}/\tilde{\chi}^{0} _{2})$ = 300 GeV, $m(\tilde{\chi}^{0} _{1})$ = 100 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the $SR^{Wh}_{high-m_{T2} }$. The wino-like doublet pair ($\tilde{\chi}^{\pm} _{1} and \tilde{\chi}^{0} _{2}$) were produced and then decays into $bino-like \tilde{\chi}^{0} _{1}$ which is the lightest SUSY particle (LSP) accompanied by mass on-shell or mass off-shell W and Higgs bosons. The masses of the superpartners involved in the process are set to $m(\tilde{\chi}^{\pm} _{1}/\tilde{\chi}^{0} _{2})$ = 300 GeV, $m(\tilde{\chi}^{0} _{1})$ = 100 GeV. Only statistical uncertainties are shown.

Signal Hepdataeptance for $SR^{bRPV}_{2l-SS}$ signal region from Fig 13(a)(aux) in a SUSY scenario where $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are produced in pairs and decay to all possible allowed bRPV decays.

Signal Hepdataeptance for $SR^{bRPV}_{3l}$ signal region from Fig 13(b)(aux) in a SUSY scenario where $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are produced in pairs and decay to all possible allowed bRPV decays.

Signal acceptance for $SR^{WZ}_{high-m_{T2}}$ in a SUSY scenario where the wino-like doublet pair ($\tilde{\chi}^{\pm} _{1} and \tilde{\chi}^{0} _{2}$) were produced and then decays into $bino-like \tilde{\chi}^{0} _{1}$ which is the lightest SUSY particle (LSP) accompanied by mass on-shell or mass off-shell W and Z bosons.

Signal acceptance for $SR^{WZ}_{low-m_{T2}}$ in a SUSY scenario where the wino-like doublet pair ($\tilde{\chi}^{\pm} _{1} and \tilde{\chi}^{0} _{2}$) were produced and then decays into $bino-like \tilde{\chi}^{0} _{1}$ which is the lightest SUSY particle (LSP) accompanied by mass on-shell or mass off-shell W and Z bosons.

Signal acceptance for $SR^{RPV}_{2l1b}-L$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.

Signal acceptance for $SR^{RPV}_{2l1b}-M$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.

Signal acceptance for $SR^{RPV}_{2l2b}-L$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.

Signal acceptance for $SR^{RPV}_{2l2b}-M$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.

Signal acceptance for $SR^{RPV}_{2l2b}-H$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.

Signal acceptance for $SR^{RPV}_{2l3b}-L$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.

Signal acceptance for $SR^{RPV}_{2l3b}-M$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.

Signal acceptance for $SR^{RPV}_{2l3b}-H$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.

Signal efficiency for $SR^{bRPV}_{2l-SS}$ signal region in a SUSY scenario where $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are produced in pairs and decay to all possible allowed bRPV decays.

Signal efficiency for $SR^{bRPV}_{3l}$ signal region in a SUSY scenario where $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are produced in pairs and decay to all possible allowed bRPV decays.

Signal efficiency for $SR^{WZ}_{high-m_{T2}}$ in a SUSY scenario where the wino-like doublet pair ($\tilde{\chi}^{\pm} _{1} and \tilde{\chi}^{0} _{2}$) were produced and then decays into $bino-like \tilde{\chi}^{0} _{1}$ which is the lightest SUSY particle (LSP) accompanied by mass on-shell or mass off-shell W and Z bosons.

Signal efficiency for $SR^{WZ}_{low-m_{T2}}$ in a SUSY scenario where the wino-like doublet pair ($\tilde{\chi}^{\pm} _{1} and \tilde{\chi}^{0} _{2}$) were produced and then decays into $bino-like \tilde{\chi}^{0} _{1}$ which is the lightest SUSY particle (LSP) accompanied by mass on-shell or mass off-shell W and Z bosons.

Signal efficiency for $SR^{RPV}_{2l1b}-L$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.

Signal efficiency for $SR^{RPV}_{2l1b}-M$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.

Signal efficiency for $SR^{RPV}_{2l2b}-L$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.

Signal efficiency for $SR^{RPV}_{2l2b}-M$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.

Signal efficiency for $SR^{RPV}_{2l2b}-H$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.

Signal efficiency for $SR^{RPV}_{2l3b}-L$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.

Signal efficiency for $SR^{RPV}_{2l3b}-M$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.

Signal efficiency for $SR^{RPV}_{2l3b}-H$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.

Signal acceptance for $SR^{Wh}_{high-m_{T2} }$ signal region from Fig 11(a)(aux) in a SUSY scenario where direct production of a lightest $\tilde{\chi}^{\pm} _{1} and \tilde{\chi}^{0} _{2}$ , decay with 100% branching ratio to a final state with a same sign light lepton (e or $\mu$) pair and two lightest neutralino1, via the on-shell emission of SM W and Higgs bosons,

Signal acceptance for $SR^{Wh}_{low-m_{T2} }$ signal region from Fig 11(b)(aux) in a SUSY scenario where direct production of a lightest $\tilde{\chi}^{\pm} _{1} and \tilde{\chi}^{0} _{2}$ , decay with 100% branching ratio to a final state with a same sign light lepton (e or $\mu$) pair and two lightest neutralino1, via the on-shell emission of SM W and Higgs bosons,

Signal efficiency for $SR^{Wh}_{high-m_{T2} }$ signal region from Fig 15(a)(aux) in a SUSY scenario where direct production of a lightest $\tilde{\chi}^{\pm} _{1} and \tilde{\chi}^{0} _{2}$ , decay with 100% branching ratio to a final state with a same sign light lepton (e or $\mu$) pair and two lightest neutralino1, via the on-shell emission of SM W and Higgs bosons,

Signal efficiency for $SR^{Wh}_{low-m_{T2} }$ signal region from Fig 15(b)(aux) in a SUSY scenario where direct production of a lightest $\tilde{\chi}^{\pm} _{1} and \tilde{\chi}^{0} _{2}$ , decay with 100% branching ratio to a final state with a same sign light lepton (e or $\mu$) pair and two lightest neutralino1, via the on-shell emission of SM W and Higgs bosons,

Observed 95% X-section upper limits as a function of higgsino $\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{1}/\tilde{\chi}^{0}_{2}$ mass in the bilinear RPV model from Fig 14.

Observed 95% X-section upper limits as a function of higgsino $\tilde{\chi}^{0}_{1}/\tilde{\chi}^{0}_{2}$ mass in the UDD RPV model from Fig 18.

Observed 95% X-section upper limits as a function of wino $\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2}$ mass in the WZ-mediated simplified model of wino $\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2}$ production from Fig 9(aux).

N-1 distributions for $m_{T2}$ of observed data and expected background towards $SR^{WZ}_{high-m_{T2}}$ from publication's Figure 11(a) . The last bin is inclusive.

N-1 distributions for $m_{T2}$ of observed data and expected background towards $SR^{WZ}_{low-m_{T2}}$ from publication's Figure 11(b) . The last bin is inclusive.

N-1 distributions for $m_{T2}$ of observed data and expected background towards $SR^{bRPV}_{2l-SS}$ from publication's Figure 11(c) . The last bin is inclusive.

N-1 distributions for $m_{T2}$ of observed data and expected background towards $SR^{bRPV}_{3l}$ from publication's Figure 11(d) . The last bin is inclusive.

N-1 distributions for $\sum p^{b-jet}_{T}/\sum p^{jet}_{T}$ of observed data and expected background towards $SR^{RPV}_{2l1b}-L$ from publication's Figure 16(a) . The last bin is inclusive.

N-1 distributions for $\sum p^{b-jet}_{T}/\sum p^{jet}_{T}$ of observed data and expected background towards $SR^{RPV}_{2l2b}-M$ from publication's Figure 16(b) . The last bin is inclusive.

N-1 distributions for $\sum p^{b-jet}_{T}/\sum p^{jet}_{T}$ of observed data and expected background towards $SR^{RPV}_{2l3b}-H$ from publication's Figure 16(c) . The last bin is inclusive.

N-1 distribution for $E_{T}^{miss}$ in $SR^{Wh}_{high-m_{T2} }$ in ee channel

N-1 distribution for $E_{T}^{miss}$ in $SR^{Wh}_{high-m_{T2} }$ in e$\mu$ channel

N-1 distribution for $E_{T}^{miss}$ in $SR^{Wh}_{high-m_{T2} }$ in $\mu\mu$ channel

N-1 distribution for $\mathcal{S}(E_{T}^{miss})$ in $SR^{Wh}_{low-m_{T2} }$ in ee channel

N-1 distribution for $\mathcal{S}(E_{T}^{miss})$ in $SR^{Wh}_{low-m_{T2} }$ in e$\mu$ channel

N-1 distribution for $\mathcal{S}(E_{T}^{miss})$ in $SR^{Wh}_{low-m_{T2} }$ in $\mu\mu$ channel

Acceptance times efficiency for signal grid in merged two-prong signal region.

Acceptance times efficiency for signal grid in resolved two-prong signal region.

Acceptance times efficiency for signal grid in resolved two-prong signal region.

The obtained p-value from comparing data to background estimation across all bins, defined by windows in the X and Y particle masses, in the anomaly signal region.

The obtained p-value from comparing data to background estimation across all bins, defined by windows in the X and Y particle masses, in the anomaly signal region.

The expected 95% CL limits on the cross-section $\sigma(pp \rightarrow Y \rightarrow XH \rightarrow q\bar{q}b\bar{b}$) in pb in the two-dimensional space of $m_Y$ versus $m_X$, obtained from a simultaneous fit of both merged and resolved two-prong signal regions with all statistical and systematic uncertainties.

The expected 95% CL limits on the cross-section $\sigma(pp \rightarrow Y \rightarrow XH \rightarrow q\bar{q}b\bar{b}$) in pb in the two-dimensional space of $m_Y$ versus $m_X$, obtained from a simultaneous fit of both merged and resolved two-prong signal regions with all statistical and systematic uncertainties.

The observed 95% CL limits on the cross-section $\sigma(pp \rightarrow Y \rightarrow XH \rightarrow q\bar{q}b\bar{b}$) in pb in the two-dimensional space of $m_Y$ versus $m_X$, obtained from a simultaneous fit of both merged and resolved two-prong signal regions with all statistical and systematic uncertainties.

The observed 95% CL limits on the cross-section $\sigma(pp \rightarrow Y \rightarrow XH \rightarrow q\bar{q}b\bar{b}$) in pb in the two-dimensional space of $m_Y$ versus $m_X$, obtained from a simultaneous fit of both merged and resolved two-prong signal regions with all statistical and systematic uncertainties.

Distribution (events/100 GeV) of the reconstructed $m_{tb}$ for data and backgrounds in the 0-lepton channel's the signal region 3 after the background-only fit to data. The systematics uncertainty is shown for the post-fit background sum, including the background statistical uncertainty. The individual background components are obtained after the fit, too. There are also the pre-fit background sum and the expected signal distribution. The distribution of the $W^{\prime}$ boson signal for a mass of 3 TeV is normalised to the predicted cross-section. The last bin in each distribution includes overflow.

Distribution (events/100 GeV) of the reconstructed $m_{tb}$ for data and backgrounds in the 0-lepton channel's validation region before the fit to data. The systematics uncertainty is shown for the pre-fit background sum, including the background statistical uncertainty. The individual background components are obtained before the fit, too. There is also the expected signal distribution. The distribution of the $W^{\prime}$ boson signal for a mass of 3 TeV is normalised to the predicted cross-section. The last bin in each distribution includes overflow.

