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A search for charged Higgs bosons decaying into $W^\pm W^\pm$ or $W^\pm Z$ bosons is performed, involving experimental signatures with two leptons of the same charge, or three or four leptons with a variety of charge combinations, missing transverse momentum and jets. A data sample of proton-proton collisions at a centre-of-mass energy of 13 TeV recorded with the ATLAS detector at the Large Hadron Collider between 2015 and 2018 is used. The data correspond to a total integrated luminosity of 139 fb$^{-1}$. The search is guided by a type-II seesaw model that extends the scalar sector of the Standard Model with a scalar triplet, leading to a phenomenology that includes doubly and singly charged Higgs bosons. Two scenarios are explored, corresponding to the pair production of doubly charged $H^{\pm\pm}$ bosons, or the associated production of a doubly charged $H^{\pm\pm}$ boson and a singly charged $H^\pm$ boson. No significant deviations from the Standard Model predictions are observed. $H^{\pm\pm}$ bosons are excluded at 95% confidence level up to 350 GeV and 230 GeV for the pair and associated production modes, respectively.
Distribution of $E_{T}^{miss}$, which is one of the discriminating variables used to define the $2\ell^{sc}$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $\Delta R_{\ell^{\pm}\ell^{\pm}}$, which is one of the discriminating variables used to define the $2\ell^{sc}$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $M_{jets}$, which is one of the discriminating variables used to define the $2\ell^{sc}$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $S$, which is one of the discriminating variables used to define the $2\ell^{sc}$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $E_{T}^{miss}$, which is one of the discriminating variables used to define the $3\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $\Delta R_{\ell^{\pm}\ell^{\pm}}$, which is one of the discriminating variables used to define the $3\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $m_{x\ell}$ ($x$=3), which is one of the discriminating variables used to define the $3\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $p_{T}^{leading jet}$, which is one of the discriminating variables used to define the $3\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $E_{T}^{miss}$, which is one of the discriminating variables used to define the $4\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $\Delta R_{\ell^{\pm}\ell^{\pm}}^{min}$, which is one of the discriminating variables used to define the $4\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $m_{x\ell}$ ($x$=4), which is one of the discriminating variables used to define the $4\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $p_{T}^{\ell_{1}}$, which is one of the discriminating variables used to define the $4\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Contributions from different categories of uncertainties relative to the expected background yields in the defined SRs, as obtained after performing the likelihood ratio test discussed in Section 9 in the paper. The uncertainties are shown for the combination of the individual channels of the $2\ell^{sc}$, $3\ell$ and $4\ell$ SRs. The SRs are indicated along the horizontal axis. In the HEPData entry, the x-axis is simplified for easier visualisation. The first number indicates the sub channel (2:$2\ell^{sc}$, 3:$3\ell$, 4:$4\ell$), while the second number indicates the mass point (2:200, 3:300, 4:400, 5:500).
Data event yields compared with the expected contributions from relevant background sources, for the combination of the individual channels of the $2\ell^{sc}$, $3\ell$ and $4\ell$ SRs. The total uncertainties in the expected event yields are shown as the hatched bands. The SRs are indicated along the horizontal axis. In the HEPData entry, the x-axis is simplified for easier visualisation. The first number indicates the sub channel (2:$2\ell^{sc}$, 3:$3\ell$, 4:$4\ell$), while the second number indicates the mass point (2:200, 3:300, 4:400, 5:500).
The $E_{T}^{miss}$ distribution for the SRs of the $m_{H^{\pm\pm}} = 300~GeV$ signal mass hypothesis, where the selection requirement on $E_{T}^{miss}$ has been removed. In the attached plot, the signals are stacked on top of the backgrounds while individuals contributions of the $2\ell^{sc}$ channel are shown in HEPData. The last bin, isolated by a vertical red dashed line, is inclusive and corresponds to the SR.
The $E_{T}^{miss}$ distribution for the SRs of the $m_{H^{\pm\pm}} = 300~GeV$ signal mass hypothesis, where the selection requirement on $E_{T}^{miss}$ has been removed. In the attached plot, the signals are stacked on top of the backgrounds while individuals contributions of the $3\ell$ channel are shown in HEPData. The last bin, isolated by a vertical red dashed line, is inclusive and corresponds to the SR.
The $E_{T}^{miss}$ distribution for the SRs of the $m_{H^{\pm\pm}} = 300~GeV$ signal mass hypothesis, where the selection requirement on $E_{T}^{miss}$ has been removed. In the attached plot, the signals are stacked on top of the backgrounds while individuals contributions of the $4\ell$ channel are shown in HEPData. The last bin, isolated by a vertical red dashed line, is inclusive and corresponds to the SR.
Observed and expected upper limits of the $H^{\pm\pm}$ pair production cross section times branching fraction at 95% CL obtained from the combination of 2$\ell^{sc}$, 3$\ell$ and 4$\ell$ channels. The region above the observed limit is excluded by the measurement. The bands represent the expected exclusion curves within one and two standard deviations.
The theoretical prediction of Figure 9(a) in the paper.
Observed and expected upper limits of the $H^{\pm\pm}$ and $H^{\pm}$ production cross section times branching fraction at 95% CL obtained from the combination of 2$\ell^{sc}$, 3$\ell$ and 4$\ell$ channels. The region above the observed limit is excluded by the measurement. The bands represent the expected exclusion curves within one and two standard deviations.
The theoretical prediction of Figure 9(b) in the paper.
Data event yields compared with the estimated background in the $m_{H^{\pm\pm}} = 200~GeV$ or $m_{H^{\pm\pm}} = 220~GeV$ SRs. SFOC 0 and SFOC 1,2 refer to the number of same-flavour opposite charge lepton pairs. The total uncertainties in the estimated background yields are shown as the hashed bands. In the HEPData entry, the x-axis is simplified for easier visualisation (1:$e^{\pm}e^{\pm}$, 2:$e^{\pm}\mu^{\pm}$, 3:$\mu^{\pm}\mu^{\pm}$, 4:SFOC 0, 5:SFOC 1,2, 6:$4\ell$).
Data event yields compared with the estimated background in the $m_{H^{\pm\pm}} = 300~GeV$ or $m_{H^{\pm\pm}} = 350~GeV$ SRs. SFOC 0 and SFOC 1,2 refer to the number of same-flavour opposite charge lepton pairs. The total uncertainties in the estimated background yields are shown as the hashed bands. In the HEPData entry, the x-axis is simplified for easier visualisation (1:$e^{\pm}e^{\pm}$, 2:$e^{\pm}\mu^{\pm}$, 3:$\mu^{\pm}\mu^{\pm}$, 4:SFOC 0, 5:SFOC 1,2, 6:$4\ell$).
Data event yields compared with the estimated background in the $m_{H^{\pm\pm}} = 400~GeV$ or $m_{H^{\pm\pm}} = 450~GeV$ SRs. SFOC 0 and SFOC 1,2 refer to the number of same-flavour opposite charge lepton pairs. The total uncertainties in the estimated background yields are shown as the hashed bands. In the HEPData entry, the x-axis is simplified for easier visualisation (1:$e^{\pm}e^{\pm}$, 2:$e^{\pm}\mu^{\pm}$, 3:$\mu^{\pm}\mu^{\pm}$, 4:SFOC 0, 5:SFOC 1,2, 6:$4\ell$).
Data event yields compared with the estimated background in the $m_{H^{\pm\pm}} = 500~GeV$ or $m_{H^{\pm\pm}} = 550~GeV$ or $m_{H^{\pm\pm}} = 600~GeV$ SRs. SFOC 0 and SFOC 1,2 refer to the number of same-flavour opposite charge lepton pairs. The total uncertainties in the estimated background yields are shown as the hashed bands. In the HEPData entry, the x-axis is simplified for easier visualisation (1:$e^{\pm}e^{\pm}$, 2:$e^{\pm}\mu^{\pm}$, 3:$\mu^{\pm}\mu^{\pm}$, 4:SFOC 0, 5:SFOC 1,2, 6:$4\ell$).
A search for charged leptons with large impact parameters using 139 fb$^{-1}$ of $\sqrt{s} = 13$ TeV $pp$ collision data from the ATLAS detector at the LHC is presented, addressing a long-standing gap in coverage of possible new physics signatures. Results are consistent with the background prediction. This search provides unique sensitivity to long-lived scalar supersymmetric lepton-partners (sleptons). For lifetimes of 0.1 ns, selectron, smuon and stau masses up to 720 GeV, 680 GeV, and 340 GeV are respectively excluded at 95% confidence level, drastically improving on the previous best limits from LEP.
Cutflow for SR-$ee$ for 5 representative signal points. For the following $\tilde{e}$ mass and lifetime points, the number of Monte Carlo events generated are: 24,000 for (100 GeV, 0.01 ns), 16,000 for (300 GeV, 1 ns), and 12,000 for (500 GeV, 0.1 ns). For the $\tilde{\tau}$ mass and lifetime points, the number of Monte Carlo events generated are: 30,000 for (200 GeV, 0.1 ns), and 104,000 for (300 GeV, 0.1 ns).
Cutflow for SR-$ee$ for 5 representative signal points. For the following $\tilde{e}$ mass and lifetime points, the number of Monte Carlo events generated are: 24,000 for (100 GeV, 0.01 ns), 16,000 for (300 GeV, 1 ns), and 12,000 for (500 GeV, 0.1 ns). For the $\tilde{\tau}$ mass and lifetime points, the number of Monte Carlo events generated are: 30,000 for (200 GeV, 0.1 ns), and 104,000 for (300 GeV, 0.1 ns).
Cutflow for SR-$e\mu$ for 2 representative signal points. For the $\tilde{\tau}$ mass and lifetime points, the number of Monte Carlo events generated are: 30,000 for (200 GeV, 0.1 ns), and 104,000 for (300 GeV, 0.1 ns).
Cutflow for SR-$e\mu$ for 2 representative signal points. For the $\tilde{\tau}$ mass and lifetime points, the number of Monte Carlo events generated are: 30,000 for (200 GeV, 0.1 ns), and 104,000 for (300 GeV, 0.1 ns).
Cutflow for SR-$\mu\mu$ for 5 representative signal points. For the following $\tilde{\mu}$ mass and lifetime points, the number of Monte Carlo events generated are: 24,000 for (100 GeV, 0.01 ns), 16,000 for (300 GeV, 1 ns), and 12,000 for (500 GeV, 0.1 ns). For the $\tilde{\tau}$ mass and lifetime points, the number of Monte Carlo events generated are: 30,000 for (200 GeV, 0.1 ns), and 104,000 for (300 GeV, 0.1 ns).
Cutflow for SR-$\mu\mu$ for 5 representative signal points. For the following $\tilde{\mu}$ mass and lifetime points, the number of Monte Carlo events generated are: 24,000 for (100 GeV, 0.01 ns), 16,000 for (300 GeV, 1 ns), and 12,000 for (500 GeV, 0.1 ns). For the $\tilde{\tau}$ mass and lifetime points, the number of Monte Carlo events generated are: 30,000 for (200 GeV, 0.1 ns), and 104,000 for (300 GeV, 0.1 ns).
Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, where all slepton flavors are mass degenerate (co-NLSP).
Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, where all slepton flavors are mass degenerate (co-NLSP).
Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for the selectron signal model. Selectron ($\tilde{e}_{L, R}$) refers to the scalar superpartners of left- and right-handed electrons.
Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for the selectron signal model. Selectron ($\tilde{e}_{L, R}$) refers to the scalar superpartners of left- and right-handed electrons.
Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for the superpartners of the left-handed electrons, $\tilde{e}_L$.
Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for the superpartners of the left-handed electrons, $\tilde{e}_L$.
Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for the superpartners of the right-handed electrons, $\tilde{e}_R$.
Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for the superpartners of the right-handed electrons, $\tilde{e}_R$.
Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for the smuon signal model. Smuon ($\tilde{\mu}_{L, R}$) refers to the scalar superpartners of left- and right-handed muons.
Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for the smuon signal model. Smuon ($\tilde{\mu}_{L, R}$) refers to the scalar superpartners of left- and right-handed muons.
Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for the superpartners of the left-handed muons, $\tilde{\mu}_L$.
Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for the superpartners of the left-handed muons, $\tilde{\mu}_L$.
Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for the superpartners of the right-handed muons, $\tilde{\mu}_R$.
Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for the superpartners of the right-handed muons, $\tilde{\mu}_R$.
Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for the stau signal model. Staus, $\tilde{\tau}_{1,2}$ are the mixed states of the superpartners of the left- and right-handed $\tau$ leptons, with mixing angle $\sin\theta_{\tilde\tau}=0.95$.
Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for the stau signal model. Staus, $\tilde{\tau}_{1,2}$ are the mixed states of the superpartners of the left- and right-handed $\tau$ leptons, with mixing angle $\sin\theta_{\tilde\tau}=0.95$.
Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for $\tilde{\tau}_L$ production, where $\tilde{\tau}_L$ is pure-state superpartner of the left-handed $\tau$.
Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for $\tilde{\tau}_L$ production, where $\tilde{\tau}_L$ is pure-state superpartner of the left-handed $\tau$.
The expected and observed yields in the signal regions. Combined statistical and systematic uncertainties are presented. Estimates are truncated at 0 if the size of measured systematic uncertainties would yield a negative result.
The expected and observed yields in the signal regions. Combined statistical and systematic uncertainties are presented. Estimates are truncated at 0 if the size of measured systematic uncertainties would yield a negative result.
Reconstruction efficiency as a function of $|d_{0}|$ and $p_\text{T}$ for signal electrons. Monte Carlo samples with $\tilde{e}$ or $\tilde{\mu}$ with mass 400 GeV and 1 ns lifetime were used. Efficiency is defined as the number of leptons passing all signal requirements and matched to generator-level muons divided by the number of generator level leptons with $p_\text{T} > 65$ GeV, $|d_{0}| >$ 3 mm, and |$\eta$| $<$ 2.47 for electrons. No event-level selections are made. Reconstructed leptons must pass all quality criteria, including the cosmic veto. Electron selection scale factors are included on the reconstructed leptons. The overflow is not shown in these plots.
Reconstruction efficiency as a function of $|d_{0}|$ and $p_\text{T}$ for signal electrons. Monte Carlo samples with $\tilde{e}$ or $\tilde{\mu}$ with mass 400 GeV and 1 ns lifetime were used. Efficiency is defined as the number of leptons passing all signal requirements and matched to generator-level muons divided by the number of generator level leptons with $p_\text{T} > 65$ GeV, $|d_{0}| >$ 3 mm, and |$\eta$| $<$ 2.47 for electrons. No event-level selections are made. Reconstructed leptons must pass all quality criteria, including the cosmic veto. Electron selection scale factors are included on the reconstructed leptons. The overflow is not shown in these plots.
Reconstruction efficiency as a function of $|d_{0}|$ and $p_\text{T}$ for signal muons. Monte Carlo samples with $\tilde{e}$ or $\tilde{\mu}$ with mass 400 GeV and 1 ns lifetime were used. Efficiency is defined as the number of leptons passing all signal requirements and matched to generator-level muons divided by the number of generator level leptons with $p_\text{T} > 65$ GeV, $|d_{0}| >$ 3 mm, and |$\eta$| $<$ 2.5 for muons. No event-level selections are made. Reconstructed leptons must pass all quality criteria, including the cosmic veto. Muon selection scale factors are included on the reconstructed leptons. The overflow is not shown in these plots.
Reconstruction efficiency as a function of $|d_{0}|$ and $p_\text{T}$ for signal muons. Monte Carlo samples with $\tilde{e}$ or $\tilde{\mu}$ with mass 400 GeV and 1 ns lifetime were used. Efficiency is defined as the number of leptons passing all signal requirements and matched to generator-level muons divided by the number of generator level leptons with $p_\text{T} > 65$ GeV, $|d_{0}| >$ 3 mm, and |$\eta$| $<$ 2.5 for muons. No event-level selections are made. Reconstructed leptons must pass all quality criteria, including the cosmic veto. Muon selection scale factors are included on the reconstructed leptons. The overflow is not shown in these plots.
Acceptance for $\tilde{e}$ of various masses and lifetimes in SR-$ee$. Acceptance is defined as the number of accepted events at generator level in signal Monte Carlo simulation divided by the total number of events in the sample. To be accepted, events are required to have at least 2 truth electrons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.47, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$.
Acceptance for $\tilde{e}$ of various masses and lifetimes in SR-$ee$. Acceptance is defined as the number of accepted events at generator level in signal Monte Carlo simulation divided by the total number of events in the sample. To be accepted, events are required to have at least 2 truth electrons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.47, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$.
Acceptance for $\tilde{\mu}$ of various masses and lifetimes in SR-$\mu\mu$. Acceptance is defined as the number of accepted events at generator level in signal Monte Carlo simulation divided by the total number of events in the sample. To be accepted, events are required to have at least 2 truth muons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$.
Acceptance for $\tilde{\mu}$ of various masses and lifetimes in SR-$\mu\mu$. Acceptance is defined as the number of accepted events at generator level in signal Monte Carlo simulation divided by the total number of events in the sample. To be accepted, events are required to have at least 2 truth muons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$.
Efficiency for $\tilde{e}$ of various masses and lifetimes in SR-$ee$. Efficiency is defined as the number of selected reconstruced events divided by the acceptance. To be accepted, events are required to have at least 2 truth electrons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.47, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. To be selected, events must satisfy all signal region requirements.
Efficiency for $\tilde{e}$ of various masses and lifetimes in SR-$ee$. Efficiency is defined as the number of selected reconstruced events divided by the acceptance. To be accepted, events are required to have at least 2 truth electrons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.47, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. To be selected, events must satisfy all signal region requirements.
Efficiency for $\tilde{\mu}$ of various masses and lifetimes in SR-$\mu\mu$. Efficiency is defined as the number of selected reconstruced events divided by the acceptance. To be accepted, events are required to have at least 2 truth muons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. To be selected, events must satisfy all signal region requirements.
Efficiency for $\tilde{\mu}$ of various masses and lifetimes in SR-$\mu\mu$. Efficiency is defined as the number of selected reconstruced events divided by the acceptance. To be accepted, events are required to have at least 2 truth muons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. To be selected, events must satisfy all signal region requirements.
Acceptance as a function of the generator-level $p_\text{T}$ of the leading and subleading lepton in SR-$ee$ from $\tilde{e}$ decays. The plot is made from signal Monte Carlo events with $\tilde{\ell}$ with mass of 400 GeV and lifetime of 1 ns. To be accepted, events are required to have at least 2 truth leptons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.47 for electrons, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. The overflow is not shown in these plots.
Acceptance as a function of the generator-level $p_\text{T}$ of the leading and subleading lepton in SR-$ee$ from $\tilde{e}$ decays. The plot is made from signal Monte Carlo events with $\tilde{\ell}$ with mass of 400 GeV and lifetime of 1 ns. To be accepted, events are required to have at least 2 truth leptons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.47 for electrons, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. The overflow is not shown in these plots.
Acceptance as a function of the generator-level $p_\text{T}$ of the leading and subleading lepton in SR-$\mu\mu$ from $\tilde{\mu}$ decays. The plot is made from signal Monte Carlo events with $\tilde{\ell}$ with mass of 400 GeV and lifetime of 1 ns. To be accepted, events are required to have at least 2 truth leptons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5 for muons, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. The overflow is not shown in these plots.
Acceptance as a function of the generator-level $p_\text{T}$ of the leading and subleading lepton in SR-$\mu\mu$ from $\tilde{\mu}$ decays. The plot is made from signal Monte Carlo events with $\tilde{\ell}$ with mass of 400 GeV and lifetime of 1 ns. To be accepted, events are required to have at least 2 truth leptons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5 for muons, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. The overflow is not shown in these plots.
Acceptance for $\tilde{\tau}$ of various masses and lifetimes in SR-$ee$. Acceptance is defined as the number of accepted events at generator level in signal Monte Carlo simulation divided by the total number of events in the sample. To be accepted, events are required to have at least 2 truth electrons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.47, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$.
Acceptance for $\tilde{\tau}$ of various masses and lifetimes in SR-$ee$. Acceptance is defined as the number of accepted events at generator level in signal Monte Carlo simulation divided by the total number of events in the sample. To be accepted, events are required to have at least 2 truth electrons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.47, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$.
Acceptance for $\tilde{\tau}$ of various masses and lifetimes in SR-$e\mu$. Acceptance is defined as the number of accepted events at generator level in signal Monte Carlo simulation divided by the total number of events in the sample. To be accepted, events are required to have at least 2 truth leptons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5 (2.47) for muons (electrons), $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$.
Acceptance for $\tilde{\tau}$ of various masses and lifetimes in SR-$e\mu$. Acceptance is defined as the number of accepted events at generator level in signal Monte Carlo simulation divided by the total number of events in the sample. To be accepted, events are required to have at least 2 truth leptons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5 (2.47) for muons (electrons), $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$.
Acceptance for $\tilde{\tau}$ of various masses and lifetimes in SR-$\mu\mu$. Acceptance is defined as the number of accepted events at generator level in signal Monte Carlo simulation divided by the total number of events in the sample. To be accepted, events are required to have at least 2 truth muons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$.
Acceptance for $\tilde{\tau}$ of various masses and lifetimes in SR-$\mu\mu$. Acceptance is defined as the number of accepted events at generator level in signal Monte Carlo simulation divided by the total number of events in the sample. To be accepted, events are required to have at least 2 truth muons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$.
Efficiency for $\tilde{\tau}$ of various masses and lifetimes in SR-$ee$. Efficiency is defined as the number of selected reconstruced events divided by the acceptance. To be accepted, events are required to have at least 2 truth electrons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.47, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. To be selected, events must satisfy all signal region requirements.
Efficiency for $\tilde{\tau}$ of various masses and lifetimes in SR-$ee$. Efficiency is defined as the number of selected reconstruced events divided by the acceptance. To be accepted, events are required to have at least 2 truth electrons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.47, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. To be selected, events must satisfy all signal region requirements.
Efficiency for $\tilde{\tau}$ of various masses and lifetimes in SR-$e\mu$. Efficiency is defined as the number of selected reconstruced events divided by the acceptance. To be accepted, events are required to have at least 2 truth leptons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5 (2.47) for muons (electrons), $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. To be selected, events must satisfy all signal region requirements.
Efficiency for $\tilde{\tau}$ of various masses and lifetimes in SR-$e\mu$. Efficiency is defined as the number of selected reconstruced events divided by the acceptance. To be accepted, events are required to have at least 2 truth leptons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5 (2.47) for muons (electrons), $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. To be selected, events must satisfy all signal region requirements.
Efficiency for $\tilde{\tau}$ of various masses and lifetimes in SR-$\mu\mu$. Efficiency is defined as the number of selected reconstruced events divided by the acceptance. To be accepted, events are required to have at least 2 truth muons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. To be selected, events must satisfy all signal region requirements.
Efficiency for $\tilde{\tau}$ of various masses and lifetimes in SR-$\mu\mu$. Efficiency is defined as the number of selected reconstruced events divided by the acceptance. To be accepted, events are required to have at least 2 truth muons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. To be selected, events must satisfy all signal region requirements.
Acceptance as a function of the generator-level $p_\text{T}$ of the leading and subleading lepton in SR-$e\mu$ from $\tilde{\tau}$ decays. The plot is made from signal Monte Carlo events with $\tilde{\ell}$ with mass of 400 GeV and lifetime of 1 ns. To be accepted, events are required to have at least 2 truth leptons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5 (2.47) for muons (electrons), $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. The overflow is not shown in these plots.
Acceptance as a function of the generator-level $p_\text{T}$ of the leading and subleading lepton in SR-$e\mu$ from $\tilde{\tau}$ decays. The plot is made from signal Monte Carlo events with $\tilde{\ell}$ with mass of 400 GeV and lifetime of 1 ns. To be accepted, events are required to have at least 2 truth leptons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5 (2.47) for muons (electrons), $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. The overflow is not shown in these plots.
Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane where all slepton flavors and chiralities are mass degenerate.
Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane where all slepton flavors and chiralities are mass degenerate.
Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane where all slepton flavors and chiralities are mass degenerate.
Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane where all slepton flavors and chiralities are mass degenerate.
Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$ee$ targeting selectron production. Selectrons ($\tilde{e}_{L, R}$) refer to the scalar superpartners of left- and right-handed electrons, which are assumed to be mass degenerate.
Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$ee$ targeting selectron production. Selectrons ($\tilde{e}_{L, R}$) refer to the scalar superpartners of left- and right-handed electrons, which are assumed to be mass degenerate.
Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$ee$ targeting selectron production. Selectrons ($\tilde{e}_{L, R}$) refer to the scalar superpartners of left- and right-handed electrons, which are assumed to be mass degenerate.
Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$ee$ targeting selectron production. Selectrons ($\tilde{e}_{L, R}$) refer to the scalar superpartners of left- and right-handed electrons, which are assumed to be mass degenerate.
Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$ee$ targeting selectron production. Selectrons ($\tilde{e}_{L}$) refer to the scalar superpartners of left-handed electrons.
Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$ee$ targeting selectron production. Selectrons ($\tilde{e}_{L}$) refer to the scalar superpartners of left-handed electrons.
Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$ee$ targeting selectron production. Selectrons ($\tilde{e}_{L}$) refer to the scalar superpartners of left-handed electrons.
Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$ee$ targeting selectron production. Selectrons ($\tilde{e}_{L}$) refer to the scalar superpartners of left-handed electrons.
Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$ee$ targeting selectron production. Selectrons ($\tilde{e}_{R}$) refer to the scalar superpartners of right-handed electrons. Purple denotes the region excluded by LEP.
Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$ee$ targeting selectron production. Selectrons ($\tilde{e}_{R}$) refer to the scalar superpartners of right-handed electrons. Purple denotes the region excluded by LEP.
Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$ee$ targeting selectron production. Selectrons ($\tilde{e}_{R}$) refer to the scalar superpartners of right-handed electrons. Purple denotes the region excluded by LEP.
Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$ee$ targeting selectron production. Selectrons ($\tilde{e}_{R}$) refer to the scalar superpartners of right-handed electrons. Purple denotes the region excluded by LEP.
Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$\mu\mu$ targeting smuon production. Smuons ($\tilde{\mu}_{L, R}$) refer to the scalar superpartners of left- and right-handed muons, which are assumed to be mass degenerate.
Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$\mu\mu$ targeting smuon production. Smuons ($\tilde{\mu}_{L, R}$) refer to the scalar superpartners of left- and right-handed muons, which are assumed to be mass degenerate.
Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$\mu\mu$ targeting smuon production. Smuons ($\tilde{\mu}_{L, R}$) refer to the scalar superpartners of left- and right-handed muons, which are assumed to be mass degenerate.
Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$\mu\mu$ targeting smuon production. Smuons ($\tilde{\mu}_{L, R}$) refer to the scalar superpartners of left- and right-handed muons, which are assumed to be mass degenerate.
Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$\mu\mu$ targeting smuon production. Smuons ($\tilde{\mu}_{L}$) refer to the scalar superpartners of left-handed muons.
Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$\mu\mu$ targeting smuon production. Smuons ($\tilde{\mu}_{L}$) refer to the scalar superpartners of left-handed muons.
Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$\mu\mu$ targeting smuon production. Smuons ($\tilde{\mu}_{L}$) refer to the scalar superpartners of left-handed muons.
Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$\mu\mu$ targeting smuon production. Smuons ($\tilde{\mu}_{L}$) refer to the scalar superpartners of left-handed muons.
Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$\mu\mu$ targeting smuon production. Smuons ($\tilde{\mu}_{R}$) refer to the scalar superpartners of right-handed muons. Purple denotes the region excluded by LEP.
Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$\mu\mu$ targeting smuon production. Smuons ($\tilde{\mu}_{R}$) refer to the scalar superpartners of right-handed muons. Purple denotes the region excluded by LEP.
Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$\mu\mu$ targeting smuon production. Smuons ($\tilde{\mu}_{R}$) refer to the scalar superpartners of right-handed muons. Purple denotes the region excluded by LEP.
Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$\mu\mu$ targeting smuon production. Smuons ($\tilde{\mu}_{R}$) refer to the scalar superpartners of right-handed muons. Purple denotes the region excluded by LEP.
Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\tau})$ plane. Staus, $\tilde{\tau}_{1,2}$ are the mixed states of the superpartners of the left- and right-handed $\tau$ leptons, with mixing angle $\sin(\theta_{\tilde\tau})=0.95$, which are assumed to be mass degenerate.
Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\tau})$ plane. Staus, $\tilde{\tau}_{1,2}$ are the mixed states of the superpartners of the left- and right-handed $\tau$ leptons, with mixing angle $\sin(\theta_{\tilde\tau})=0.95$, which are assumed to be mass degenerate.
Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\tau})$ plane. Staus, $\tilde{\tau}_{1,2}$ are the mixed states of the superpartners of the left- and right-handed $\tau$ leptons, with mixing angle $\sin(\theta_{\tilde\tau})=0.95$, which are assumed to be mass degenerate.
Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\tau})$ plane. Staus, $\tilde{\tau}_{1,2}$ are the mixed states of the superpartners of the left- and right-handed $\tau$ leptons, with mixing angle $\sin(\theta_{\tilde\tau})=0.95$, which are assumed to be mass degenerate.
Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\tau}_L)$ plane, where $\tilde{\tau}_L$ is the pure-state super-partner of the left-handed $\tau$. Purple denotes the region excluded by LEP. This result does not present signficant sensitivity to the pure-state superpartner of the right-handed $\tau$.
Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\tau}_L)$ plane, where $\tilde{\tau}_L$ is the pure-state super-partner of the left-handed $\tau$. Purple denotes the region excluded by LEP. This result does not present signficant sensitivity to the pure-state superpartner of the right-handed $\tau$.
Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\tau}_L)$ plane, where $\tilde{\tau}_L$ is the pure-state super-partner of the left-handed $\tau$. Purple denotes the region excluded by LEP. This result does not present signficant sensitivity to the pure-state superpartner of the right-handed $\tau$.
Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\tau}_L)$ plane, where $\tilde{\tau}_L$ is the pure-state super-partner of the left-handed $\tau$. Purple denotes the region excluded by LEP. This result does not present signficant sensitivity to the pure-state superpartner of the right-handed $\tau$.
This article presents the results of two studies of Higgs boson properties using the $WW^*(\rightarrow e\nu\mu\nu)jj$ final state, based on a dataset corresponding to 36.1/fb of $\sqrt{s}$=13 TeV proton$-$proton collisions recorded by the ATLAS experiment at the Large Hadron Collider. The first study targets Higgs boson production via gluon$-$gluon fusion and constrains the CP properties of the effective Higgs$-$gluon interaction. Using angular distributions and the overall rate, a value of $\tan(\alpha) = 0.0 \pm 0.4$ stat. $ \pm 0.3$ syst is obtained for the tangent of the mixing angle for CP-even and CP-odd contributions. The second study exploits the vector-boson fusion production mechanism to probe the Higgs boson couplings to longitudinally and transversely polarised $W$ and $Z$ bosons in both the production and the decay of the Higgs boson; these couplings have not been directly constrained previously. The polarisation-dependent coupling-strength scale factors are defined as the ratios of the measured polarisation-dependent coupling strengths to those predicted by the Standard Model, and are determined using rate and kinematic information to be $a_L=0.91^{+0.10}_{-0.18}$(stat.)$^{+0.09}_{-0.17}$(syst.) and $a_{T}=1.2 \pm 0.4 $(stat.)$ ^{+0.2}_{-0.3} $(syst.). These coupling strengths are translated into pseudo-observables, resulting in $\kappa_{VV}= 0.91^{+0.10}_{-0.18}$(stat.)$^{+0.09}_{-0.17}$(syst.) and $\epsilon_{VV} =0.13^{+0.28}_{-0.20}$ (stat.)$^{+0.08}_{-0.10}$(syst.). All results are consistent with the Standard Model predictions.
Post-fit NFs and their uncertainties for the Z+jets, top and WW backgrounds. Both sets of normalisation factors differ slightly depending on which (B)SM model is tested, but are consistent within their total uncertainties.
Post-fit event yields in the signal and control regions obtained from the study of the signal strength parameter $\mu^{\text{ggF+2jets}}$. The quoted uncertainties include the theoretical and experimental systematic sources and those due to sample statistics. The fit constrains the total expected yield to the observed yield. The diboson background is split into $W W$ and non-$W W$ contributions.
Breakdown of the main contributions to the total uncertainty on $\tan \alpha$ based on the fit that exploits both shape and rate information. Individual sources of systematic uncertainty are grouped into either the theoretical or the experimental uncertainty. The sum in quadrature of the individual components differs from the total uncertainty due to correlations between the components.
Post-fit event yields in the signal and control regions obtained from a scan over $\epsilon_{VV}$ exploiting both shape and rate information. The quoted uncertainties include the theoretical and experimental systematic sources and those due to sample statistics. The fit constrains the total expected yield to the observed yield. The diboson background is split into $W W$ and non-$W W$ contributions.
Best-fit values and their uncertainties as obtained from the shape-only and shape-plus-rate likelihood fits to the Asimov dataset and to ATLAS data. Results of both shape-only and shape+rate fits for $a_L$ and $a_T$ are shown. Results of fits to one parameter with the other one fixed or profiled are presented.
Best-fit values and their uncertainties as obtained from the shape-only and shape-plus-rate likelihood fits to the Asimov dataset and to ATLAS data. Results of both shape-only and shape+rate fits for $\epsilon_{VV}$ and $\kappa_{VV}$ are shown. Results of fits to one parameter with the other one fixed or profiled are presented.
The contributions of the leading individual systematic uncertainties together with the data statistical uncertainties, in the one dimensional fit for the pseudo-observables $\kappa_{VV}$ (a) and $\epsilon_{VV}$ (b) for electroweak-boson polarisation in the VBF $H\to WW$ channel. Both shape and rate informations are exploited in the fit. The theoretical and experimental uncertainties are subdivided further into categories.
The contributions of the leading individual systematic uncertainties together with the data statistical uncertainties, in the one dimensional fit for the pseudo-observables $\kappa_{VV}$ (a) and $\epsilon_{VV}$ (b) for electroweak-boson polarisation in the VBF $H\to WW$ channel. Both shape and rate informations are exploited in the fit. The theoretical and experimental uncertainties are subdivided further into categories.
Post-fit distribution of the BDT response observable presented in the four $|\Delta \eta jj|$ categories of the ggF +2 jets signal region, with signal and background yields fixed from the fit for $\mu^{\text{ggF+2jets}}$. The distributions of the ggF + 2 jets and VBF processes are overlaid with their respective contributions multiplied by 50.
The weighted $\Delta \Phi_{jj}$ post-fit distribution in the ggF +2 jets signal region, with signal and background yields fixed from the fit to $\tan \alpha$ using shape and rate information.
Expected and observed likelihood curves for scans over $\tan \alpha$ where only the shape is taken into account in the fit, $\mu_{VBF}$ is fixed.
Expected and observed likelihood curves for scans over $\tan \alpha$ where both shape and normalisation are taken into account in the fit, $\mu_{VBF}$ is fixed.
68% and 95% CL two-dimensional likelihood contours of the CP-even and CP-odd coupling parameters $K_{gg} \cos(\alpha)$ and $K_{gg} \sin(\alpha)$. The minima are represented by black stars, while the SM value is shown as a red star.
The weighted $\Delta \Phi jj$ distribution in the VBF signal region, with signal and background yields fixed from the fit for $\epsilon_{VV}$ using shape and rate information.
Likelihood scans over the transversally polarised couplings. The fit is using shape-only information. All relevant experimental and modelling systematic uncertainties are considered in the fit.
Likelihood scans over the transversally polarised couplings. The fit is using shape + rate information. All relevant experimental and modelling systematic uncertainties are considered in the fit.
Likelihood scans over the longitudinally polarised couplings. The fit is using shape + rate information. All relevant experimental and modelling systematic uncertainties are considered in the fit.
Likelihood scans over $\kappa_{VV}$ with the $\epsilon_{VV}$ profiled. The fit is performed using both shape and rate information. All relevant experimental and theoretical systematic uncertainties are considered in the fit.
Likelihood scans over $\epsilon_{VV}$ with the $\kappa_{VV}$ profiled. The fit is performed using both shape and rate information. All relevant experimental and theoretical systematic uncertainties are considered in the fit.
The contributions of the leading individual systematic uncertainties together with the data statistical uncertainties, in the one dimensional fit for electroweak-boson polarisation in the VBF $H\to WW$ channel, using (aL, aT) parametrisation. Both shape and rate informations are exploited in the fit. The theoretical and experimental uncertainties are subdivided further into categories.