Reconstructed $m_{tb}$ distributions (events/50 GeV) for data and backgrounds in the 1-lepton channel's 2j1b signal region after the background-only fit to data. The systematics uncertainty is shown for the post-fit background sum, including the background statistical uncertainty. The individual background components are obtained after the fit, too. There are also the pre-fit background sum and the expected signal distribution. The distribution of the $W^{\prime}$ boson signal for a mass of 3 TeV is normalised to the predicted cross-section. The last bin in each distribution includes overflow.

Reconstructed $m_{tb}$ distributions (events/50 GeV) for data and backgrounds in the 1-lepton channel's 3j1b signal region after the background-only fit to data. The systematics uncertainty is shown for the post-fit background sum, including the background statistical uncertainty. The individual background components are obtained after the fit, too. There are also the pre-fit background sum and the expected signal distribution. The distribution of the $W^{\prime}$ boson signal for a mass of 3 TeV is normalised to the predicted cross-section. The last bin in each distribution includes overflow.

Reconstructed $m_{tb}$ distributions (events/50 GeV) for data and backgrounds in the 1-lepton channel's 2j2b signal region after the background-only fit to data. The systematics uncertainty is shown for the post-fit background sum, including the background statistical uncertainty. The individual background components are obtained after the fit, too. There are also the pre-fit background sum and the expected signal distribution. The distribution of the $W^{\prime}$ boson signal for a mass of 3 TeV is normalised to the predicted cross-section. The last bin in each distribution includes overflow.

Reconstructed $m_{tb}$ distributions (events/50 GeV) for data and backgrounds in the 1-lepton channel's 3j2b signal region after the background-only fit to data. The systematics uncertainty is shown for the post-fit background sum, including the background statistical uncertainty. The individual background components are obtained after the fit, too. There are also the pre-fit background sum and the expected signal distribution. The distribution of the $W^{\prime}$ boson signal for a mass of 3 TeV is normalised to the predicted cross-section. The last bin in each distribution includes overflow.

Reconstructed $m_{tb}$ distributions (events/50 GeV) for data and backgrounds in the 1-lepton channel's 2j1b control region after the background-only fit to data. The systematics uncertainty is shown for the post-fit background sum, including the background statistical uncertainty. The individual background components are obtained after the fit, too. There are also the pre-fit background sum and the expected signal distribution. The distribution of the $W^{\prime}$ boson signal for a mass of 3 TeV is normalised to the predicted cross-section. The last bin in each distribution includes overflow.

Reconstructed $m_{tb}$ distributions (events/50 GeV) for data and backgrounds in the 1-lepton channel's 3j1b control region after the background-only fit to data. The systematics uncertainty is shown for the post-fit background sum, including the background statistical uncertainty. The individual background components are obtained after the fit, too. There are also the pre-fit background sum and the expected signal distribution. The distribution of the $W^{\prime}$ boson signal for a mass of 3 TeV is normalised to the predicted cross-section. The last bin in each distribution includes overflow.

Reconstructed $m_{tb}$ distributions (events/50 GeV) for data and backgrounds in the 1-lepton channel's 2j1b validation region after the background-only fit to data. The systematics uncertainty is shown for the post-fit background sum, including the background statistical uncertainty. The individual background components are obtained after the fit, too. There are also the pre-fit background sum and the expected signal distribution. The distribution of the $W^{\prime}$ boson signal for a mass of 3 TeV is normalised to the predicted cross-section. The last bin in each distribution includes overflow.

Reconstructed $m_{tb}$ distributions (events/50 GeV) for data and backgrounds in the 1-lepton channel's 3j1b validation region after the background-only fit to data. The systematics uncertainty is shown for the post-fit background sum, including the background statistical uncertainty. The individual background components are obtained after the fit, too. There are also the pre-fit background sum and the expected signal distribution. The distribution of the $W^{\prime}$ boson signal for a mass of 3 TeV is normalised to the predicted cross-section. The last bin in each distribution includes overflow.

Observed and expected 95% CL limits on the cross-section times branching ratio for the production of a $W^{\prime}$ boson with decay to tb and left-handed couplings as a function of the mass of the $W^{\prime}$ boson and a coupling value of $g^{\prime}/g$=0.5. The observed and expected limits are derived using a linear interpolation between simulated signal mass hypotheses. The uncertainty on the theory prediction includes components from factorisation and renormalisation scales, PDFs, the strong coupling constant, and the top-quark mass.

Observed and expected 95% CL limits on the cross-section times branching ratio for the production of a $W^{\prime}$ boson with decay to tb and left-handed couplings as a function of the mass of the $W^{\prime}$ boson and a coupling value of $g^{\prime}/g$=1.0. The observed and expected limits are derived using a linear interpolation between simulated signal mass hypotheses. The uncertainty on the theory prediction includes components from factorisation and renormalisation scales, PDFs, the strong coupling constant, and the top-quark mass.

Observed and expected 95% CL limits on the cross-section times branching ratio for the production of a $W^{\prime}$ boson with decay to tb and left-handed couplings as a function of the mass of the $W^{\prime}$ boson and a coupling value of $g^{\prime}/g$=2.0. The observed and expected limits are derived using a linear interpolation between simulated signal mass hypotheses. The uncertainty on the theory prediction includes components from factorisation and renormalisation scales, PDFs, the strong coupling constant, and the top-quark mass.

Observed and expected 95% CL limits on the cross-section times branching ratio for the production of a $W^{\prime}$ boson with decay to tb and right-handed couplings as a function of the mass of the $W^{\prime}$ boson and a coupling value of $g^{\prime}/g$=0.5. The observed and expected limits are derived using a linear interpolation between simulated signal mass hypotheses. The uncertainty on the theory prediction includes components from factorisation and renormalisation scales, PDFs, the strong coupling constant, and the top-quark mass.

Observed and expected 95% CL limits on the cross-section times branching ratio for the production of a $W^{\prime}$ boson with decay to tb and right-handed couplings as a function of the mass of the $W^{\prime}$ boson and a coupling value of $g^{\prime}/g$=1.0. The observed and expected limits are derived using a linear interpolation between simulated signal mass hypotheses. The uncertainty on the theory prediction includes components from factorisation and renormalisation scales, PDFs, the strong coupling constant, and the top-quark mass.

Observed and expected 95% CL limits on the cross-section times branching ratio for the production of a $W^{\prime}$ boson with decay to tb and right-handed couplings as a function of the mass of the $W^{\prime}$ boson and a coupling value of $g^{\prime}/g$=2.0. The observed and expected limits are derived using a linear interpolation between simulated signal mass hypotheses. The uncertainty on the theory prediction includes components from factorisation and renormalisation scales, PDFs, the strong coupling constant, and the top-quark mass.

95% CL limits on the coupling value ($g^{\prime}/g$) and the $W^{\prime}$-boson mass for left-handed $W^{\prime}$-boson couplings. The area above the line is excluded.

95% CL limits on the coupling value ($g^{\prime}/g$) and the $W^{\prime}$-boson mass for right-handed $W^{\prime}$-boson couplings. The area above the line is excluded.

The product of fiducial acceptance and selection efficiency for the three signal regions of the 0-lepton channel as a function of the mass of the $W^{\prime}$ boson with left-handed chirality. The $W^{\prime}$ boson coupling strength is set to $g^{\prime}/g=1$.

The product of fiducial acceptance and selection efficiency for the three signal regions of the 0-lepton channel as a function of the mass of the $W^{\prime}$ boson with left-handed chirality. The $W^{\prime}$ boson coupling strength is set to $g^{\prime}/g=0.5$.

The product of fiducial acceptance and selection efficiency for the three signal regions of the 0-lepton channel as a function of the mass of the $W^{\prime}$ boson with left-handed chirality. The $W^{\prime}$ boson coupling strength is set to $g^{\prime}/g=2$.

The product of fiducial acceptance and selection efficiency for the four signal regions of the 1-lepton channel as a function of the mass of the $W^{\prime}$ boson with left-handed chirality. The $W^{\prime}$ boson coupling strength is set to $g^{\prime}/g=1$.

The product of fiducial acceptance and selection efficiency for the four signal regions of the 1-lepton channel as a function of the mass of the $W^{\prime}$ boson with left-handed chirality. The $W^{\prime}$ boson coupling strength is set to $g^{\prime}/g=0.5$.

The product of fiducial acceptance and selection efficiency for the four signal regions of the 1-lepton channel as a function of the mass of the $W^{\prime}$ boson with left-handed chirality. The $W^{\prime}$ boson coupling strength is set to $g^{\prime}/g=2$.

The product of fiducial acceptance and selection efficiency for the three signal regions of the 0-lepton channel as a function of the mass of the $W^{\prime}$ boson with right-handed chirality. The $W^{\prime}$ boson coupling strength is set to $g^{\prime}/g=1$.

The product of fiducial acceptance and selection efficiency for the three signal regions of the 0-lepton channel as a function of the mass of the $W^{\prime}$ boson with right-handed chirality. The $W^{\prime}$ boson coupling strength is set to $g^{\prime}/g=0.5$.

The product of fiducial acceptance and selection efficiency for the three signal regions of the 0-lepton channel as a function of the mass of the $W^{\prime}$ boson with right-handed chirality. The $W^{\prime}$ boson coupling strength is set to $g^{\prime}/g=2$.

The product of fiducial acceptance and selection efficiency for the four signal regions of the 1-lepton channel as a function of the mass of the $W^{\prime}$ boson with right-handed chirality. The $W^{\prime}$ boson coupling strength is set to $g^{\prime}/g=1$.

The product of fiducial acceptance and selection efficiency for the four signal regions of the 1-lepton channel as a function of the mass of the $W^{\prime}$ boson with right-handed chirality. The $W^{\prime}$ boson coupling strength is set to $g^{\prime}/g=0.5$.

The product of fiducial acceptance and selection efficiency for the four signal regions of the 1-lepton channel as a function of the mass of the $W^{\prime}$ boson with right-handed chirality. The $W^{\prime}$ boson coupling strength is set to $g^{\prime}/g=2$.

Cutflow for two representative signal samples used in this analysis. The excited tau mass $m_{\tau^\ast} = 2.75$ TeV and the contact interaction scale $\Lambda=10$ TeV. The LQ mass $m_\mathrm{LQ} = 1.3$ TeV. The event yields include all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.

Acceptance x efficiency of the $\tau^\ast$ signal SR selection

Acceptance x efficiency of the LQ signal SR selection

Distribution of ${E}_{T}^{miss}$ after the fit of the multijet backgrounds, in the electron channel, in the $t\bar{t}$ 3-jets VR, without applying the cut on ${E}_{T}^{miss}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.

Distribution of ${E}_{T}^{miss}$ after the fit of the multijet backgrounds, in the electron channel, in the $t\bar{t}$ 4-jets VR, without applying the cut on ${E}_{T}^{miss}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.

Distribution of $m_{T}^{W}$ after the fit of the multijet backgrounds, in the muon channel, in the signal region, without applying the cut on $m_{T}^{W}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.

Distribution of $m_{T}^{W}$ after the fit of the multijet backgrounds, in the muon channel, in the $W$+jets VR, without applying the cut on $m_{T}^{W}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.

Distribution of $m_{T}^{W}$ after the fit of the multijet backgrounds, in the muon channel, in the $t\bar{t}$ 3-jets VR, without applying the cut on $m_{T}^{W}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.

Distribution of $m_{T}^{W}$ after the fit of the multijet backgrounds, in the muon channel, in the $t\bar{t}$ 4-jets VR, without applying the cut on $m_{T}^{W}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.

Expected distributions of the MEM discriminant $P(S|X)$ in the SR, for the s-channel single-top signal, and for the $t\bar{t}$ and $W$+jets backgrounds, for MEM discriminant values larger than $2.0\times10^{-4}$. Each distribution is normalised to unity. The binning is the same as the optimised binning used in the signal extraction fit, resulting in a non-linear horizontal scale.

Distribution of the MEM discriminant $P(S|X)$ in the $W$+jets VR. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit presented in Section 5 in the paper. The uncertainty band indicates the simulation's statistical uncertainty and the normalisation uncertainties for the various processes in each bin, summed in quadrature. The ratio of the observed number to the predicted number of events in each bin is shown in the lower panel of the figure, with different vertical axis ranges. The binning is the same as the optimised binning used in the signal extraction fit described in Section 8 in the paper, resulting in a non-linear horizontal scale.

Distribution of the MEM discriminant $P(S|X)$ in the $t\bar{t}$ 3-jets VR. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit presented in Section 5 in the paper. The uncertainty band indicates the simulation's statistical uncertainty and the normalisation uncertainties for the various processes in each bin, summed in quadrature. The ratio of the observed number to the predicted number of events in each bin is shown in the lower panel of the figure, with different vertical axis ranges. The binning is the same as the optimised binning used in the signal extraction fit described in Section 8 in the paper, resulting in a non-linear horizontal scale.

Distribution of the MEM discriminant $P(S|X)$ in the $t\bar{t}$ 4-jets VR. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit presented in Section 5 in the paper. The uncertainty bands indicate the simulation's statistical uncertainty and the normalisation uncertainties for the various processes in each bin, summed in quadrature. The ratio of the observed number to the predicted number of events in each bin is shown in the lower panel of the figure, with different vertical axis ranges. The binning is the same as the optimised binning used in the signal extraction fit described in Section 8 in the paper, resulting in a non-linear horizontal scale.

Distribution of the MEM discriminant $P(S|X)$ in the SR before the fit to data, for MEM discriminant values larger than $2.0\times10^{-4}$. The lower panel of the figure shows the ratio of the data to the prediction, with different vertical axis ranges. The uncertainty band indicates the total uncertainties and their correlations in each bin. The uncertainties in the $t\bar{t}$ and $W$+jets normalisation factors, as well as in the s-channel signal cross-section, are not defined pre-fit and therefore not included. The binning is the same as the optimised binning used in the fit, resulting in a non-linear horizontal scale.

Distribution of the MEM discriminant $P(S|X)$ in the SR after the fit to data, for MEM discriminant values larger than $2.0\times10^{-4}$. The lower panel of the figure shows the ratio of the data to the prediction, with different vertical axis ranges. The uncertainty band indicates the total uncertainties and their correlations in each bin. The binning is the same as the optimised binning used in the fit, resulting in a non-linear horizontal scale.

Distribution of the MEM discriminant $P(S|X)$ in the SR after the fit to data, for MEM discriminant values larger than $2.0\times10^{-4}$, after subtraction of all backgrounds. The fitted distribution for the simulation of the signal is shown together with the post-fit uncertainty in the backgrounds. The binning is the same as the optimised binning used in the fit, resulting in a non-linear horizontal scale.

Pre-fit and post-fit event yields in the SR, for MEM discriminant values larger than $2.0\times10^{-4}$. The central value of the event yield for each process is calculated by summing the values of the discriminant bin contents, using the nominal expected yield for the pre-fit value, and the best-fit estimate for the post-fit value. The error includes statistical and systematic uncertainties summed in quadrature. All sources of systematic uncertainties are included, taking into account correlations and anti-correlations in the post-fit case. The uncertainties in the $t\bar{t}$ and $W$+jets normalisation factors, as well as in the s-channel signal cross-section, are not defined pre-fit and therefore only included in the post-fit uncertainties.

Observed impact of the different sources of uncertainty on the measured s-channel signal cross-section, grouped by categories. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root. The 'Systematic uncertainties' category combines all sources of systematic uncertainties. The statistical uncertainty is obtained by repeating the fit after having fixed all nuisance parameters, including the $t\bar{t}$ and $W$+jets normalisation factors. 'Total' gives the total uncertainty on the measurement.

Observed impact of the different sources of $t\bar{t}$ modelling uncertainty on the measured s-channel signal cross-section. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root. 'PS & had.' refers to the parton shower and hadronisation model, and 'ME/PS matching' to the matching of the ME to the parton shower.

Observed impact of the different sources of s-channel modelling uncertainty on the measured s-channel signal cross-section. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root. 'PS & had.' refers to the parton shower and hadronisation model, as described in Section 7 in the paper.

Observed impact of the different sources of t-channel modelling uncertainty on the measured s-channel signal cross-section. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root. 'PS & had.' refers to the parton shower and hadronisation model, as described in Section 7 in the paper.

Observed impact of the different sources of $tW$ modelling uncertainty on the measured s-channel signal cross-section, grouped by categories. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root. 'PS & had.' refers to the parton shower and hadronisation model, and '$t\bar{t}$ overlap' to the algorithm removing the overlap between $tW$ and $t\bar{t}$ production at NLO, as described in Section 7 in the paper.

Observed impact of the different sources of PDF uncertainties on the measured s-channel signal cross-section, grouped by categories. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root.

Comparison between data and prediction after the fit to data in the signal region for the leading-jet $p_{T}$. The last bin includes the overflow. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Comparison between data and prediction after the fit to data in the signal region for the leading-jet $\eta$. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Comparison between data and prediction after the fit to data in the signal region for the subleading-jet $p_{T}$. The last bin includes the overflow. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Comparison between data and prediction after the fit to data in the signal region for the subleading-jet $\eta$. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Comparison between data and prediction after the fit to data in the signal region for the lepton $p_{T}$. The last bin includes the overflow. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Comparison between data and prediction after the fit to data in the signal region for the lepton $\eta$. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Comparison between data and prediction after the fit to data in the signal region for the ${E}_{T}^{miss}$. The last bin includes the overflow. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Comparison between data and prediction after the fit to data in the signal region for the $m_{T}^{W}$. The last bin includes the overflow. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Nuisance parameters ranked according to their post-fit impacts on the best-fit value of the ratio $\mu$ of the measured cross-section to the predicted cross-section. In the figure, only the 20 nuisance parameters with the largest post-fit impacts are shown. The empty (solid) blue rectangles illustrate the pre-fit (post-fit) impact on $\mu$, corresponding to the upper axis. The pre-fit (post-fit) impact of each nuisance parameter, $\Delta\mu$, is calculated as the difference in the fitted value of $\mu$ between the nominal fit and the fit when fixing the corresponding nuisance parameter to $\hat{\theta}\pm\Delta\theta$ ($\hat{\theta}\pm\Delta\hat{\theta}$), where $\hat{\theta}$ is the best-fit value of the nuisance parameter and $\Delta\theta$ ($\Delta\hat{\theta}$) is its pre-fit (post-fit) uncertainty. Several systematic uncertainties are split into different nuisance parameters, which are indicated by NP. JES (JER) indicates jet energy scale (resolution), and $\gamma$ indicates a nuisance parameter associated to the MC statistics in one of the 18 bins numbered from 0 to 17. The black points show the best-fit values of the nuisance parameters, with the error bars representing the post-fit uncertainties. Each nuisance parameter is shown wrt. its nominal value, $\theta_0$, and in units of its pre-fit uncertainty, except the free-floating normalisation factors of the $t\bar{t}$ and $W$+jets backgrounds, and the parameters associated to the MC statistics in each bin, for which the post-fit values and uncertainties are shown.

Correlation matrix of the nuisance parameters and of the ratio $\mu$ of the measured cross-section to the predicted cross-section. The correlations are given after the fit to data. In the figure, only the parameters which have a correlation of at least 0.2 with any other parameter are shown.

Distribution of the MEM discriminant $P(S|X)$ in the SR for MEM discriminant values larger than $2.0\times10^{-4}$, for the collision data used for the measurement, and for 1000 pseudo-data replicas, generated using a bootstrapping technique, in order to assess the statistical correlations between this measurement and others, for the purpose of combinations. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the <a href="https://zenodo.org/record/5361038">BootstrapGenerator</a> software package , which implements a technique described in <a href="https://cds.cern.ch/record/2759945/">ATL-PHYS-PUB-2021-011</a>. 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. Each pseudo-data replica is assigned an index, ranging from 0 to 999, corresponding to the random number index used consistently for each observed data event.

Measured values of the signal cross-section and of the $t\bar{t}$ and $W$+jets normalisation factors, obtained by statistical-only fits to the collision data used for the measurement, and to 1000 pseudo-data replicas, generated using a bootstrapping technique, in order to assess the statistical correlations between this measurement and others, for the purpose of combinations. The central values and their statistical uncertainties are obtained by repeating the fit after having fixed all nuisance parameters, except the $t\bar{t}$ and $W$+jets normalisation factors, which are let free-floating (unlike for the statistical uncertainty on the cross-section quoted in the paper). The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the <a href="https://zenodo.org/record/5361038">BootstrapGenerator</a> software package , which implements a technique described in <a href="https://cds.cern.ch/record/2759945/">ATL-PHYS-PUB-2021-011</a>. 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. Each pseudo-data replica is assigned an index, ranging from 0 to 999, corresponding to the random number index used consistently for each observed data event.

Observed 95% CL upper limits on the cross section for all masses and charges of photon-fusion pair-produced spin-1/2 monopoles as a function of mass for magnetic charges $|g|=1g_D$ and $|g|=2g_D$.

Observed 95% CL upper limits on the cross section for all masses and charges of Drell-Yan spin-0 HECOs production as a function of mass for various values of electric charge in the range $20\le|z|\le100$.

Observed 95% CL upper limits on the cross section for all masses and charges of Drell-Yan spin-1/2 HECOs production as a function of mass for various values of electric charge in the range $20\le|z|\le100$.

Observed 95% CL upper limits on the cross section for all masses and charges of photon-fusion pair-produced spin-0 HECOs as a function of mass for various values of electric charge in the range $20\le|z|\le100$.

Observed 95% CL upper limits on the cross section for all masses and charges of photon-fusion pair-produced spin-1/2 HECOs as a function of mass for various values of electric charge in the range $20\le|z|\le100$.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=1g_\textrm{D}$ monopoles of mass 200 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=1g_\textrm{D}$ monopoles of mass 500 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=1g_\textrm{D}$ monopoles of mass 1000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=1g_\textrm{D}$ monopoles of mass 1500 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=1g_\textrm{D}$ monopoles of mass 2000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=1g_\textrm{D}$ monopoles of mass 2500 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=1g_\textrm{D}$ monopoles of mass 3000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=1g_\textrm{D}$ monopoles of mass 4000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=2g_\textrm{D}$ monopoles of mass 200 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=2g_\textrm{D}$ monopoles of mass 500 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=2g_\textrm{D}$ monopoles of mass 1000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=2g_\textrm{D}$ monopoles of mass 1500 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=2g_\textrm{D}$ monopoles of mass 2000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=2g_\textrm{D}$ monopoles of mass 2500 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=2g_\textrm{D}$ monopoles of mass 3000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for $g=2g_\textrm{D}$ monopoles of mass 4000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=20$ of mass 200 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=20$ of mass 500 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=20$ of mass 1000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=20$ of mass 1500 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=20$ of mass 2000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=20$ of mass 2500 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=20$ of mass 3000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=20$ of mass 4000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=40$ of mass 200 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=40$ of mass 500 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=40$ of mass 1000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=40$ of mass 1500 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=40$ of mass 2000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=40$ of mass 2500 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=40$ of mass 3000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=40$ of mass 4000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=60$ of mass 200 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=60$ of mass 500 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=60$ of mass 1000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=60$ of mass 1500 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=60$ of mass 2000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=60$ of mass 2500 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=60$ of mass 3000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=60$ of mass 4000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=80$ of mass 200 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=80$ of mass 500 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=80$ of mass 1000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=80$ of mass 1500 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=80$ of mass 2000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=80$ of mass 2500 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=80$ of mass 3000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=80$ of mass 4000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=100$ of mass 200 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=100$ of mass 500 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=100$ of mass 1000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=100$ of mass 1500 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=100$ of mass 2000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=100$ of mass 2500 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=100$ of mass 3000 GeV.