The contributions of the leading individual systematic uncertainties together with the data statistical uncertainties, in the one dimensional fit for electroweak-boson polarisation in the VBF $H\to WW$ channel, using (aL, aT) parametrisation.. Both shape and rate informations are exploited in the fit. The theoretical and experimental uncertainties are subdivided further into categories.
A search for dark-matter particles in events with large missing transverse momentum and a Higgs boson candidate decaying into two photons is reported. The search uses $139$ fb$^{-1}$ of proton-proton collision data collected at $\sqrt{s}=13$ TeV with the ATLAS detector at the CERN LHC between 2015 and 2018. No significant excess of events over the Standard Model predictions is observed. The results are interpreted by extracting limits on three simplified models that include either vector or pseudoscalar mediators and predict a final state with a pair of dark-matter candidates and a Higgs boson decaying into two photons.
The $E^{miss}_{T}$ distribution of data and MC after the diphoton selection.
The observed exclusion contor for the $Z^{\prime}_{B}$ model in the $m_{\chi}$-$m_{Z^{\prime}_{B}}$ plane.
The expected exclusion contor for the $Z^{\prime}_{B}$ model in the $m_{\chi}$-$m_{Z^{\prime}_{B}}$ plane.
The +1 $\sigma$ band of the observed exclusion contor for the $Z^{\prime}_{B}$ model in the $m_{\chi}$-$m_{Z^{\prime}_{B}}$ plane.
The -1 $\sigma$ band of the observed exclusion contor for the $Z^{\prime}_{B}$ model in the $m_{\chi}$-$m_{Z^{\prime}_{B}}$ plane.
A comparison of the inferred limits to the constraints from direct detection experiments on the spin-independent DM--nucleon cross section in the context of the $Z'_B$ simplified model with vector couplings. Limits are shown at 90% CL.
The observed exclusion contor for the $Z^{\prime}$-2HDM model in the $m_{A}$-$m_{Z^{\prime}}$ plane.
The expected exclusion contor for the $Z^{\prime}$-2HDM model in the $m_{A}$-$m_{Z^{\prime}}$ plane.
The +1 $\sigma$ band of the observed exclusion contor for the $m_{A}$-$Z^{\prime}$-2HDM model in the $m_{Z^{\prime}}$ plane.
The -1 $\sigma$ band of the observed exclusion contor for the $m_{A}$-$Z^{\prime}$-2HDM model in the $m_{Z^{\prime}}$ plane.
The observed exclusion contor for the 2HDM-a model in the $m_{A}$-$m_{a}$ plane.
The expected exclusion contor for the 2HDM-a model in the $m_{A}$-$m_{a}$ plane.
The +1 $\sigma$ band of the observed exclusion contor for the 2HDM-a model in the $m_{A}$-$m_{a}$ plane.
The -1 $\sigma$ band of the observed exclusion contor for the 2HDM-a model in the $m_{A}$-$m_{a}$ plane.
The observed exclusion contor for the 2HDM-a model in the $tan\beta$-$m_{a}$ plane.
The expected exclusion contor for the 2HDM-a model in the $tan\beta$-$m_{a}$ plane.
The +1 $\sigma$ band of the observed exclusion contor for the 2HDM-a model in the $tan\beta$-$m_{a}$ plane.
The -1 $\sigma$ band of the observed exclusion contor for the 2HDM-a model in the $tan\beta$-$m_{a}$ plane.
The exclusion limits at 95% CL for the 2HDM+a model as a function of $\sin \theta$ for $m_{A,H^{\pm},H}$= 600GeV, $m_a$ = 200GeV, $\tan \beta$ = 1.0$.
The exclusion limits at 95% CL for the 2HDM+a model as a function of $\sin \theta$ for $m_{A,H^{\pm},H}$= 1000GeV, $m_a$ = 350GeV, $\tan \beta$ = 1.0$.
Breakdown of the dominant systematic uncertainties.
Event yields in the range of 120 $<m_{\gamma\gamma}<$ 130 GeV for data, signal models, the SM Higgs boson background and non-resonant background in each analysis category, for an integrated luminosity of $139$fb$^{-1}$.
Detailed background contributions from the SM Higgs boson and continuum background for each cut
Detailed contributions from the signals for each cut.
Acceptance times efficiency for several signals in each category.
A search is presented for the production of the Standard Model Higgs boson in association with a high-energy photon. With a focus on the vector-boson fusion process and the dominant Higgs boson decay into $b$-quark pairs, the search benefits from a large reduction of multijet background compared to more inclusive searches. Results are reported from the analysis of 132 fb$^{-1}$ of $pp$ collision data at $\sqrt{s}$=13 TeV collected with the ATLAS detector at the LHC. The measured Higgs boson signal yield in this final-state signature is $1.3 \pm 1.0$ times the Standard Model prediction. The observed significance of the Higgs boson signal above the background is 1.3 standard deviations, compared to an expected significance of 1.0 standard deviations.
Comparisons of data and simulated event distributions of the BDT input variable \(\Delta \eta_{jj}\) in the two \(m_{bb}\) sidebands after kinematic reweighting of the non-resonant \(b\bar{b}\gamma jj\) background. The data are shown as black points, and the background contributions are stacked in coloured histograms. The Higgs boson signal contribution is scaled up and represented by the dashed red line. The bottom panel in each plot shows the ratio of the data to the SM prediction, where the uncertainty band corresponds to the statistical uncertainty only.
Comparisons of data and simulated event distributions of the BDT input variable \(p_{\text{T}}^{\text{balance}}\) in the two \(m_{bb}\) sidebands after kinematic reweighting of the non-resonant \(b\bar{b}\gamma jj\) background. The data are shown as black points, and the background contributions are stacked in coloured histograms. The Higgs boson signal contribution is scaled up and represented by the dashed red line. The bottom panel in each plot shows the ratio of the data to the SM prediction, where the uncertainty band corresponds to the statistical uncertainty only.
The \(m_{bb}\) distributions in the HighBDT categories, overlaid with contributions from the \(H\gamma jj\) signal as well as the resonant \(Z\gamma jj\) and non-resonant \(b\bar{b} \gamma jj\) background fits. The combined \(\chi^2\) per degree of freedom is \(45.2/45\). The bottom panel in each plot presents the significance of the Higgs boson signal relative to the non-resonant \(b\bar{b} \gamma jj\) background in each bin.
The \(m_{bb}\) distributions in the MediumBDT categories, overlaid with contributions from the \(H\gamma jj\) signal as well as the resonant \(Z\gamma jj\) and non-resonant \(b\bar{b} \gamma jj\) background fits. The combined \(\chi^2\) per degree of freedom is \(45.2/45\). The bottom panel in each plot presents the significance of the Higgs boson signal relative to the non-resonant \(b\bar{b} \gamma jj\) background in each bin.
The \(m_{bb}\) distributions in the MediumBDT categories, overlaid with contributions from the \(H\gamma jj\) signal as well as the resonant \(Z\gamma jj\) and non-resonant \(b\bar{b} \gamma jj\) background fits. The combined \(\chi^2\) per degree of freedom is \(45.2/45\). The bottom panel in each plot presents the significance of the Higgs boson signal relative to the non-resonant \(b\bar{b} \gamma jj\) background in each bin.
Comparisons of data and simulated event distributions of the BDT input variables \(\Delta R (b1, \gamma)\) in the two \(m_{bb}\) sidebands after kinematic reweighting of the non-resonant \(b\bar{b}\gamma jj\) background. The data are shown as black points, and the background contributions are stacked in coloured histograms. The Higgs boson signal contribution is scaled up and represented by the dashed red line. The bottom panel in each plot shows the ratio between the data and the SM prediction, where the uncertainty band corresponds to the statistical uncertainty only.
Comparisons of data and simulated event distributions of the BDT input variables \(m_{jj}\) in the two \(m_{bb}\) sidebands after kinematic reweighting of the non-resonant \(b\bar{b}\gamma jj\) background. The data are shown as black points, and the background contributions are stacked in coloured histograms. The Higgs boson signal contribution is scaled up and represented by the dashed red line. The bottom panel in each plot shows the ratio between the data and the SM prediction, where the uncertainty band corresponds to the statistical uncertainty only.
Comparisons of data and simulated event distributions of the BDT input variables \(\Delta R (b2, \gamma)\) in the two \(m_{bb}\) sidebands after kinematic reweighting of the non-resonant \(b\bar{b}\gamma jj\) background. The data are shown as black points, and the background contributions are stacked in coloured histograms. The Higgs boson signal contribution is scaled up and represented by the dashed red line. The bottom panel in each plot shows the ratio between the data and the SM prediction, where the uncertainty band corresponds to the statistical uncertainty only.
Comparisons of data and simulated event distributions of the BDT input variables \(\text{centrality}(\gamma, j1, j2)\) in the two \(m_{bb}\) sidebands after kinematic reweighting of the non-resonant \(b\bar{b}\gamma jj\) background. The data are shown as black points, and the background contributions are stacked in coloured histograms. The Higgs boson signal contribution is scaled up and represented by the dashed red line. The bottom panel in each plot shows the ratio between the data and the SM prediction, where the uncertainty band corresponds to the statistical uncertainty only.
Comparisons of data and simulated event distributions of the BDT input variables \(\Delta \phi(b\bar{b}, jj)\) in the two \(m_{bb}\) sidebands after kinematic reweighting of the non-resonant \(b\bar{b}\gamma jj\) background. The data are shown as black points, and the background contributions are stacked in coloured histograms. The Higgs boson signal contribution is scaled up and represented by the dashed red line. The bottom panel in each plot shows the ratio between the data and the SM prediction, where the uncertainty band corresponds to the statistical uncertainty only.
Comparisons of data and simulated event distributions of the BDT input variables \(p_{\mathrm{T}}^{jj}\) in the two \(m_{bb}\) sidebands after kinematic reweighting of the non-resonant \(b\bar{b}\gamma jj\) background. The data are shown as black points, and the background contributions are stacked in coloured histograms. The Higgs boson signal contribution is scaled up and represented by the dashed red line. The bottom panel in each plot shows the ratio between the data and the SM prediction, where the uncertainty band corresponds to the statistical uncertainty only.
Comparisons of data and simulated event distributions of the BDT input variables \(\cos \theta\) in the two \(m_{bb}\) sidebands after kinematic reweighting of the non-resonant \(b\bar{b}\gamma jj\) background. The data are shown as black points, and the background contributions are stacked in coloured histograms. The Higgs boson signal contribution is scaled up and represented by the dashed red line. The bottom panel in each plot shows the ratio between the data and the SM prediction, where the uncertainty band corresponds to the statistical uncertainty only.
Comparisons of data and simulated event distributions of the BDT input variables \(\Delta R(b1,j1)\) in the two \(m_{bb}\) sidebands after kinematic reweighting of the non-resonant \(b\bar{b}\gamma jj\) background. The data are shown as black points, and the background contributions are stacked in coloured histograms. The Higgs boson signal contribution is scaled up and represented by the dashed red line. The bottom panel in each plot shows the ratio between the data and the SM prediction, where the uncertainty band corresponds to the statistical uncertainty only.
Two-particle long-range azimuthal correlations are measured in photonuclear collisions using 1.7 nb$^{-1}$ of 5.02 TeV Pb+Pb collision data collected by the ATLAS experiment at the LHC. Candidate events are selected using a dedicated high-multiplicity photonuclear event trigger, a combination of information from the zero-degree calorimeters and forward calorimeters, and from pseudorapidity gaps constructed using calorimeter energy clusters and charged-particle tracks. Distributions of event properties are compared between data and Monte Carlo simulations of photonuclear processes. Two-particle correlation functions are formed using charged-particle tracks in the selected events, and a template-fitting method is employed to subtract the non-flow contribution to the correlation. Significant nonzero values of the second- and third-order flow coefficients are observed and presented as a function of charged-particle multiplicity and transverse momentum. The results are compared with flow coefficients obtained in proton-proton and proton-lead collisions in similar multiplicity ranges, and with theoretical expectations. The unique initial conditions present in this measurement provide a new way to probe the origin of the collective signatures previously observed only in hadronic collisions.