Selection efficiency as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=100$ of mass 4000 GeV.

Expected, with the corresponding $\pm 1\sigma$ intervals, and observed 95% CL branching fraction upper limits for the Higgs and $Z$ boson decays into a quarkonium state and a photon. Standard Model production of the Higgs boson is assumed. The corresponding upper limits on the production cross section times branching fraction $\sigma\times\mathcal{B}$ are also shown.

$v(Q)$, for central events, as a function of the azimuthal coverage of the detector for data. (Angles in degrees.)

The effect on $v(Q)$ of varying the acceptance in $\varphi_r$. The solid curve shows the expectation from global charge conservation. The 10% most central events are used for data and RQMD. (Angles in degrees.)

The $M_{e_T}$ distributions for four different centrality classes. The curves are the random baseline mixed event distributions. The source of differences in the data and mixed event distributions are addressed in the text.

The residual distribution between the data and mixed event $M_{e_T}$ spectra as a function of $M_{e_T}$ in units of standard deviation. The total ${\chi}^2$ and the number of degrees of freedom for the $0-5\%$, $0-10\%$, $10-20\%$, $20-30\%$ centrality classes are 310.0/32, 896.4/36, 678.7/47, and 553.9/53, respectively. A large fraction of the residual contributions are due to the effects of cluster merging.

Ratio of the electron data to the calculated background as a function of $p_T$ in minimum bias collisions (upper panel) and relative contributions to the background from various sources (lower panel). The curves for $\omega$ and $\phi$ show the sum of the Dalitz and the di-electron decay modes.

The background-subtracted electron spectra for central (0-10%) collisions compared with the expected contributions from open charm decays. Also shown, for central collisions only, are the expected contribution from bottom decays (dashed) and the conversion electron spectrum from a direct phonon prediction (dotted).

The background-subtracted electron spectra for minimum bias (0-92%) collisions compared with the expected contributions from open charm decays. Also shown, for central collisions only, are the expected contribution from bottom decays (dashed) and the conversion electron spectrum from a direct phonon prediction (dotted).

Single electron cross sections $\frac{d\sigma_e}{dy}|_{y=0}$ of this measurement and ISR experiments [9,11,31] are displayed (bottom of figure, right-hand scale) with charm decay contributions calculated with PYTHIA. Open and filled symbols for 1.0 < $p_T$ < 1.4 GeV/$c$ and $p_T$ > 1.4 GeV/$c$, respectively. The derived charm cross section of this measurement is compared with charm cross sections from SPS/FNAL experiments (top of figure, left-hand scale). The thick curve and the shaded band represent the charm cross section in the PYTHIA model and in a NLO pQCD calculation [30], respectively.

Single electron cross sections $\frac{d\sigma_e}{dy}|_{y=0}$ of this measurement and ISR experiments [9,11,31] are displayed (bottom of figure, right-hand scale) with charm decay contributions calculated with PYTHIA. Open and filled symbols for 1.0 < $p_T$ < 1.4 GeV/$c$ and $p_T$ > 1.4 GeV/$c$, respectively. The derived charm cross section of this measurement is compared with charm cross sections from SPS/FNAL experiments (top of figure, left-hand scale). The thick curve and the shaded band represent the charm cross section in the PYTHIA model and in a NLO pQCD calculation [30], respectively.

Measured differential cross section with associated uncertainties as a function of $N$($b$-jets). Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate. For the meaning of the bins please refer to the figure.

Measured differential cross section with associated uncertainties as a function of $p_{T}^{j1}$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of $p_{T}^{\gamma\gamma} (N_\mathrm{jets}^{p_T>30\ \mathrm{GeV}}=0)$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of $m_{jj}$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of $\Delta\phi_{jj}$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of $p_{T}^{\gamma\gamma}$ in bins of $|y_{\gamma\gamma}|$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Measured differential cross section with associated uncertainties as a function of $\Delta\phi_{jj}$ in the VBF fiducial region. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Observed statistical correlations, evaluated with a bootstrapping technique, between $p_\mathrm{T}^{\gamma\gamma}$, $N_\mathrm{jets}$, $m_{jj}$, $\Delta\phi_{jj}$, and $p_\mathrm{T}^{j1}$

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{\gamma\gamma}$.

Post-fit correlation matrix for the differential cross section measured as a function of $N_\mathrm{jets}$.

Post-fit correlation matrix for the differential cross section measured as a function of $N$($b$-jets).

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{j1}$.

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{\gamma\gamma} (N_\mathrm{jets}^{p_T>30\ \mathrm{GeV}}=0)$.

Post-fit correlation matrix for the differential cross section measured as a function of $m_{jj}$.

Post-fit correlation matrix for the differential cross section measured as a function of $\Delta\phi_{jj}$.

Post-fit correlation matrix for the differential cross section measured as a function of $\Delta\phi_{jj}$ in the VBF fiducial region.

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{\gamma\gamma}$ in bins of $|y_{\gamma\gamma}|$. The bins are the same as in the corresponding plot of the differential cross section.

Measured differential cross section with associated uncertainties as a function of $p_{T}^{\gamma1}/m_{\gamma\gamma}$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{\gamma1}/m_{\gamma\gamma}$.

Measured differential cross section with associated uncertainties as a function of $p_{T}^{\gamma2}/m_{\gamma\gamma}$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{\gamma2}/m_{\gamma\gamma}$.

Measured differential cross section with associated uncertainties as a function of $|y_{\gamma\gamma}|$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $|y_{\gamma\gamma}|$.

Measured differential cross section with associated uncertainties as a function of $m_{\gamma\gamma j}$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $m_{\gamma\gamma j}$.

Measured differential cross section with associated uncertainties as a function of $p_{T}^{\gamma\gamma j}$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{\gamma\gamma j}$.

Measured differential cross section with associated uncertainties as a function of $H_{T}$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $H_{T}$.

Measured differential cross section with associated uncertainties as a function of $\tau_{C,j1}$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $\tau_{C,j1}$.

Measured differential cross section with associated uncertainties as a function of $\sum\tau_{C,j}$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $\sum\tau_{C,j}$.

Measured differential cross section with associated uncertainties as a function of $p_{T}^{\gamma\gamma} (N_\mathrm{jets}^{p_T>40\ \mathrm{GeV}}=0)$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{\gamma\gamma} (N_\mathrm{jets}^{p_T>40\ \mathrm{GeV}}=0)$.

Measured differential cross section with associated uncertainties as a function of $p_{T}^{\gamma\gamma} (N_\mathrm{jets}^{p_T>50\ \mathrm{GeV}}=0)$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{\gamma\gamma} (N_\mathrm{jets}^{p_T>50\ \mathrm{GeV}}=0)$.

Measured differential cross section with associated uncertainties as a function of $p_{T}^{\gamma\gamma} (N_\mathrm{jets}^{p_T>60\ \mathrm{GeV}}=0)$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{\gamma\gamma} (N_\mathrm{jets}^{p_T>60\ \mathrm{GeV}}=0)$.

Measured differential cross section with associated uncertainties as a function of $\pi - |\Delta\phi_{\gamma\gamma,jj}|$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $\pi - |\Delta\phi_{\gamma\gamma,jj}|$.

Measured differential cross section with associated uncertainties as a function of $p_{T}^{\gamma\gamma jj}$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{\gamma\gamma jj}$.

Measured differential cross section with associated uncertainties as a function of $p_{T}^{\gamma\gamma}$ in bins of $p_{T}^{\gamma\gamma j}$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{\gamma\gamma}$ in bins of $p_{T}^{\gamma\gamma j}$. The bins are the same as in the corresponding plot of the differential cross section.

Measured differential cross section with associated uncertainties as a function of $p_{T}^{\gamma\gamma}$ in bins of $\tau_{C,j1}$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{\gamma\gamma}$ in bins of $\tau_{C,j1}$. The bins are the same as in the corresponding plot of the differential cross section.

Measured differential cross section with associated uncertainties as a function of $(p_{T}^{\gamma1}-p_{T}^{\gamma2})/m_{\gamma\gamma}$ in bins of $(p_{T}^{\gamma1}+p_{T}^{\gamma2})/m_{\gamma\gamma}$. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $(p_{T}^{\gamma1}-p_{T}^{\gamma2})/m_{\gamma\gamma}$ in bins of $(p_{T}^{\gamma1}+p_{T}^{\gamma2})/m_{\gamma\gamma}$. The bins are the same as in the corresponding plot of the differential cross section.

Measured differential cross section with associated uncertainties as a function of $|\eta^*|$ in the VBF fiducial region. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $|\eta^*|$ in the VBF fiducial region.

Measured differential cross section with associated uncertainties as a function of $p_{T}^{\gamma\gamma jj}$ in the VBF fiducial region. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{\gamma\gamma jj}$ in the VBF fiducial region.

Measured differential cross section with associated uncertainties as a function of $p_{T}^{j1}$ in the VBF fiducial region. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{j1}$ in the VBF fiducial region.

Measured differential cross section with associated uncertainties as a function of $p_{T}^{j1}$ in bins of $\Delta\phi_{jj}$ in the VBF fiducial region. Each systematic uncertainty source is fully uncorrelated with the other sources and fully correlated across bins, except for the background modelling systematics for which an uncorrelated treatment across bins is more appropriate.

Post-fit correlation matrix for the differential cross section measured as a function of $p_{T}^{j1}$ in bins of $\Delta\phi_{jj}$ in the VBF fiducial region. The bins are the same as in the corresponding plot of the differential cross section.

Covariance matrix of the Absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $p_T^{t,h}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $p_T^{t,l}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $p_T^{t,l}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $m^{t\bar{t}}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $m^{t\bar{t}}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $y^{t,h}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $y^{t,h}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $y^{t,h}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $y^{t,l}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $y^{t,l}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $y^{t,l}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $y^{t\bar{t}}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $y^{t\bar{t}}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $y^{t\bar{t}}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $H_T^{t\bar{t}}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $H_T^{t\bar{t}}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $H_T^{t\bar{t}}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $p_T^{t\bar{t}}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $p_T^{t\bar{t}}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $p_T^{t\bar{t}}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $H_T^{t\bar{t}+jets}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $H_T^{t\bar{t}+jets}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $N^j$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $N^j$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $N^j$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $p_T^{j,1}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $p_T^{j,1}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $p_T^{j,1}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $m(j_1, t_h)$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $m(j_1, t_h)$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $m(j_1, t_h)$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $p_T^{j,2}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $p_T^{j,2}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $p_T^{j,2}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of $p_T^{j,1}$ vs $N^j$ at particle level in the boosted topology in $N^j$ = 1. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of $p_T^{j,1}$ vs $N^j$ at particle level in the boosted topology in $N^j$ = 2. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of $p_T^{j,1}$ vs $N^j$ at particle level in the boosted topology in $N^j$ $\geq$ 3. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of $p_T^{j,1}$ vs $N^j$ at particle level in the boosted topology in $N^j$ = 1. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of $p_T^{j,1}$ vs $N^j$ at particle level in the boosted topology in $N^j$ = 2. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of $p_T^{j,1}$ vs $N^j$ at particle level in the boosted topology in $N^j$ $\geq$ 3. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ = 1 and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ = 1 at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ = 2 and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ = 1 at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ = 2 and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ = 2 at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ $\geq$ 3 and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ = 1 at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ $\geq$ 3 and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ = 2 at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ $\geq$ 3 and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ $\geq$ 3 at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative double-differential cross-section as a function of $p_T^{j,1}$ vs $p_T^{t,h}$ at particle level in the boosted topology in 355.0 GeV < $p_T^{t,h}$ < 398.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of $p_T^{j,1}$ vs $p_T^{t,h}$ at particle level in the boosted topology in 398.0 GeV < $p_T^{t,h}$ < 496.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of $p_T^{j,1}$ vs $p_T^{t,h}$ at particle level in the boosted topology in 496.0 GeV < $p_T^{t,h}$ < 2000.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of $p_T^{j,1}$ vs $p_T^{t,h}$ at particle level in the boosted topology in 355.0 GeV < $p_T^{t,h}$ < 398.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of $p_T^{j,1}$ vs $p_T^{t,h}$ at particle level in the boosted topology in 398.0 GeV < $p_T^{t,h}$ < 496.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of $p_T^{j,1}$ vs $p_T^{t,h}$ at particle level in the boosted topology in 496.0 GeV < $p_T^{t,h}$ < 2000.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $p_T^{t,h}$ in 355.0 GeV < $p_T^{t,h}$ < 398.0 GeV and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $p_T^{t,h}$ in 355.0 GeV < $p_T^{t,h}$ < 398.0 GeV at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $p_T^{t,h}$ in 398.0 GeV < $p_T^{t,h}$ < 496.0 GeV and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $p_T^{t,h}$ in 355.0 GeV < $p_T^{t,h}$ < 398.0 GeV at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $p_T^{t,h}$ in 398.0 GeV < $p_T^{t,h}$ < 496.0 GeV and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $p_T^{t,h}$ in 398.0 GeV < $p_T^{t,h}$ < 496.0 GeV at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $p_T^{t,h}$ in 496.0 GeV < $p_T^{t,h}$ < 2000.0 GeV and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $p_T^{t,h}$ in 355.0 GeV < $p_T^{t,h}$ < 398.0 GeV at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $p_T^{t,h}$ in 496.0 GeV < $p_T^{t,h}$ < 2000.0 GeV and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $p_T^{t,h}$ in 398.0 GeV < $p_T^{t,h}$ < 496.0 GeV at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $p_T^{t,h}$ in 496.0 GeV < $p_T^{t,h}$ < 2000.0 GeV and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $p_T^{t,h}$ in 496.0 GeV < $p_T^{t,h}$ < 2000.0 GeV at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative double-differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ at particle level in the boosted topology in 355.0 GeV < $p_T^{t,h}$ < 398.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ at particle level in the boosted topology in 398.0 GeV < $p_T^{t,h}$ < 496.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ at particle level in the boosted topology in 496.0 GeV < $p_T^{t,h}$ < 2000.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ at particle level in the boosted topology in 355.0 GeV < $p_T^{t,h}$ < 398.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ at particle level in the boosted topology in 398.0 GeV < $p_T^{t,h}$ < 496.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ at particle level in the boosted topology in 496.0 GeV < $p_T^{t,h}$ < 2000.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix between the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ in 355.0 GeV < $p_T^{t,h}$ < 398.0 GeV and the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ in 355.0 GeV < $p_T^{t,h}$ < 398.0 GeV at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ in 398.0 GeV < $p_T^{t,h}$ < 496.0 GeV and the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ in 355.0 GeV < $p_T^{t,h}$ < 398.0 GeV at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ in 398.0 GeV < $p_T^{t,h}$ < 496.0 GeV and the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ in 398.0 GeV < $p_T^{t,h}$ < 496.0 GeV at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ in 496.0 GeV < $p_T^{t,h}$ < 2000.0 GeV and the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ in 355.0 GeV < $p_T^{t,h}$ < 398.0 GeV at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ in 496.0 GeV < $p_T^{t,h}$ < 2000.0 GeV and the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ in 398.0 GeV < $p_T^{t,h}$ < 496.0 GeV at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ in 496.0 GeV < $p_T^{t,h}$ < 2000.0 GeV and the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $p_T^{t,h}$ in 496.0 GeV < $p_T^{t,h}$ < 2000.0 GeV at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative double-differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ at particle level in the boosted topology in $N^j$ = 1. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ at particle level in the boosted topology in $N^j$ = 2. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ at particle level in the boosted topology in $N^j$ $\geq$ 3. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ at particle level in the boosted topology in $N^j$ = 1. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ at particle level in the boosted topology in $N^j$ = 2. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ at particle level in the boosted topology in $N^j$ $\geq$ 3. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix between the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ in $N^j$ = 1 and the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ in $N^j$ = 1 at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ in $N^j$ = 2 and the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ in $N^j$ = 1 at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ in $N^j$ = 2 and the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ in $N^j$ = 2 at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ in $N^j$ $\geq$ 3 and the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ in $N^j$ = 1 at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ in $N^j$ $\geq$ 3 and the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ in $N^j$ = 2 at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ in $N^j$ $\geq$ 3 and the Absolute double-differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ vs $N^j$ in $N^j$ $\geq$ 3 at particle level in the boosted topology, accounting for the statistical uncertainties.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{t,h}$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{t,l}$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{t,l}$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m^{t\bar{t}}$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m^{t\bar{t}}$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m^{t\bar{t}}$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $y^{t,h}$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $y^{t,h}$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $y^{t,h}$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $y^{t,h}$ and the absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $y^{t,l}$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $y^{t,l}$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $y^{t,l}$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $y^{t,l}$ and the absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $y^{t,l}$ and the absolute differential cross-section as function of $y^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $y^{t\bar{t}}$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $y^{t\bar{t}}$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $y^{t\bar{t}}$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $y^{t\bar{t}}$ and the absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $y^{t\bar{t}}$ and the absolute differential cross-section as function of $y^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $y^{t\bar{t}}$ and the absolute differential cross-section as function of $y^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}}$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}}$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}}$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}}$ and the absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}}$ and the absolute differential cross-section as function of $y^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}}$ and the absolute differential cross-section as function of $y^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}}$ and the absolute differential cross-section as function of $y^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ and the absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ and the absolute differential cross-section as function of $y^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ and the absolute differential cross-section as function of $y^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ and the absolute differential cross-section as function of $y^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ and the absolute differential cross-section as function of $H_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{t\bar{t}}$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{t\bar{t}}$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{t\bar{t}}$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{t\bar{t}}$ and the absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{t\bar{t}}$ and the absolute differential cross-section as function of $y^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{t\bar{t}}$ and the absolute differential cross-section as function of $y^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{t\bar{t}}$ and the absolute differential cross-section as function of $y^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{t\bar{t}}$ and the absolute differential cross-section as function of $H_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{t\bar{t}}$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ and the absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ and the absolute differential cross-section as function of $y^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ and the absolute differential cross-section as function of $y^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ and the absolute differential cross-section as function of $y^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ and the absolute differential cross-section as function of $H_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ and the absolute differential cross-section as function of $p_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ and the absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ and the absolute differential cross-section as function of $y^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ and the absolute differential cross-section as function of $y^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ and the absolute differential cross-section as function of $y^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ and the absolute differential cross-section as function of $H_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ and the absolute differential cross-section as function of $p_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $N^j$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $N^j$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $N^j$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $N^j$ and the absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $N^j$ and the absolute differential cross-section as function of $y^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $N^j$ and the absolute differential cross-section as function of $y^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $N^j$ and the absolute differential cross-section as function of $y^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $N^j$ and the absolute differential cross-section as function of $H_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $N^j$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $N^j$ and the absolute differential cross-section as function of $p_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $N^j$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $N^j$ and the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,1}$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,1}$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,1}$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,1}$ and the absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,1}$ and the absolute differential cross-section as function of $y^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,1}$ and the absolute differential cross-section as function of $y^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,1}$ and the absolute differential cross-section as function of $y^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,1}$ and the absolute differential cross-section as function of $H_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,1}$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,1}$ and the absolute differential cross-section as function of $p_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,1}$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,1}$ and the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,1}$ and the absolute differential cross-section as function of $N^j$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m(j_1, t_h)$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m(j_1, t_h)$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m(j_1, t_h)$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m(j_1, t_h)$ and the absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m(j_1, t_h)$ and the absolute differential cross-section as function of $y^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m(j_1, t_h)$ and the absolute differential cross-section as function of $y^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m(j_1, t_h)$ and the absolute differential cross-section as function of $y^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m(j_1, t_h)$ and the absolute differential cross-section as function of $H_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m(j_1, t_h)$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m(j_1, t_h)$ and the absolute differential cross-section as function of $p_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m(j_1, t_h)$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m(j_1, t_h)$ and the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m(j_1, t_h)$ and the absolute differential cross-section as function of $N^j$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $m(j_1, t_h)$ and the absolute differential cross-section as function of $p_T^{j,1}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ and the absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ and the absolute differential cross-section as function of $y^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ and the absolute differential cross-section as function of $y^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ and the absolute differential cross-section as function of $y^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ and the absolute differential cross-section as function of $H_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ and the absolute differential cross-section as function of $p_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ and the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ and the absolute differential cross-section as function of $N^j$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ and the absolute differential cross-section as function of $p_T^{j,1}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ and the absolute differential cross-section as function of $m(j_1, t_h)$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of $y^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of $y^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of $y^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of $H_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of $p_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of $N^j$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of $p_T^{j,1}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of $m(j_1, t_h)$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $y^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $y^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $y^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $H_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $p_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $N^j$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $p_T^{j,1}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $m(j_1, t_h)$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of Inclusive $\sigma$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $y^{t,h}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $y^{t,l}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $y^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $H_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $p_T^{t\bar{t}}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $N^j$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $p_T^{j,1}$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $m(j_1, t_h)$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ at particle level in the boosted topology.

Statistical covariance matrix between the absolute differential cross-section as function of $p_T^{j,2}$ and the absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ at particle level in the boosted topology.

$v_2$ vs Fixed $p_T$ for several centrality selections. [F] and [A] follow the notation Fig. 2. Systematic errors are estimated to be $\sim 5$%.

$v_2$ vs Assorted $p_T$ for several centrality selections. [F] and [A] follow the notation Fig. 2. Systematic errors are estimated to be $\sim 5$%.

$v_2$ vs Assorted $p_T$ for several centrality selections. [F] and [A] follow the notation Fig. 2. Systematic errors are estimated to be $\sim 5$%.

The centrality dependence of $A_2$ for two different $p_T$ selections. [F] and [A] follow the notation in Fig. 2. Systematic errors are estimated to be $\sim 10$%, dominated by the normalization of the correction function and the model determination of$ \varepsilon$.

The centrality dependence of $A_2$ for two different $p_T$ selections. [F] and [A] follow the notation in Fig. 2. Systematic errors are estimated to be $\sim 10$%, dominated by the normalization of the correction function and the model determination of$ \varepsilon$.

Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of single plus non-resonant plus pair vector LQ production from the combination of the high b-jet $p_{T}$ signal region for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$U_1^{MIN}$ model ($\kappa$ = 1) with $\lambda$ = 1.0]

Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of single plus non-resonant plus pair vector LQ production from the combination of the high b-jet $p_{T}$ signal region for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$U_1^{MIN}$ model ($\kappa$ = 1) with $\lambda$ = 1.7]

Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of single plus non-resonant plus pair vector LQ production from the combination of the high b-jet $p_{T}$ signal region for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$U_1^{MIN}$ model ($\kappa$ = 1) with $\lambda$ = 2.5]

The two-dimensional 95% CL exclusion limits in the $\lambda$-$m_{LQ}$ plane for singly plus non-resonant produced vector LQ (green lines) and for the sum, referred as Total, of single plus non-resonant plus pair vector LQ production (blue lines). Regions to the left of the lines are excluded. The dotted area shows the preferred region where the chosen LQ model can explain observed B anomalies. [$\kappa$ = 0]

The two-dimensional 95% CL exclusion limits in the $\lambda$-$m_{LQ}$ plane for singly plus non-resonant produced vector LQ (green lines) and for the sum, referred as Total, of single plus non-resonant plus pair vector LQ production (blue lines). Regions to the left of the lines are excluded. The dotted area shows the preferred region where the chosen LQ model can explain observed B anomalies. [$\kappa$ = 1]

Observed (solid line) and expected (dashed line) 95% CL upper limits for $\lambda$ = 1.0 on the cross-section of single plus non-resonant plus pair $\widetilde{S_{1}}$ production hypotheses from the combination of the high b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels.

Observed (solid line) and expected (dashed line) 95% CL upper limits for $\lambda$ = 1.7 on the cross-section of single plus non-resonant plus pair $\widetilde{S_{1}}$ production hypotheses from the combination of the high b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels.

Observed (solid line) and expected (dashed line) 95% CL upper limits for $\lambda$ = 2.5 on the cross-section of single plus non-resonant plus pair $\widetilde{S_{1}}$ production hypotheses from the combination of the high b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels.

The two-dimensional 95% CL exclusion limits in the $\lambda$-$m_{LQ}$ plane for singly plus non-resonant produced $\widetilde{S_{1}}$ (green lines) and for the sum, referred as Total, of single plus non-resonant plus pair vector LQ production (blue lines). Regions to the left of the lines are excluded.

Observed (solid line) and expected (dashed line) 95% upper limits on the visible cross-section, $\sigma_{\mathrm{vis}}$, obtained from model-independent search by a signal-plus-background fit in the high and low b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels.

Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of singly plus non-resonant produced vector LQ signals from the combination of the high b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$U_1^{YM}$ model ($\kappa$ = 0) with $\lambda$ = 1.0]

Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of singly plus non-resonant produced vector LQ signals from the combination of the high b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$U_1^{YM}$ model ($\kappa$ = 0) with $\lambda$ = 1.7]

Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of singly plus non-resonant produced vector LQ signals from the combination of the high b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$U_1^{YM}$ model ($\kappa$ = 0) with $\lambda$ = 2.5]

Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of singly plus non-resonant produced vector LQ signals from the combination of the high b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$U_1^{MIN}$ model ($\kappa$ = 1) with $\lambda$ = 1.0]

Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of singly plus non-resonant produced vector LQ signals from the combination of the high b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$U_1^{MIN}$ model ($\kappa$ = 1) with $\lambda$ = 1.7]

Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of singly plus non-resonant produced vector LQ signals from the combination of the high b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$U_1^{MIN}$ model ($\kappa$ = 1) with $\lambda$ = 2.5]

Observed (solid line) and expected (dashed line) 95% CL upper limits for $\lambda$ = 1.0 on the cross-section of singly produced $\widetilde{S_{1}}$ signal hypotheses from the combination of the high b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels.

Observed (solid line) and expected (dashed line) 95% CL upper limits for $\lambda$ = 1.7 on the cross-section of singly produced $\widetilde{S_{1}}$ signal hypotheses from the combination of the high b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels.

Observed (solid line) and expected (dashed line) 95% CL upper limits for $\lambda$ = 2.5 on the cross-section of singly produced $\widetilde{S_{1}}$ signal hypotheses from the combination of the high b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels.

The signal acceptance times efficiency for single plus non-resonant produced LQ in the $\widetilde{S_{1}}$ model from the combination of the high and low b-jet $p_{T}$ signal regions for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$\lambda$ = 1.0]

The signal acceptance times efficiency for single plus non-resonant produced LQ in the $\widetilde{S_{1}}$ model from the combination of the high and low b-jet $p_{T}$ signal regions for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$\lambda$ = 1.7]

The signal acceptance times efficiency for single plus non-resonant produced LQ in the $\widetilde{S_{1}}$ model from the combination of the high and low b-jet $p_{T}$ signal regions for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$\lambda$ = 2.5]

The signal acceptance times efficiency for single plus non-resonant produced LQ in the $U_1^{MIN}$ model from the combination of the high and low b-jet $p_{T}$ signal regions for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$\lambda$ = 1.0]

The signal acceptance times efficiency for single plus non-resonant produced LQ in the $U_1^{MIN}$ model from the combination of the high and low b-jet $p_{T}$ signal regions for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$\lambda$ = 1.7]

The signal acceptance times efficiency for single plus non-resonant produced LQ in the $U_1^{MIN}$ model from the combination of the high and low b-jet $p_{T}$ signal regions for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$\lambda$ = 2.5]

The signal acceptance times efficiency for single plus non-resonant produced LQ in the $U_1^{YM}$ model from the combination of the high and low b-jet $p_{T}$ signal regions for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$\lambda$ = 1.0]

The signal acceptance times efficiency for single plus non-resonant produced LQ in the $U_1^{YM}$ model from the combination of the high and low b-jet $p_{T}$ signal regions for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$\lambda$ = 1.7]

The signal acceptance times efficiency for single plus non-resonant produced LQ in the $U_1^{YM}$ model from the combination of the high and low b-jet $p_{T}$ signal regions for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels. [$\lambda$ = 2.5]

Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of singly produced vector LQ signals from the combination of the high and low b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region. [$U_1^{YM}$ model ($\kappa$ = 0) with $\lambda$ = 1.0]

Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of singly produced vector LQ signals from the combination of the high and low b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region. [$U_1^{YM}$ model ($\kappa$ = 0) with $\lambda$ = 1.7]

Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of singly produced vector LQ signals from the combination of the high and low b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region. [$U_1^{YM}$ model ($\kappa$ = 0) with $\lambda$ = 2.5]

Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of singly produced vector LQ signals from the combination of the high and low b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region. [$U_1^{MIN}$ model ($\kappa$ = 1) with $\lambda$ = 1.0]

Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of singly produced vector LQ signals from the combination of the high and low b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region. [$U_1^{MIN}$ model ($\kappa$ = 1) with $\lambda$ = 1.7]

Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of singly produced vector LQ signals from the combination of the high and low b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region. [$U_1^{MIN}$ model ($\kappa$ = 1) with $\lambda$ = 2.5]

Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of the single plus non-resonant plus pair production of vector LQ from the combination of the high and low b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region. [$U_1^{YM}$ model ($\kappa$ = 0) with $\lambda$ = 1.0]

Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of the single plus non-resonant plus pair production of vector LQ from the combination of the high and low b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region. [$U_1^{YM}$ model ($\kappa$ = 0) with $\lambda$ = 1.7]

Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of the single plus non-resonant plus pair production of vector LQ from the combination of the high and low b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region. [$U_1^{YM}$ model ($\kappa$ = 0) with $\lambda$ = 2.5]

Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of the single plus non-resonant plus pair production of vector LQ from the combination of the high and low b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region. [$U_1^{MIN}$ model ($\kappa$ = 1) with $\lambda$ = 1.0]

Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of the single plus non-resonant plus pair production of vector LQ from the combination of the high and low b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region. [$U_1^{MIN}$ model ($\kappa$ = 1) with $\lambda$ = 1.7]

Observed (solid line) and expected (dashed line) 95% CL upper limits on the cross-section of the single plus non-resonant plus pair production of vector LQ from the combination of the high and low b-jet $p_{T}$ category for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region. [$U_1^{MIN}$ model ($\kappa$ = 1) with $\lambda$ = 2.5]

The two-dimensional 95% CL exclusion limits in the $\lambda$-$m_{LQ}$ plane for singly plus non-resonant produced vector LQ (green lines) and for the sum, referred as Total, of single plus non-resonant plus pair vector LQ production (blue lines).Regions to the left of the lines are excluded. The dotted area shows the preferred region where the chosen LQ model can explain observed B anomalies. Results are extracted from the combination of the high and low b-jet $p_{T}$ signal region for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region. [$\kappa$ = 0]

The two-dimensional 95% CL exclusion limits in the $\lambda$-$m_{LQ}$ plane for singly plus non-resonant produced vector LQ (green lines) and for the sum, referred as Total, of single plus non-resonant plus pair vector LQ production (blue lines).Regions to the left of the lines are excluded. The dotted area shows the preferred region where the chosen LQ model can explain observed B anomalies. Results are extracted from the combination of the high and low b-jet $p_{T}$ signal region for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region. [$\kappa$ = 1]

Observed (solid line) and expected (dashed line) 95% CL upper limits for $\lambda$ = 1.0 on the cross-section of singly-produced $\widetilde{S_{1}}$ signals from the combination of the high and low b-jet $p_{T}$ categories for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region.

Observed (solid line) and expected (dashed line) 95% CL upper limits for $\lambda$ = 1.7 on the cross-section of singly-produced $\widetilde{S_{1}}$ signals from the combination of the high and low b-jet $p_{T}$ categories for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region.

Observed (solid line) and expected (dashed line) 95% CL upper limits for $\lambda$ = 2.5 on the cross-section of singly-produced $\widetilde{S_{1}}$ signals from the combination of the high and low b-jet $p_{T}$ categories for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region.

Observed (solid line) and expected (dashed line) 95% CL upper limits for $\lambda$ = 1.0 on the cross-section of single plus non-resonant plus pair $\widetilde{S_{1}}$ production signal from the combination of the high and low b-jet $p_{T}$ categories for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region.

Observed (solid line) and expected (dashed line) 95% CL upper limits for $\lambda$ = 1.7 on the cross-section of single plus non-resonant plus pair $\widetilde{S_{1}}$ production signal from the combination of the high and low b-jet $p_{T}$ categories for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region.

Observed (solid line) and expected (dashed line) 95% CL upper limits for $\lambda$ = 2.5 on the cross-section of single plus non-resonant plus pair $\widetilde{S_{1}}$ production signal from the combination of the high and low b-jet $p_{T}$ categories for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region.

The two-dimensional 95% CL exclusion limits in the $\lambda$-$m_{LQ}$ plane for singly plus non-resonant produced $\widetilde{S_{1}}$ (green lines) and for the sum, referred as Total, of single plus non-resonant plus pair $\widetilde{S_{1}}$ production (blue lines). Regions to the left of the lines are excluded. Results are extracted from the combination of the high and low b-jet $p_{T}$ signal region for the $\tau_\text{lep}\tau_\text{had}$ and $\tau_\text{had}\tau_\text{had}$ channels, neglecting the interference between the LQ non-resonant production processes and the SM processes. However, the interference between the non-resonant LQ production and SM diagrams, such as those from Z+jets, could be non-negligible for events in the low b-jet $p_{T}$ signal region.

Event yields after a background-only fit and data in the three signal regions. All the backgrounds except the fake $\tau_{\mathrm{had}}$ are estimated using the real $\tau_{\mathrm{had}}$ contributions from MC. The fake $\tau_{\mathrm{had}}$ background contribution is data-driven. The top-quark, $V$+jets, and small backgrounds are included in "Others". The total uncertainties include both systematic and statistical. In the $WW1\ell2\tau_{\mathrm{had}}$ channel, the smaller uncertainty in the total background than the fake $\tau_{\mathrm{had}}$ is due to the anticorrelations between the nuisance parameters of the fake $\tau_{\mathrm{had}}$ and diboson backgrounds obtained in the fit.