The measured $v_2$ and $v_3$ charged-particle anisotropies as a function of charged-particle multiplicity in photonuclear collisions
The measured $v_2$ and $v_3$ charged-particle anisotropies as a function of charged-particle transverse momentum in photonuclear collisions
This paper presents a measurement of the production cross-section of a $Z$ boson in association with $b$-jets, in proton-proton collisions at $\sqrt{s} = 13$ TeV with the ATLAS experiment at the Large Hadron Collider using data corresponding to an integrated luminosity of 35.6 fb$^{-1}$. Inclusive and differential cross-sections are measured for events containing a $Z$ boson decaying into electrons or muons and produced in association with at least one or at least two $b$-jets with transverse momentum $p_\textrm{T}>$ 20 GeV and rapidity $|y| < 2.5$. Predictions from several Monte Carlo generators based on leading-order (LO) or next-to-leading-order (NLO) matrix elements interfaced with a parton-shower simulation and testing different flavour schemes for the choice of initial-state partons are compared with measured cross-sections. The 5-flavour number scheme predictions at NLO accuracy agree better with data than 4-flavour number scheme ones. The 4-flavour number scheme predictions underestimate data in events with at least one b-jet.
Measured fiducial cross sections for events with $Z(\rightarrow ll)\ge+1$ b-jets or with $Z(\rightarrow ll)\ge+2$ b-jets. The statistical uncertainties and the individual components of systematic uncertainty are given in each bin. Statistical uncertainties are bin-to-bin uncorrelated.
Differential fiducial cross section of the Z boson $p_{\text{T}}$ in events with $Z(\rightarrow ll)\ge+1$ b-jets. The statistical uncertainties and the individual components of systematic uncertainty are given in each bin. Statistical uncertainties are bin-to-bin uncorrelated.
Differential fiducial cross section of the leading b-jet $p_{\text{T}}$ in events with $Z(\rightarrow ll)\ge+1$ b-jets. The statistical uncertainties and the individual components of systematic uncertainty are given in each bin. Statistical uncertainties are bin-to-bin uncorrelated.
Differential fiducial cross section of the Z boson $|y|$ in events with $Z(\rightarrow ll)\ge+1$ b-jets. The statistical uncertainties and the individual components of systematic uncertainty are given in each bin. Statistical uncertainties are bin-to-bin uncorrelated.
Differential fiducial cross section of the leading b-jet $|y|$ in events with $Z(\rightarrow ll)\ge+1$ b-jets. The statistical uncertainties and the individual components of systematic uncertainty are given in each bin. Statistical uncertainties are bin-to-bin uncorrelated.
Differential fiducial cross section of the $\Delta \phi$ between Z boson and leading $b$-jet in events with $Z(\rightarrow ll)\ge+1$ b-jets. The statistical uncertainties and the individual components of systematic uncertainty are given in each bin. Statistical uncertainties are bin-to-bin uncorrelated.
Differential fiducial cross section of the $\Delta y$ between Z boson and leading $b$-jet in events with $Z(\rightarrow ll)\ge+1$ b-jets. The statistical uncertainties and the individual components of systematic uncertainty are given in each bin. Statistical uncertainties are bin-to-bin uncorrelated.
Differential fiducial cross section of the $\Delta R$ between Z boson and leading $b$-jet in events with $Z(\rightarrow ll)\ge+1$ b-jets. The statistical uncertainties and the individual components of systematic uncertainty are given in each bin. Statistical uncertainties are bin-to-bin uncorrelated.
Differential fiducial cross section of the $\Delta \phi$ between the first two leading $b$-jets in events with $Z(\rightarrow ll)\ge+2$ b-jets. The statistical uncertainties and the individual components of systematic uncertainty are given in each bin. Statistical uncertainties are bin-to-bin uncorrelated.
Differential fiducial cross section of the $\Delta y$ between the first two leading $b$-jets in events with $Z(\rightarrow ll)\ge+2$ b-jets. The statistical uncertainties and the individual components of systematic uncertainty are given in each bin. Statistical uncertainties are bin-to-bin uncorrelated.
Differential fiducial cross section of the $\Delta R$ between the first two leading $b$-jets in events with $Z(\rightarrow ll)\ge+2$ b-jets. The statistical uncertainties and the individual components of systematic uncertainty are given in each bin. Statistical uncertainties are bin-to-bin uncorrelated.
Differential fiducial cross section of the invariant mass of the first two leading $b$-jets in events with $Z(\rightarrow ll)\ge+2$ b-jets. The statistical uncertainties and the individual components of systematic uncertainty are given in each bin. Statistical uncertainties are bin-to-bin uncorrelated.
Differential fiducial cross section of the Z boson $p_{\text{T}}$ in events with $Z(\rightarrow ll)\ge+2$ b-jets. The statistical uncertainties and the individual components of systematic uncertainty are given in each bin. Statistical uncertainties are bin-to-bin uncorrelated.
Differential fiducial cross section of the $p_{\text{T}}$ of the first two leading $b$-jets in events with $Z(\rightarrow ll)\ge+2$ b-jets. The statistical uncertainties and the individual components of systematic uncertainty are given in each bin. Statistical uncertainties are bin-to-bin uncorrelated.
Differential fiducial cross section of the ratio between the $p_{\text{T}}$ and the invariant mass of the first two leading $b$-jets in events with $Z(\rightarrow ll)\ge+2$ b-jets. The statistical uncertainties and the individual components of systematic uncertainty are given in each bin. Statistical uncertainties are bin-to-bin uncorrelated.
A search for Higgs boson decays into a $Z$ boson and a light resonance in two-lepton plus jet events is performed, using a $pp$ collision dataset with an integrated luminosity of 139 fb$^{-1}$ collected at $\sqrt{s}=13$ TeV by the ATLAS experiment at the CERN LHC. The resonance considered is a light boson with a mass below 4 GeV from a possible extended scalar sector, or a charmonium state. Multivariate discriminants are used for the event selection and for evaluating the mass of the light resonance. No excess of events above the expected background is found. Observed (expected) 95$\% $ confidence-level upper limits are set on the Higgs boson production cross section times branching fraction to a $Z$ boson and the signal resonance, with values in the range 17 pb to 340 pb ($16^{+6}_{-5}$ pb to $320^{+130}_{-90}$ pb) for the different light spin-0 boson mass and branching fraction hypotheses, and with values of 110 pb and 100 pb ($100^{+40}_{-30}$ pb and $100^{+40}_{-30}$ pb) for the $\eta_c$ and $J/\psi$ hypotheses, respectively.
Observed number of data events and expected number of background events in the signal region.
Efficiencies of the MLP selection, complete selection and total expected signal yields for each signal sample, assuming B$(H\to Z(Q/a))=100\%$ and $\sigma(pp\to H) = \sigma_\text{SM}(pp\to H)$. Pythia 8 branching fractions of $a$ are assumed using a $\tan\beta$ value of 1. The MLP efficiencies, total efficiencies, and expected yields are determined using MC samples, with uncertainties due to MC sample statistics, except for the expected background yield. The expected background yield and its uncertainty is calculated as described in the main text of the paper.
Expected and observed 95% CL upper limits on $\sigma(pp\to H)B(H\to Za)/$pb. These results are quoted for $B(a\to gg)=100\%$ and $B(a\to s\bar{s})=100\%$ for each signal sample. The smaller (larger) quoted ranges around the expected limits represent $\pm 1\sigma$ ($\pm 2\sigma$) fluctuations.
Expected and observed 95% CL upper limits on $\sigma(pp\to H)B(H\to Z(\eta_c~\text{or}~J/\psi))/$pb. The smaller (larger) quoted ranges around the expected limits represent $\pm 1\sigma$ ($\pm 2\sigma$) fluctuations.
The prevalence of hadronic jets at the LHC requires that a deep understanding of jet formation and structure is achieved in order to reach the highest levels of experimental and theoretical precision. There have been many measurements of jet substructure at the LHC and previous colliders, but the targeted observables mix physical effects from various origins. Based on a recent proposal to factorize physical effects, this Letter presents a double-differential cross-section measurement of the Lund jet plane using 139 fb$^{-1}$ of $\sqrt{s}=13$ TeV proton-proton collision data collected with the ATLAS detector using jets with transverse momentum above 675 GeV. The measurement uses charged particles to achieve a fine angular resolution and is corrected for acceptance and detector effects. Several parton shower Monte Carlo models are compared with the data. No single model is found to be in agreement with the measured data across the entire plane.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for use in MC tuning.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 0.00 < ln(R/#DeltaR) < 0.33.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 0.33 < ln(R/#DeltaR) < 0.67.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 0.67 < ln(R/#DeltaR) < 1.00.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 1.00 < ln(R/#DeltaR) < 1.33.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 1.33 < ln(R/#DeltaR) < 1.67.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 1.67 < ln(R/#DeltaR) < 2.00.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 2.00 < ln(R/#DeltaR) < 2.33.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 2.33 < ln(R/#DeltaR) < 2.67.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 2.67 < ln(R/#DeltaR) < 3.00.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 3.00 < ln(R/#DeltaR) < 3.33.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 3.33 < ln(R/#DeltaR) < 3.67.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 3.67 < ln(R/#DeltaR) < 4.00.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 4.00 < ln(R/#DeltaR) < 4.33.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 0.69 < ln(1/z) < 0.97.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 0.97 < ln(1/z) < 1.25.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 1.25 < ln(1/z) < 1.52.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 1.52 < ln(1/z) < 1.80.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 1.80 < ln(1/z) < 2.08.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 2.08 < ln(1/z) < 2.36.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 2.36 < ln(1/z) < 2.63.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 2.63 < ln(1/z) < 2.91.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 2.91 < ln(1/z) < 3.19.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 3.19 < ln(1/z) < 3.47.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 3.47 < ln(1/z) < 3.74.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 3.74 < ln(1/z) < 4.02.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 4.02 < ln(1/z) < 4.30.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 4.30 < ln(1/z) < 4.57.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 4.57 < ln(1/z) < 4.85.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 4.85 < ln(1/z) < 5.13.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 5.13 < ln(1/z) < 5.41.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 5.41 < ln(1/z) < 5.68.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 5.68 < ln(1/z) < 5.96.
The summed covariance matrix of all systematic and statistical uncertainties associated with the measurement in bins of $\ln{(1/z)} \times \ln{(R/\Delta R)}$.
The summed covariance matrix of all statistical uncertainties associated with the measurement in bins of $\ln{(1/z)} \times \ln{(R/\Delta R)}$.
This paper presents measurements of the $W^+ \rightarrow \mu^+\nu$ and $W^- \rightarrow \mu^-\nu$ cross-sections and the associated charge asymmetry as a function of the absolute pseudorapidity of the decay muon. The data were collected in proton--proton collisions at a centre-of-mass energy of 8 TeV with the ATLAS experiment at the LHC and correspond to a total integrated luminosity of $20.2~\mbox{fb$^{-1}$}$. The precision of the cross-section measurements varies between 0.8% to 1.5% as a function of the pseudorapidity, excluding the 1.9% uncertainty on the integrated luminosity. The charge asymmetry is measured with an uncertainty between 0.002 and 0.003. The results are compared with predictions based on next-to-next-to-leading-order calculations with various parton distribution functions and have the sensitivity to discriminate between them.
The correction factors, $C_{W^±,i}$ with their associated systematic uncertainties as a function of $|\eta_{\mu}|$, for $W^+$ and $W^−$
The integrated global correction factor $C_{W^±}$, for $W^+$ and $W^−$
Cross-sections (differential in $\eta_{\mu}$) and asymmetry, as a function of $|\eta_{\mu}|$). The central values are provided along with the statistical and dominant systematic uncertainties: the data statistical uncertainty (Data Stat.), the $E_T^{\textrm{miss}}$ uncertainty, the uncertainties related to muon reconstruction (Muon Reco.), those related to the background, those from MC statistics (MC Stat.), and modelling uncertainties. The uncertainties of the cross-sections are given in percent and those of the asymmetry as an absolute difference from the nominal.
The measured fiducial production cross-sections times branching ratio for $W^+\rightarrow\mu^+\nu$ and $W^-\rightarrow\mu^-\bar{\nu}$, their sum, and their ratio for data
The measured fiducial production cross-sections times branching ratio for $W^+\rightarrow\mu^+ u$ and $W^-\rightarrow\mu^-\bar{\nu}$, their sum, and their ratio for the predictions from DYNNLO (CT14 NNLO PDF set)
Size of the $W^{+}$ the cross-section (differential in $\eta_{\mu}$, as a function of $|\eta_{\mu}|$. The central values are provided along with the statistical and systematic uncertainties together with the sign information. gThe uncertainties are given in percent.
Size of the $W^{+}$ the cross-section (differential in $\eta_{\mu}$, as a function of $|\eta_{\mu}|$. The central values are provided along with the statistical and systematic uncertainties together with the sign information. gThe uncertainties are given in percent.