Uncertainties on $\sigma(pp\to X\to SH)$ obtained from the combined fit to the data for the least and most sensitive mass points. The uncertainties are symmetrised and grouped into the categories described in the systematic section.

Summary of observed and expected 95\% CL upper limits on the production cross-section of $\sigma(pp\to X\to SH)$ in fb in the combination of $WW$+$ZZ$, and in the $WW$ and $ZZ$ individual channels. The best expected limit is set to 85 fb for $m_{X}$ = 1250 GeV and $_{S}$ = 300 GeV. The combination limits gain about 26--53% over the best individual limit from the $WW1\ell2\tau_{\mathrm{had}}$ channel.

Measured cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $1.56<|\eta^{\gamma}|<1.81$ and photon isolation cone radius $R=0.4$.

Measured cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $1.81<|\eta^{\gamma}|<2.01$ and photon isolation cone radius $R=0.4$.

Measured cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $2.01<|\eta^{\gamma}|<2.37$ and photon isolation cone radius $R=0.4$.

Measured cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $|\eta^{\gamma}|<0.6$ and photon isolation cone radius $R=0.2$.

Measured cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $0.6<|\eta^{\gamma}|<0.8$ and photon isolation cone radius $R=0.2$.

Measured cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $0.8<|\eta^{\gamma}|<1.37$ and photon isolation cone radius $R=0.2$.

Measured cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $1.56<|\eta^{\gamma}|<1.81$ and photon isolation cone radius $R=0.2$.

Measured cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $1.81<|\eta^{\gamma}|<2.01$ and photon isolation cone radius $R=0.2$.

Measured cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $2.01<|\eta^{\gamma}|<2.37$ and photon isolation cone radius $R=0.2$.

Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $|\eta^{\gamma}|<0.6$ and isolation cone radius $0.4$ at NNLO QCD.

Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $0.6<|\eta^{\gamma}|<0.8$ and isolation cone radius $0.4$ at NNLO QCD.

Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $0.8<|\eta^{\gamma}|<1.37$ and isolation cone radius $0.4$ at NNLO QCD.

Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $1.56<|\eta^{\gamma}|<1.81$ and isolation cone radius $0.4$ at NNLO QCD.

Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $1.81<|\eta^{\gamma}|<2.01$ and isolation cone radius $0.4$ at NNLO QCD.

Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $2.01<|\eta^{\gamma}|<2.37$ and isolation cone radius $0.4$ at NNLO QCD.

Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $|\eta^{\gamma}|<0.6$ and isolation cone radius $0.2$ at NNLO QCD.

Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $0.6<|\eta^{\gamma}|<0.8$ and isolation cone radius $0.2$ at NNLO QCD.

Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $0.8<|\eta^{\gamma}|<1.37$ and isolation cone radius $0.2$ at NNLO QCD.

Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $1.56<|\eta^{\gamma}|<1.81$ and isolation cone radius $0.2$ at NNLO QCD.

Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $1.81<|\eta^{\gamma}|<2.01$ and isolation cone radius $0.2$ at NNLO QCD.

Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $2.01<|\eta^{\gamma}|<2.37$ and isolation cone radius $0.2$ at NNLO QCD.

Measured ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $|\eta^{\gamma}|<0.6$.

Measured ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $0.6<|\eta^{\gamma}|<0.8$.

Measured ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $0.8<|\eta^{\gamma}|<1.37$.

Measured ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $1.56<|\eta^{\gamma}|<1.81$.

Measured ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $1.81<|\eta^{\gamma}|<2.01$.

Measured ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $2.01<|\eta^{\gamma}|<2.37$.

Predicted ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $|\eta^{\gamma}|<0.6$ at NNLO QCD.

Predicted ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $0.6<|\eta^{\gamma}|<0.8$ at NNLO QCD.

Predicted ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $0.8<|\eta^{\gamma}|<1.37$ at NNLO QCD.

Predicted ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $1.56<|\eta^{\gamma}|<1.81$ at NNLO QCD.

Predicted ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $1.81<|\eta^{\gamma}|<2.01$ at NNLO QCD.

Predicted ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $2.01<|\eta^{\gamma}|<2.37$ at NNLO QCD.

Measured fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $|\eta^{\gamma}|<0.6$.

Measured fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $0.6<|\eta^{\gamma}|<0.8$.

Measured fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $0.8<|\eta^{\gamma}|<1.37$.

Measured fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $1.56<|\eta^{\gamma}|<1.81$.

Measured fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $1.81<|\eta^{\gamma}|<2.01$.

Measured fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $2.01<|\eta^{\gamma}|<2.37$.

Predicted fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $|\eta^{\gamma}|<0.6$ at NNLO QCD.

Predicted fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $0.6<|\eta^{\gamma}|<0.8$ at NNLO QCD.

Predicted fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $0.8<|\eta^{\gamma}|<1.37$ at NNLO QCD.

Predicted fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $1.56<|\eta^{\gamma}|<1.81$ at NNLO QCD.

Predicted fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $1.81<|\eta^{\gamma}|<2.01$ at NNLO QCD.

Predicted fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $2.01<|\eta^{\gamma}|<2.37$ at NNLO QCD.

Distribution of the NN output in the $\geq$1fj$\,$SR in data and the expected contribution of the signal and background processes after the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions considering the correlations of the uncertainties as obtained by the fit.

Distribution of the NN output in the $t\bar{t}\gamma\,$CR in data and the expected contribution of the signal and background processes after the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions considering the correlations of the uncertainties as obtained by the fit.

Total event yield in the $W\gamma\,$CR in data and the expected contribution of the signal and background processes after the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions considering the correlations of the uncertainties as obtained by the fit.

Distribution of the scalar sum of the jet transverse momenta in the 0fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions. The first and last bins include the underflow and overflow, respectively.

Distribution of the $\eta$ of the $b$-tagged jet in the 0fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions.

Distribution of the reconstructed top-quark mass in the 0fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions. The first and last bins include the underflow and overflow, respectively.

Distribution of the $p_{\mathrm{T}}$ of the top-quark+photon system in the 0fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.

Distribution of the photon $p_{\mathrm{T}}$ in the 0fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.

Distribution of the photon $\eta$ in the 0fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions.

Distribution of the scalar sum of the jet transverse momenta in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.

Distribution of the invariant mass of the $b$-tagged jet and the highest-$p_{\mathrm{T}}$ forward jet in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.

Distribution of $p_{\mathrm{T}}$ of the highest-$p_{\mathrm{T}}$ forward jet in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.

Distribution of the difference in $\eta$ between the highest-$p_{\mathrm{T}}$ forward jet and the photon in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.

Distribution of the energy of the system formed by the highest-$p_{\mathrm{T}}$ forward jet and the photon in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions. The first and last bins include the underflow and overflow, respectively.

Distribution of the $\eta$ of the $b$-tagged jet in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions.

Distribution of the reconstructed top-quark mass in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions. The first and last bins include the underflow and overflow, respectively.

Distribution of the $p_{\mathrm{T}}$ of the top-quark and photon system in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.

Distribution of the photon $p_{\mathrm{T}}$ in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.

Distribution of the photon $\eta$ in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions.

Ordered list of the 30 systematic uncertainties with the largest impact on the measured signal normalisation in the fit to data in the parton-level measurement considered as nuisance parameters (NPs) in the profile-likelihood fit. The column "NP value, error" corresponds to the nominal best-fit values and the corresponding uncertainties. The impact of each NP, $\Delta\sigma$/$\sigma_{\mathrm{pred}}$, is computed by comparing the nominal best-fit value of the POI ($\sigma$/$\sigma_{\mathrm{pred}}$) with the result of the fits when fixing the considered NP to its best-fit value shifted by its pre-fit and post-fit uncertainties. The corresponding impacts are listed in the "POI impact prefit high/low" and "POI impact high/low" columns, respectively. The "MC stat." NPs represent the MC statistical uncertainty and they enter the likelihood with a Poisson term, while all the other NPs enter the likelihood via a Gaussian term.

Ordered list of the 30 systematic uncertainties with the largest impact on the measured signal normalisation in the fit to data in the particle-level measurement considered as nuisance parameters (NPs) in the profile-likelihood fit. The column "NP value, error" corresponds to the nominal best-fit values and the corresponding uncertainties. The impact of each NP, $\Delta\sigma$/$\sigma_{\mathrm{pred}}$, is computed by comparing the nominal best-fit value of the POI ($\sigma$/$\sigma_{\mathrm{pred}}$) with the result of the fits when fixing the considered NP to its best-fit value shifted by its pre-fit and post-fit uncertainties. The corresponding impacts are listed in the "POI impact prefit high/low" and "POI impact high/low" columns, respectively. The "MC stat." NPs represent the MC statistical uncertainty and they enter the likelihood with a Poisson term, while all the other NPs enter the likelihood via a Gaussian term.

This table lists the kinematic requirements on parton-level objects used to define of the fiducial phase space for the parton-level measurement. Frixione isolation ($\href{https://arxiv.org/abs/hep-ph/9801442}{\text{hep-ph/9801442}}$) with a chosen radius of $\Delta R = 0.2$ is applied to photons ($\gamma$). The measured fiducial parton-level cross section is $\sigma_{tq\gamma}\times\mathcal{B}(t\rightarrow l\nu b) = 688\pm 23(\text{stat.})^{+75}_{-71}(\text{syst.})\,$fb.

This table lists the kinematic requirements on particle-level objects used to define of the fiducial phase space for the particle-level measurement. The particle level objects are photons ($\gamma$) not from a hadron decay, neutrinos not from a hadron decay ($\nu$), prompt electrons and muons ($\ell$) "dressed" by adding close-by ($\Delta R < 0.1$) photons, and anti-$k_t$ $R = 0.4$ jets built from stable particles ($\tau > 30\,$ps) and tau leptons excluding neutrinos and prompt dressed muons. Jets are $b$-tagged ($b$-jet) using ghost-matched $b$-hadrons with $p_{\text{T}} > 5\,$GeV. Apart from the kinematic requirements, isolation and overlap removal criteria are applied. Jets within $\Delta R = 0.4$ of a photon are removed if the $p_{\text{T}}$ of charged particles within $\Delta R = 0.3$ of the photon is smaller than $10\,\%$ of its $p_{\text{T}}$. Jets within $\Delta R = 0.4$ of a lepton are removed. Events are removed where a photon is close ($\Delta R < 0.4$) to a lepton or a surviving jet. The measured fiducial particle-level cross section is $\sigma_{tq\gamma}\times\mathcal{B}(t\rightarrow l\nu b)+\sigma_{t(\rightarrow l\nu b\gamma)q} = 303\pm 9(\text{stat.})^{+33}_{-32}(\text{syst.})\,$fb.

The performance of jet energy resolution (JER) for jets with |y| < 2.1 evaluated as a function of pT_truth in different centrality bins. Simulated hard scatter events were overlaid onto events from a dedicated sample of minimum-bias Xe+Xe data. The fit parameters are listed in a sperate table (Extras 1)

The relative magnitude of systematic uncertainties for per-pair normalized xJ distributions in 0-10% Xe+Xe centrality

The relative magnitude of systematic uncertainties for absolutely normalized xJ distributions in 0-10% Xe+Xe centrality

The relative magnitude of systematic uncertainties for rho distributions for leading jets in 0-10% Xe+Xe centrality

Per-pair normalized xJ distribution evaluated in four centrality intervals and given pT1 interval.

Per-pair normalized xJ distribution evaluated in four centrality intervals and given pT1 interval.

Per-pair normalized xJ distribution evaluated in four centrality intervals and given pT1 interval.

Absolutely normalized xJ distribution evaluated in four centrality intervals and given pT1 interval.

Absolutely normalized xJ distribution evaluated in four centrality intervals and given pT1 interval.

Absolutely normalized xJ distribution evaluated in four centrality intervals and given pT1 interval.

Per-pair normalized xJ distribution in Xe+Xe collisions.

Per-pair normalized xJ distribution in Pb+Pb collisions.

Per-pair normalized xJ distribution in Xe+Xe collisions.

Per-pair normalized xJ distribution in Pb+Pb collisions.

Per-pair normalized xJ distribution in Xe+Xe collisions.

Per-pair normalized xJ distribution in Pb+Pb collisions.

Absolutely normalized xJ distribution in Xe+Xe collisions.

Absolutely normalized xJ distribution in Xe+Xe collisions.

Absolutely normalized xJ distribution in Xe+Xe collisions.

Absolutely normalized xJ distribution in Xe+Xe collisions.

Absolutely normalized xJ distribution in Xe+Xe collisions.

Absolutely normalized xJ distribution in Xe+Xe collisions.

The ratios of Xe+Xe and Pb+Pb pair nuclear-modification factors, rho, evaluated as a function of leading jet pT in the same centrality intervals.

The ratios of Xe+Xe and Pb+Pb pair nuclear-modification factors, rho, evaluated as a function of leading jet pT in the same centrality intervals.

The ratios of Xe+Xe and Pb+Pb pair nuclear-modification factors, rho, evaluated as a function of leading jet pT in the same centrality intervals.

The ratios of Xe+Xe and Pb+Pb pair nuclear-modification factors, rho, evaluated as a function of subleading jet pT in the same centrality intervals.

The ratios of Xe+Xe and Pb+Pb pair nuclear-modification factors, rho, evaluated as a function of subleading jet pT in the same centrality intervals.

The ratios of Xe+Xe and Pb+Pb pair nuclear-modification factors, rho, evaluated as a function of subleading jet pT in the same centrality intervals.

The ratios of Xe+Xe and Pb+Pb pair nuclear-modification factors, rho, evaluated as a function of leading jet pT in the same SUM ETFCal intervals (selecting equivalent event activity)

The ratios of Xe+Xe and Pb+Pb pair nuclear-modification factors, rho, evaluated as a function of leading jet pT in the same SUM ETFCal intervals (selecting equivalent event activity)

The ratios of Xe+Xe and Pb+Pb pair nuclear-modification factors, rho, evaluated as a function of leading jet pT in the same SUM ETFCal intervals (selecting equivalent event activity)

The ratios of Xe+Xe and Pb+Pb pair nuclear-modification factors, rho, evaluated as a function of subleading jet pT in the same SUM ETFCal intervals (selecting equivalent event activity)

The ratios of Xe+Xe and Pb+Pb pair nuclear-modification factors, rho, evaluated as a function of subleading jet pT in the same SUM ETFCal intervals (selecting equivalent event activity)

The ratios of Xe+Xe and Pb+Pb pair nuclear-modification factors, rho, evaluated as a function of subleading jet pT in the same SUM ETFCal intervals (selecting equivalent event activity)

Parameter a,b, and c from JER fits in Figure 1b.

Per-pair normalized xJ distribution in Xe+Xe collisions for selected Pb+Pb centrality and pT1 bin.

Per-pair normalized xJ distribution in Xe+Xe collisions for selected Pb+Pb centrality and pT1 bin.

Per-pair normalized xJ distribution in Xe+Xe collisions for selected Pb+Pb centrality and pT1 bin.

Per-pair normalized xJ distribution in Xe+Xe collisions for selected Pb+Pb centrality and pT1 bin.

Per-pair normalized xJ distribution in Xe+Xe collisions for selected Pb+Pb centrality and pT1 bin.

Per-pair normalized xJ distribution in Xe+Xe collisions for selected Pb+Pb centrality and pT1 bin.

Per-pair normalized xJ distribution in Xe+Xe collisions for selected Pb+Pb centrality and pT1 bin.

Per-pair normalized xJ distribution in Xe+Xe collisions for selected Pb+Pb centrality and pT1 bin.

Per-pair normalized xJ distribution in Xe+Xe collisions for selected Pb+Pb centrality and pT1 bin.

Normalisation factors for the major background processes and ttW ($\Delta \eta < 0$) from the fit using only statistical uncertainties (fixing Nuisance Parameters (NP) to their fitted values) to data in all analysis regions.

Normalisation factors for the major background processes and ttW ($\Delta \eta < 0$) from the fit using using both statistical and systematic uncertainties to data in all analysis regions.

Correlation matrix between the Normalisation Factors in the fit using only statistical uncertainties (fixing Nuisance Parameters (NP) to their fitted values) to data in all analysis regions.

The most relevant systematic uncertainties ranked by their impact on the leptonic charge asymmetry ($A_c^{\ell}$) parameter at reconstructed level. The impact of the uncertainties is shown before and after the combined profile-likelihood fit to data in the signal and control regions. Pulls introduced by the fitting procedure are also shown. The entries shown in bold are the uncertainties of the freely floating background normalisations. ME stands for "matrix element", PS for "parton shower" and JER for "jet energy resolution". The gamma-uncertainties refer to the MC statistical uncertainties in a specific region and bin.

The most relevant systematic uncertainties ranked by their impact on the ttW Normalisation Factor ($\Delta \eta < 0$) parameter at reconstructed level. The impact of the uncertainties is shown before and after the combined profile-likelihood fit to data in the signal and control regions. Pulls introduced by the fitting procedure are also shown. ME stands for "matrix element", PS for "parton shower" and JER for "jet energy resolution". The gamma-uncertainties refer to the MC statistical uncertainties in a specific region and bin.

The predicted and observed numbers of events in the control and signal regions. The predictions are shown before the fit to data. The indicated uncertainties consider statistical as well as all experimental and theoretical systematic uncertainties. Background categories with event yields with a value of 1.0e-6 have a negligible contribution to the region and are manually set to that value.

The predicted and observed numbers of events in the control and signal regions. The predictions are shown after the fit to data. The indicated uncertainties consider statistical as well as all experimental and theoretical systematic uncertainties. Background categories with event yields with a value of 1.0e-6 have a negligible contribution to the region and are manually set to that value.

Centrality dependence of $⟨p^{trunc}_T⟩$, the average $p_T$ of charged particles with $p_T$ above a threshold $p^{min}_T$ minus the threshold $p^{min}_T$. Shown are values for two $p^{min}_T$ cuts, one at $p_T >$ 0.5 GeV/$c$ representing all data presented in Fig. 2 and the other one at $p_T >$ 2 GeV/$c$.

Nuclear modification factor ($R_{AA}$) for the 60-80%, 30-60%, 15-30%, and 5-15% centrality selections compared to the one for the most central sample (0-5%). Due to insufficient statistics $R_{AA}$ is not shown for the 80-92% sample.

The top panel gives the nuclear modification factor $R_{AA}$ for three exclusive $p_T$ regions as a function of the centrality of the collision. The lower panel shows essentially the same quantity but normalized to the number of participant pairs rather than to the number of binary collisions. The dotted line indicates the expectation for scaling with the number of binary collisions (top) or with the number of participants (bottom). Only statistical errors are shown. The systematic error on the scale and the centrality dependence are identical to the errors shown in Fig. 5. These errors are correlated, i.e. take their maximum or minimum value simultaneously for all centrality and $p_T$ selections. In addition, there are also $p_T$ dependent systematic errors, which are given in Table 1. The systematic errors do not alter the trends in the data.

The top panel shows the measured $R_{side}$ from identical pions for PHENIX. The bottom panel shows the ratio $R_{out}/R_{side}$ as a function of $k_T$. Longitudinal Co-Moving System (LCMS) frame for $\pi^-$

The top panel shows the measured $R_{side}$ from identical pions for PHENIX. The bottom panel shows the ratio $R_{out}/R_{side}$ as a function of $k_T$. Pair Center-of-Mass System (PCMS) frame for $\pi^+$

The top panel shows the measured $R_{side}$ from identical pions for PHENIX. The bottom panel shows the ratio $R_{out}/R_{side}$ as a function of $k_T$. Pair Center-of-Mass System (PCMS) frame for $\pi^-$

Summary of the total uncertainty in the background prediction for each SR of the tt0L-low, tt0L-high, tt1L and tt2L analysis channels in the statistical combination. Their dominant contributions are indicated by individual lines. Individual uncertainties can be correlated, and do not necessarily add up in quadrature to the total background uncertainty.

Exclusion limits for colour-neutral scalar mediator dark matter models as a function of the mediator mass $m(\phi)$ for a DM mass $m_{\chi} = 1$ GeV. Associated production of DM with both single top quarks ($tW$ and $tj$ channels) and top quark pairs is considered. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross section to the cross section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines show the observed (expected) exclusion limits for each individual channel and their statistical combination.

Exclusion limits for colour-neutral pseudoscalar mediator dark matter models as a function of the mediator mass $m(a)$ for a DM mass $m_{\chi} = 1$ GeV. Associated production of DM with both single top quarks ($tW$ and $tj$ channels) and top quark pairs is considered. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross section to the cross section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines show the observed (expected) exclusion limits for each individual channel and their statistical combination.

$E_{\text{T}}^{\text{miss}}$ distribution in SR0X for the tt0L-low analysis. The contributions from all SM backgrounds are shown after the profile likelihood simultaneous fit to all tt0L-low CRs, with the hatched bands representing the total uncertainty. The category '$t\bar{t}$ (other)' represents $t\bar{t}$ events without extra jets or events with extra light-flavour jets. 'Other' includes contributions from $t\bar{t}W$, $tZ$ and $tWZ$ processes. The expected distributions for selected signal models are shown as dashed lines. The overflow events are included in the last bin. The bottom panels show the ratio of the observed data to the total SM background prediction, with the hatched area representing the total uncertainty in the background prediction and the red arrows marking data outside the vertical-axis range.

$E_{\text{T}}^{\text{miss}}$ distribution in SRWX for the tt0L-low analysis. The contributions from all SM backgrounds are shown after the profile likelihood simultaneous fit to all tt0L-low CRs, with the hatched bands representing the total uncertainty. The category '$t\bar{t}$ (other)' represents $t\bar{t}$ events without extra jets or events with extra light-flavour jets. 'Other' includes contributions from $t\bar{t}W$, $tZ$ and $tWZ$ processes. The expected distributions for selected signal models are shown as dashed lines. The overflow events are included in the last bin. The bottom panels show the ratio of the observed data to the total SM background prediction, with the hatched area representing the total uncertainty in the background prediction and the red arrows marking data outside the vertical-axis range.

$E_{\text{T}}^{\text{miss}}$ distribution in SRTX for the tt0L-low analysis. The contributions from all SM backgrounds are shown after the profile likelihood simultaneous fit to all tt0L-low CRs, with the hatched bands representing the total uncertainty. The category '$t\bar{t}$ (other)' represents $t\bar{t}$ events without extra jets or events with extra light-flavour jets. 'Other' includes contributions from $t\bar{t}W$, $tZ$ and $tWZ$ processes. The expected distributions for selected signal models are shown as dashed lines. The overflow events are included in the last bin. The bottom panels show the ratio of the observed data to the total SM background prediction, with the hatched area representing the total uncertainty in the background prediction and the red arrows marking data outside the vertical-axis range.