Size of the asymmetry as a function of $|\eta_{\mu}|$. The central values are provided along with the statistical and systematic uncertainties together with the sign information. The uncertainties are given as an absolute difference from the nominal.
A test of CP invariance in Higgs boson production via vector-boson fusion is performed in the $H\rightarrow\tau\tau$ decay channel. This test uses the Optimal Observable method and is carried out using 36.1 $\mathrm{fb}^{-1}$ of $\sqrt{s}$ = 13 TeV proton$-$proton collision data collected by the ATLAS experiment at the LHC. Contributions from CP-violating interactions between the Higgs boson and electroweak gauge bosons are described by an effective field theory, in which the parameter $\tilde{d}$ governs the strength of CP violation. No sign of CP violation is observed in the distributions of the Optimal Observable, and $\tilde{d}$ is constrained to the interval $[-0.090, 0.035]$ at the 68% confidence level (CL), compared to an expected interval of $\tilde{d} \in [-0.035,0.033]$ based upon the Standard Model prediction. No constraints can be set on $\tilde{d}$ at 95% CL, while an expected 95% CL interval of $\tilde{d} \in [-0.21,0.15]$ for the Standard Model hypothesis was expected.
Post-fit BDT distributions after the VBF event selection for the $\tau_{\mathrm{lep}}\tau_{\mathrm{lep}}$ SF analysis channel. The VBF signal is shown for $\mu = 0.73$ and $\tilde d = -0.01$. ''Other bkg'' denotes all background contributions not listed explicitly in the legend. The size of the combined statistical, experimental, and theoretical uncertainties is given. The exact value of the $p_{\mathrm{T}}$ cut on the leptons depends on the trigger.
Post-fit BDT distributions after the VBF event selection for the $\tau_{\mathrm{lep}}\tau_{\mathrm{lep}}$ DF analysis channel. The VBF signal is shown for $\mu = 0.73$ and $\tilde d = -0.01$. ''Other bkg'' denotes all background contributions not listed explicitly in the legend. The size of the combined statistical, experimental, and theoretical uncertainties is given.
Post-fit BDT distributions after the VBF event selection for the $\tau_{\mathrm{lep}}\tau_{\mathrm{had}}$ analysis channel. The VBF signal is shown for $\mu = 0.73$ and $\tilde d = -0.01$. ''Other bkg'' denotes all background contributions not listed explicitly in the legend. The size of the combined statistical, experimental, and theoretical uncertainties is given. The exact value of the $p_{\mathrm{T}}$ cut on the leading lepton depends on the trigger.
Post-fit BDT distributions after the VBF event selection for the $\tau_{\mathrm{had}}\tau_{\mathrm{had}}$ analysis channel. The VBF signal is shown for $\mu = 0.73$ and $\tilde d = -0.01$. ''Other bkg'' denotes all background contributions not listed explicitly in the legend. The size of the combined statistical, experimental, and theoretical uncertainties is given.
Post-fit $m_{\tau\tau}^{\mathrm{MMC}}$ distributions in the low BDT score CR for the $\tau_{\mathrm{lep}}\tau_{\mathrm{lep}}$ SF analysis channel. ''Other bkg'' denotes all background contributions not listed explicitly in the legend. The size of the combined statistical, experimental, and theoretical uncertainties is given. The exact value of the $p_{\mathrm{T}}$ cut on the leptons depends on the trigger.
Post-fit $m_{\tau\tau}^{\mathrm{MMC}}$ distributions in the low BDT score CR for the $\tau_{\mathrm{lep}}\tau_{\mathrm{lep}}$ DF analysis channel. ''Other bkg'' denotes all background contributions not listed explicitly in the legend. The size of the combined statistical, experimental, and theoretical uncertainties is given.
Post-fit $m_{\tau\tau}^{\mathrm{MMC}}$ distributions in the low BDT score CR for the $\tau_{\mathrm{lep}}\tau_{\mathrm{had}}$ analysis channel. ''Other bkg'' denotes all background contributions not listed explicitly in the legend. The size of the combined statistical, experimental, and theoretical uncertainties is given. The exact value of the $p_{\mathrm{T}}$ cut on the leading lepton depends on the trigger.
Post-fit $m_{\tau\tau}^{\mathrm{MMC}}$ distributions in the low BDT score CR for the $\tau_{\mathrm{had}}\tau_{\mathrm{had}}$ analysis channel. ''Other bkg'' denotes all background contributions not listed explicitly in the legend. The size of the combined statistical, experimental, and theoretical uncertainties is given.
Post-fit Optimal Observable distributions in the low BDT score CR for the $\tau_{\mathrm{lep}}\tau_{\mathrm{lep}}$ SF analysis channel. ''Other bkg'' denotes all background contributions not listed explicitly in the legend. The size of the combined statistical, experimental, and theoretical uncertainties is given. The exact value of the $p_{\mathrm{T}}$ cut on the leptons depends on the trigger.
Post-fit Optimal Observable distributions in the low BDT score CR for the $\tau_{\mathrm{lep}}\tau_{\mathrm{lep}}$ DF analysis channel. ''Other bkg'' denotes all background contributions not listed explicitly in the legend. The size of the combined statistical, experimental, and theoretical uncertainties is given.
Post-fit Optimal Observable distributions in the low BDT score CR for the $\tau_{\mathrm{lep}}\tau_{\mathrm{had}}$ analysis channel. ''Other bkg'' denotes all background contributions not listed explicitly in the legend. The size of the combined statistical, experimental, and theoretical uncertainties is given. The exact value of the $p_{\mathrm{T}}$ cut on the leading lepton depends on the trigger.
Post-fit Optimal Observable distributions in the low BDT score CR for the $\tau_{\mathrm{had}}\tau_{\mathrm{had}}$ analysis channel. ''Other bkg'' denotes all background contributions not listed explicitly in the legend. The size of the combined statistical, experimental, and theoretical uncertainties is given.
Post-fit distributions of the event yields as a function of the Optimal Observable in the SR for the $\tau_{\mathrm{lep}}\tau_{\mathrm{lep}}$ SF analysis channel. The values of $\tilde d$, the signal strength $\mu$, the normalization of background processes, and nuisance parameters for the event yield prediction are set to those which minimize the NLL. The size of the combined statistical, experimental and theoretical uncertainties is given.
Post-fit distributions of the event yields as a function of the Optimal Observable in the SR for the $\tau_{\mathrm{lep}}\tau_{\mathrm{lep}}$ DF analysis channel. The values of $\tilde d$, the signal strength $\mu$, the normalization of background processes, and nuisance parameters for the event yield prediction are set to those which minimize the NLL. The size of the combined statistical, experimental and theoretical uncertainties is given.
Post-fit distributions of the event yields as a function of the Optimal Observable in the SR for the $\tau_{\mathrm{lep}}\tau_{\mathrm{had}}$ analysis channel. The values of $\tilde d$, the signal strength $\mu$, the normalization of background processes, and nuisance parameters for the event yield prediction are set to those which minimize the NLL. The size of the combined statistical, experimental and theoretical uncertainties is given. The exact value of the $p_{\mathrm{T}}$ cut on the leading lepton depends on the trigger.
Post-fit distributions of the event yields as a function of the Optimal Observable in the SR for the $\tau_{\mathrm{had}}\tau_{\mathrm{had}}$ analysis channel. The values of $\tilde d$, the signal strength $\mu$, the normalization of background processes, and nuisance parameters for the event yield prediction are set to those which minimize the NLL. The size of the combined statistical, experimental and theoretical uncertainties is given.
The observed $\Delta\mathrm{NLL}$ curve as a function of $\tilde d$ values. For comparison, expected $\Delta\mathrm{NLL}$ curves are also shown. The constraints on the nuisance parameters and normalization factors are first determined in a CR-only fit, and then a fit to pseudo-data corresponding to these nuisance parameters, normalization factors, and to $\tilde d=0, \mu = 1$ or $\tilde d =0, \mu = 0.73$ is performed to obtain these $\Delta\mathrm{NLL}$ curves. Moreover, a pre-fit expected $\Delta\mathrm{NLL}$ is shown, using pseudo-data corresponding to $\tilde d =0$ and $\mu = 1$ in the signal and control regions.
The expected $\Delta\mathrm{NLL}$ curves comparing the sensitivity of the fit with and without systematic uncertainties. For comparison, other curves are shown which remove the effect of jet-based systematic uncertainties, $\tau$-based systematic uncertainties, and MC statistical uncertainties.
The observed $\Delta\mathrm{NLL}$ curves for each analysis channel as a function of $\tilde d$, compared to the combined result. For the individual analysis channel $\Delta\mathrm{NLL}$ curves, only event yield information in the other SRs is used, ensuring that the Optimal Observable distributions in the other SRs do not influence the preferred value of $\tilde d$. The signal strength is constrained to be positive in these individual channel $\Delta\mathrm{NLL}$ curves. The exact value of the $p_{\mathrm{T}}$ cut on the leading lepton depends on the trigger.
Post-fit BDT distributions in the top-quark CR for the $\tau_{\mathrm{lep}}\tau_{\mathrm{lep}}$ SF channel. The size of the combined statistical, experimental, and theoretical uncertainties is given. The exact value of the $p_{\mathrm{T}}$ cut on the leptons depends on the trigger.
Post-fit BDT distributions in the top-quark CR for the $\tau_{\mathrm{lep}}\tau_{\mathrm{lep}}$ DF channel. The size of the combined statistical, experimental, and theoretical uncertainties is given.
Post-fit BDT distributions in the $Z\to \ell\ell$ CR for the $\tau_{\mathrm{lep}}\tau_{\mathrm{lep}}$ SF analysis channel. The size of the combined statistical, experimental, and theoretical uncertainties is given. The exact value of the $p_{\mathrm{T}}$ cut on the leptons depends on the trigger.
Post-fit Optimal Observable distributions in the top-quark CR for the $\tau_{\mathrm{lep}}\tau_{\mathrm{lep}}$ SF channel. The size of the combined statistical, experimental, and theoretical uncertainties is given. The exact value of the $p_{\mathrm{T}}$ cut on the leptons depends on the trigger.
Post-fit Optimal Observable distributions in the top-quark CR for the $\tau_{\mathrm{lep}}\tau_{\mathrm{lep}}$ DF channel. The size of the combined statistical, experimental, and theoretical uncertainties is given.
Post-fit Optimal Observable distributions in the $Z\to \ell\ell$ CR for the $\tau_{\mathrm{lep}}\tau_{\mathrm{lep}}$ SF analysis channel. The size of the combined statistical, experimental, and theoretical uncertainties is given. The exact value of the $p_{\mathrm{T}}$ cut on the leptons depends on the trigger.
Post-fit distribution of weighted event yields as a function of the Optimal Observable for all four SRs combined. The contributions of the different SRs are weighted by a factor of ln(1 + S/B), where S and B are the post-fit expected numbers of signal and background events in that region, respectively. The size of the combined statistical, experimental, and theoretical uncertainties is given.
A search for new resonances decaying into a pair of jets is reported using the dataset of proton-proton collisions recorded at $\sqrt{s}=13$ TeV with the ATLAS detector at the Large Hadron Collider between 2015 and 2018, corresponding to an integrated luminosity of 139 fb$^{-1}$. The distribution of the invariant mass of the two leading jets is examined for local excesses above a data-derived estimate of the Standard Model background. In addition to an inclusive dijet search, events with jets identified as containing $b$-hadrons are examined specifically. No significant excess of events above the smoothly falling background spectra is observed. The results are used to set cross-section upper limits at 95% confidence level on a range of new physics scenarios. Model-independent limits on Gaussian-shaped signals are also reported. The analysis looking at jets containing $b$-hadrons benefits from improvements in the jet flavour identification at high transverse momentum, which increases its sensitivity relative to the previous analysis beyond that expected from the higher integrated luminosity.
The probability of an event to pass the b-tagging requirement after the rest of the event selection, shown as a function of the resonance mass and for the 1b and 2b analysis categories.
Dijet invariant mass distribution for the inclusive category with |y*| < 0.6.
Dijet invariant mass distribution for the inclusive category with |y*| < 1.2.
Dijet invariant mass distribution for the category with at least one b-tagged jet.
Dijet invariant mass distribution for the category with both jets b-tagged.
The 95% CL upper limits on the cross-section times acceptance times branching ratio into two jets as a function of the mass of q* signal.
The 95% CL upper limits on the cross-section times acceptance times branching ratio into two jets as a function of the mass of QBH signal.
The 95% CL upper limits on the cross-section times acceptance times branching ratio into two jets as a function of the mass of W' signal.
The 95% CL upper limits on the cross-section times acceptance times branching ratio into two jets as a function of the mass of W* signal.
The upper limits on the DM mediator Z' signal at 95% CL from the inclusive category. The 95% CL upper limits are set on the universal quark coupling $g_q$ as a function of the Z' mass.
The 95% CL upper limit on the cross-section times acceptance times b-tagging efficiency times branching ratio as a function of the mass of the b* signal.
The 95% CL upper limit on the cross-section times acceptance times b-tagging efficiency times branching ratio as a function of the signal mass in the DM mediator Z' with $g_q$ = 0.25 model.
The 95% CL upper limit on the cross-section times acceptance times b-tagging efficiency times branching ratio as a function of the signal mass in the SSM Z' model.
The 95% CL upper limit on the cross-section times acceptance times b-tagging efficiency times branching ratio as a function of the signal mass in the graviton with $k/\overline{M}_{PL}=0.2$ model.
The 95% CL upper limit on the cross-section times kinematic acceptance times branching ratio for resonances with a generic Gaussian shape, as a function of the Gaussian mean mass in the inclusive category. Different widths, from 0% up to 15% of the signal mass, are considered. Gaussian-shape signals with 0% widths correspond to signal widths smaller than the experimental resolution. For a Gaussian-shaped signal with a relative width of 15%, the limits are truncated at high mass when the broad signal starts to overlap the upper end of the mass spectrum.
The 95% CL upper limit on the cross-section times kinematic acceptance times b-tagging efficiency times branching ratio for resonances with a generic Gaussian shape, as a function of the Gaussian mean mass in the 1 b category. Different widths, from 0% up to 15% of the signal mass, are considered. Gaussian-shape signals with 0% widths correspond to signal widths smaller than the experimental resolution. For a Gaussian-shaped signal with a relative width of 15%, the limits are truncated at high mass when the broad signal starts to overlap the upper end of the mass spectrum.
The 95% CL upper limit on the cross-section times kinematic acceptance times b-tagging efficiency times branching ratio for resonances with a generic Gaussian shape, as a function of the Gaussian mean mass in the 2 b category. Different widths, from 0% up to 15% of the signal mass, are considered. Gaussian-shape signals with 0% widths correspond to signal widths smaller than the experimental resolution. For a Gaussian-shaped signal with a relative width of 15%, the limits are truncated at high mass when the broad signal starts to overlap the upper end of the mass spectrum.
The expected 95% CL upper limits on the cross-section times acceptance times b-tagging efficiency times branching ratio as a function of the DM mediator Z' mass for the current and previous iterations of the analysis. The upper limit of the previous result was obtained with the Bayesian method and is also shown scaled to the 139 fb$^{-1}$ integrated luminosity of the current result to illustrate the effect of the analysis improvements.
Acceptance for the QBH, Q* and W' benchmark signal models in the inclusive category, as a function of the simulated mass.
Acceptance for the DM Z' benchmark signal model for various $g_q$ coupling parameters in the inclusive category, as a function of the simulated mass.
Acceptance for the W* benchmark signal model in the inclusive category, as a function of the simulated mass.
Acceptance times b-tagging efficiency for the b* benchmark signal model in the 1b category, as a function of the simulated mass.
Acceptance times b-tagging efficiency for the DM Z' with $g_q$=0.25, SSM Z' and graviton with $k/\overline{M}_{PL}=0.2$ benchmark signal models in the 2b category, as a function of the simulated mass.
The expected 95% CL upper limits on the cross-section times branching ratio as a function of the DM mediator Z' mass for the current and previous iterations of the analysis. The upper limit of the previous result was obtained with the Bayesian method and is also shown scaled to the 139 fb$^{-1}$ integrated luminosity of the current result to illustrate the effect of the analysis improvements. The current b-tagging requirement is tighter than the previous one for high-$p_T$ jets, resulting in a data sample with limited size for mass above 4 TeV. The background rejection, instead, has improved significantly across the entire mass spectrum inspected by the analysis.
Results of a search for new particles decaying into eight or more jets and moderate missing transverse momentum are presented. The analysis uses 139 fb$^{-1}$ of proton$-$proton collision data at $\sqrt{s} = 13$ TeV collected by the ATLAS experiment at the Large Hadron Collider between 2015 and 2018. The selection rejects events containing isolated electrons or muons, and makes requirements according to the number of $b$-tagged jets and the scalar sum of masses of large-radius jets. The search extends previous analyses both in using a larger dataset and by employing improved jet and missing transverse momentum reconstruction methods which more cleanly separate signal from background processes. No evidence for physics beyond the Standard Model is found. The results are interpreted in the context of supersymmetry-inspired simplified models, significantly extending the limits on the gluino mass in those models. In particular, limits on the gluino mass are set at 2 TeV when the lightest neutralino is nearly massless in a model assuming a two-step cascade decay via the lightest chargino and second-lightest neutralino.
Post-fit yields for data and prediction in each of the multi-bin signal regions for the 8 jet regions.
Post-fit yields for data and prediction in each of the multi-bin signal regions for the 9 jet regions.
Post-fit yields for data and prediction in each of the multi-bin signal regions for the 10 jet regions.
Post-fit yields for data and prediction in each of the single-bin signal regions of the analysis.
Observed 95% confidence level limit for the two-step signal grid.
Observed 95% confidence level limit for the two-step signal grid with the signal cross section increased by one sigma.
Observed 95% confidence level limit for the two-step signal grid with the signal cross section decreased by one sigma.
Expected 95% confidence level limit for the two-step signal grid.
Expected 95% confidence level limit for the two-step signal grid plus one sigma from experimental systematics.
Expected 95% confidence level limit for the two-step signal grid minus one sigma from experimental systematics.
Observed 95% confidence level limit for the Gtt signal grid.
Observed 95% confidence level limit for the Gtt signal grid with the signal cross section increased by one sigma.
Observed 95% confidence level limit for the Gtt signal grid with the signal cross section decreased by one sigma.
Expected 95% confidence level limit for the Gtt signal grid.
Expected 95% confidence level limit for the Gtt signal grid plus one sigma from experimental systematics.
Expected 95% confidence level limit for the Gtt signal grid minus one sigma from experimental systematics.
Observed 95% confidence level limit for the RPV signal grid.
Observed 95% confidence level limit for the RPV signal grid with the signal cross section increased by one sigma.
Observed 95% confidence level limit for the RPV signal grid with the signal cross section decreased by one sigma.
Expected 95% confidence level limit for the RPV signal grid.
Expected 95% confidence level limit for the RPV signal grid plus one sigma from experimental systematics.
Expected 95% confidence level limit for the RPV signal grid minus one sigma from experimental systematics.
Observed 95% confidence level limit for the two-step signal grid.
Expected 95% confidence level limit for the two-step signal grid.
Observed 95% confidence level limit for the Gtt signal grid.
Expected 95% confidence level limit for the Gtt signal grid.
Observed 95% confidence level limit for the RPV signal grid.
Expected 95% confidence level limit for the RPV signal grid.
$\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ distribution in the signal region SR-10ij50-0ib-MJ340. Two benchmark signal models are shown along with the background yields. These models, each representing a single mass point, are labelled 'RPV' with $(m_{\tilde{g}}, m_{\tilde{t}}) = (1600, 600) \, \mathrm{GeV}$ and 'two-step' with $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
$\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ distribution in the signal region SR-12ij50-2ib. Two benchmark signal models are shown along with the background yields. These models, each representing a single mass point, are labelled 'RPV' with $(m_{\tilde{g}}, m_{\tilde{t}}) = (1600, 600) \, \mathrm{GeV}$ and 'two-step' with $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
$\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ distribution in the signal region SR-9ij80-0ib. Two benchmark signal models are shown along with the background yields. These models, each representing a single mass point, are labelled 'RPV' with $(m_{\tilde{g}}, m_{\tilde{t}}) = (1600, 600) \, \mathrm{GeV}$ and 'two-step' with $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-8ij50-0ib-MJ500. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-9ij50-0ib-MJ340. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-10ij50-0ib-MJ340. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-10ij50-0ib-MJ500. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-10ij50-1ib-MJ500. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-11ij50-0ib. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-12ij50-2ib. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-9ij80-0ib. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
Acceptance for the signal region SR-8ij50-0ib-MJ500 showing the acceptance for the complete two-step signal grid.
Efficiency for the signal region SR-8ij50-0ib-MJ500 showing the efficiency for the complete two-step signal grid.
Acceptance for the signal region SR-9ij50-0ib-MJ340 showing the acceptance for the complete two-step signal grid.
Efficiency for the signal region SR-9ij50-0ib-MJ340 showing the efficiency for the complete two-step signal grid.
Acceptance for the signal region SR-10ij50-0ib-MJ340 showing the acceptance for the complete two-step signal grid.
Efficiency for the signal region SR-10ij50-0ib-MJ340 showing the efficiency for the complete two-step signal grid.
Acceptance for the signal region SR-10ij50-0ib-MJ500 showing the acceptance for the complete two-step signal grid.
Efficiency for the signal region SR-10ij50-0ib-MJ500 showing the efficiency for the complete two-step signal grid.
Acceptance for the signal region SR-10ij50-1ib-MJ500 showing the acceptance for the complete two-step signal grid.
Efficiency for the signal region SR-10ij50-1ib-MJ500 showing the efficiency for the complete two-step signal grid.
Acceptance for the signal region SR-11ij50-0ib showing the acceptance for the complete two-step signal grid.
Efficiency for the signal region SR-11ij50-0ib showing the efficiency for the complete two-step signal grid.
Acceptance for the signal region SR-12ij50-2ib showing the acceptance for the complete two-step signal grid.
Efficiency for the signal region SR-12ij50-2ib showing the efficiency for the complete two-step signal grid.
Acceptance for the signal region SR-9ij80-0ib showing the acceptance for the complete two-step signal grid.
Efficiency for the signal region SR-9ij80-0ib showing the efficiency for the complete two-step signal grid.
The normalisation factors for the dominant backgrounds of the analysis in each of the multi-bin and single-bin regions.
Post-fit yields for data and prediction in each of the single-bin validation regions to test the $N_{\mathrm{jet}}$ extraction.
Post-fit yields for data and prediction in each of the single-bin validation regions to test the $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ extrapolation.
Post-fit yields for data and prediction in each of the multi-bin validation regions to test the $N_{\mathrm{jet}}$ extraction.
Post-fit yields for data and prediction in each of the multi-bin validation regions to test the $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ extrapolation.
The observed Cls from the best expected signal regions for the two-step decay.
The observed Cls from the best expected signal regions for the Gtt decay.
The observed Cls from the best expected signal regions for the RPV decay.
Number of events in each signal region broken down by background type and the number of observed data events.
From left to right; the $95\%$ CL upper limits on the visible cross section (${\langle \epsilon\sigma \rangle}^{95}_{obs}$) and on the number of signal events. Next is the $95\%$ CL upper limit on the number of signal events, given the expected number of background events. The last two columns show the confidence level for the background only hypothesis ($CL_{b}$) and the dicovery $p$-value along with the Gaussian significance (Z).
Visualisation of the highest jet multiplicity event selected in signal regions targeting long cascade decays of pair-produced gluinos. This event was recorded by ATLAS on 23 October 2016, and contains 16 jets, illustrated by cones. Yellow blocks represent the calorimeter energy measured in noise-suppressed clusters. Of the reconstructed jets, 13 (11) have transverse momenta above 50 GeV (80 GeV), with 3 (2) being b-tagged. The leading jet has a transverse momentum of 507 GeV, and the sum of jet transverse momenta $H_T=2.9$ TeV. A value of 343 GeV is observed for the $E_{T}^{miss}$, whose direction is shown by the dashed red line, producing a significance $S(E_{T}^{miss})=6.4$. The sum of the masses of large-radius jets is evaluated as $M_{J}^{\Sigma}=1070$ GeV.
Visualisation of the highest jet multiplicity event selected in a control region used to make predictions of the background from multijet production. This event was recorded by ATLAS on 18 July 2018, and contains 19 jets, illustrated by cones. Yellow blocks represent the calorimeter energy measured in in noise-suppressed clusters. Of the reconstructed jets, 16 (10) have transverse momenta above 50 GeV (80 GeV). No jets were b-tagged. The leading et has a transverse momentum of 371 GeV, and the sum of jet transverse momenta $H_T=2.2$ TeV. A value of 8 GeV is observed for the $E_{T}^{miss}$, whose direction is shown by the dashed red line, producing a significance $S(E_{T}^{miss})=0.2$. The sum of the masses of large-radius jets is evaluated as $M_{J}^{\Sigma}=767$ GeV.
This paper reports on a search for heavy resonances decaying into $WW$, $ZZ$ or $WZ$ using proton-proton collision data at a centre-of-mass energy of $\sqrt{s}=13$ TeV. The data, corresponding to an integrated luminosity of 139 $\mathrm{fb^{-1}}$, were recorded with the ATLAS detector from 2015 to 2018 at the Large Hadron Collider. The search is performed for final states in which one $W$ or $Z$ boson decays leptonically, and the other $W$ boson or $Z$ boson decays hadronically. The data are found to be described well by expected backgrounds. Upper bounds on the production cross sections of heavy scalar, vector or tensor resonances are derived in the mass range 300-5000 GeV within the context of Standard Model extensions with warped extra dimensions or including a heavy vector triplet. Production through gluon-gluon fusion, Drell-Yan or vector-boson fusion are considered, depending on the assumed model.
Selection acceptance times efficiency for the 0 leptons signal events from MC simulations as a function of the resonance mass for ggF/DY production.
Selection acceptance times efficiency for the 0 leptons signal events from MC simulations as a function of the resonance mass for VBF production.
Selection acceptance times efficiency for the 1 lepton signal events from MC simulations as a function of the resonance mass for ggF/DY production.
Selection acceptance times efficiency for the 1 lepton signal events from MC simulations as a function of the resonance mass for VBF production.
Selection acceptance times efficiency for the 2 leptons signal events from MC simulations as a function of the resonance mass for ggF/DY production.
Selection acceptance times efficiency for the 2 leptons signal events from MC simulations as a function of the resonance mass for VBF production.
The fractions of signal events passing the VBF requirement on the RNN score as functions of the resonance mass for both VBF and ggF production. Information on the RNN model, such as the architecture, network weights and features scaling files are provided as additional resources.
Upper 95% CLs limits on the ggF production cross section of Radions in their $WW+ZZ$ decays as a function of the resonance mass.
Upper 95% CLs limits on the VBF production cross section of Radions in their $WW+ZZ$ decays as a function of the resonance mass.
Upper 95% CLs limits on the DY production cross section of HVT $W'$ in their $WZ$ decays as a function of the resonance mass.
Upper 95% CLs limits on the VBF production cross section of HVT $W'$ in their $WZ$ decays as a function of the resonance mass.
Upper 95% CLs limits on the DY production cross section of HVT $Z'$ in their $WW$ decays as a function of the resonance mass.
Upper 95% CLs limits on the VBF production cross section of HVT $Z'$ in their $WW$ decays as a function of the resonance mass.
Upper 95% CLs limits on the ggF production cross section of Gravitons in their $WW+ZZ$ decays as a function of the resonance mass.
Upper 95% CLs limits on the VBF production cross section of Gravitons in their $WW+ZZ$ decays as a function of the resonance mass.
Upper 95% CLs limits on the ggF production cross section of Radions in their $WW$ decays as a function of the resonance mass.
Upper 95% CLs limits on the VBF production cross section of Radions in their $WW$ decays as a function of the resonance mass.
Upper 95% CLs limits on the ggF production cross section of Radions in their $ZZ$ decays as a function of the resonance mass.
Upper 95% CLs limits on the VBF production cross section of Radions in their $ZZ$ decays as a function of the resonance mass.
Upper 95% CLs limits on the ggF production cross section of Gravitons in their $WW$ decays as a function of the resonance mass.
Upper 95% CLs limits on the VBF production cross section of Gravitons in their $WW$ decays as a function of the resonance mass.
Upper 95% CLs limits on the ggF production cross section of Gravitons in their $ZZ$ decays as a function of the resonance mass.
Upper 95% CLs limits on the VBF production cross section of Gravitons in their $ZZ$ decays as a function of the resonance mass.
Higgs boson properties are studied in the four-lepton decay channel (where lepton = $e$, $\mu$) using 139 fb$^{-1}$ of proton-proton collision data recorded at $\sqrt{s}$ = 13 TeV by the ATLAS experiment at the Large Hadron Collider. The inclusive cross-section times branching ratio for $H\to ZZ^*$ decay is measured to be $1.34 \pm 0.12$ pb for a Higgs boson with absolute rapidity below 2.5, in good agreement with the Standard Model prediction of $1.33 \pm 0.08$ pb. Cross-sections times branching ratio are measured for the main Higgs boson production modes in several exclusive phase-space regions. The measurements are interpreted in terms of coupling modifiers and of the tensor structure of Higgs boson interactions using an effective field theory approach. Exclusion limits are set on the CP-even and CP-odd `beyond the Standard Model' couplings of the Higgs boson to vector bosons, gluons and top quarks.
The expected number of SM Higgs boson events with a mass $m_{H}$= 125 GeV for an integrated luminosity of 139 fb$^{-1}$ at $\sqrt{s}$=13 TeV in each reconstructed event signal (115 < $m_{4l}$< 130 GeV) and sideband ($m_{4l}$ in 105-115 GeV or 130-160 GeV for $ZZ^{*}$, 130-350 GeV for $tXX$) category, shown separately for each production bin of the Production Mode Stage. The ggF and $bbH$ yields are shown separately but both contribute to the same (ggF)production bin, and $ZH$ and $WH$ are reported separately but are merged together for the final result. Statistical and systematic uncertainties, including those for total SM cross-section predictions, are added in quadrature. Contributions that are below 0.2% of the total signal in each reconstructed event category are not shown and are replaced by -.
The impact of the dominant systematic uncertainties (in percent) on the cross-sections in production bins of the Production Mode Stage and the Reduced Stage 1.1. Similar sources of systematic uncertainties are grouped together in luminosity (Lumi.),electron/muon reconstruction and identification efficiencies and pile up modelling ($e$, $\mu$, pile up), jet energy scale/resolution and $b$-tagging efficiencies (Jets, flav. tag), uncertainties in reducible background (reducible bkg), theoretical uncertainties in $ZZ^{*}$ background and $tXX$ background, and theoretical uncertainties in the signal due to parton distribution function (PDF), QCD scale (QCD) and parton showering algorithm (Shower). The uncertainties are rounded to the nearest 0.5%, except for the luminosity uncertainty, which is measured to be 1.7% and increases for the $VH$ signal processes due to the simulation-based normalisation of the $VVV$ background. The uncertainties that are below 0.5% are not shown and replaced by -.
The expected and the observed (post-fit) the four-lepton invariant mass distribution for the selected Higgs boson candidates, shown for an integrated luminosity of 139fb$^{-1}$ at $\sqrt{s}$=13TeV. The SM Higgs boson signal is assumed tohave a mass $m_{H}$= 125GeV.
The expected (pre-fit) and observed numbers of events for an integrated luminosity of 139 fb$^{-1}$ at $\sqrt{s}$=13 TeV in the signal region 115 < $m_{4l}$< 130 GeV and sideband region $m_{4l}$ in 105-115 GeV or 130-160 GeV (350 GeV for $tXX$-enriched) in each reconstructed event category assuming the SM Higgs boson signal with a mass $m_{H}$= 125 GeV. Combined statistical and systematic uncertainties are included for the predictions. Expected contributions that are below 0.2% of the total yield in each reconstructed event category are not shown and replaced by -.
The expected and the observed (post-fit) the jet multiplicity distribution after the inclusive event selection for an integrated luminosity of 139fb$^{-1}$ at $\sqrt{s}$=13TeV. The SM Higgs boson signal is assumed to have a mass $m_{H}$=125 GeV.
The expected and the observed (post-fit) the four-lepton transverse momentum distribution for events with zero jets, after the inclusive event selection for an integrated luminosity of 139fb$^{-1}$ at $\sqrt{s}$=13TeV. The SM Higgs boson signal is assumed to have a mass $m_{H}$=125 GeV.
The expected and the observed (post-fit) the four-lepton transverse momentum distribution for events with one jet, after the inclusive event selection for an integrated luminosity of 139fb$^{-1}$ at $\sqrt{s}$=13TeV. The SM Higgs boson signal is assumed to have a mass $m_{H}$=125 GeV.
The expected and the observed (post-fit) the four-lepton transverse momentum distribution for events with at least two jets, after the inclusive event selection for an integrated luminosity of 139fb$^{-1}$ at $\sqrt{s}$=13TeV. The SM Higgs boson signal is assumed to have a mass $m_{H}$=125 GeV.
The expected and the observed (post-fit) the dijet invariant mass distribution for events with at least two jets, after the inclusive event selection for an integrated luminosity of 139fb$^{-1}$ at $\sqrt{s}$=13TeV. The SM Higgs boson signal is assumed to have a mass $m_{H}$=125 GeV.
The expected and the observed $NN_{ggF}$ output (post-fit) distribution in 0$j$-$p_{T}^{4l}$-Low category for an integrated luminosity of 139fb$^{-1}$ at $\sqrt{s}$=13TeV. The SM Higgs boson signal is assumed to have a mass $m_{H}$=125 GeV.
The expected and the observed $NN_{ggF}$ output (post-fit) distribution in 0$j$-$p_{T}^{4l}$-Med category for an integrated luminosity of 139fb$^{-1}$ at $\sqrt{s}$=13TeV. The SM Higgs boson signal is assumed to have a mass $m_{H}$=125 GeV.
The expected and the observed $NN_{VBF}$ output (post-fit) distribution in 1$j$-$p_{T}^{4l}$-Low category with $NN_{ZZ}$<0.25 for an integrated luminosity of 139fb$^{-1}$ at $\sqrt{s}$=13TeV. The SM Higgs boson signal is assumed to have a mass $m_{H}$=125 GeV.
The expected and the observed $NN_{ZZ}$ output (post-fit) distribution in 1$j$-$p_{T}^{4l}$-Low category with $NN_{ZZ}$>0.25 for an integrated luminosity of 139fb$^{-1}$ at $\sqrt{s}$=13TeV. The SM Higgs boson signal is assumed to have a mass $m_{H}$=125 GeV.
The expected and the observed $NN_{VBF}$ output (post-fit) distribution in 1$j$-$p_{T}^{4l}$-Med category with $NN_{ZZ}$<0.25 for an integrated luminosity of 139fb$^{-1}$ at $\sqrt{s}$=13TeV. The SM Higgs boson signal is assumed to have a mass $m_{H}$=125 GeV.
The expected and the observed $NN_{ZZ}$ output (post-fit) distribution in 1$j$-$p_{T}^{4l}$-Med category with $NN_{ZZ}$>0.25 for an integrated luminosity of 139fb$^{-1}$ at $\sqrt{s}$=13TeV. The SM Higgs boson signal is assumed to have a mass $m_{H}$=125 GeV.
The expected and the observed $NN_{VBF}$ output (post-fit) distribution in 1$j$-$p_{T}^{4l}$-High category for an integrated luminosity of 139fb$^{-1}$ at $\sqrt{s}$=13TeV. The SM Higgs boson signal is assumed to have a mass $m_{H}$=125 GeV.
The expected and the observed $NN_{VBF}$ output (post-fit) distribution in 2$j$ category with $NN_{VH}$<0.2 for an integrated luminosity of 139fb$^{-1}$ at $\sqrt{s}$=13TeV. The SM Higgs boson signal is assumed to have a mass $m_{H}$=125 GeV.
The expected and the observed $NN_{VH}$ output (post-fit) distribution in 2$j$ category with $NN_{VH}$>0.2 for an integrated luminosity of 139fb$^{-1}$ at $\sqrt{s}$=13TeV. The SM Higgs boson signal is assumed to have a mass $m_{H}$=125 GeV.
The expected and the observed $NN_{VBF}$ output (post-fit) distribution in 2$j$-BSM-like category for an integrated luminosity of 139fb$^{-1}$ at $\sqrt{s}$=13TeV. The SM Higgs boson signal is assumed to have a mass $m_{H}$=125 GeV.
The expected and the observed $NN_{ttH}$ output (post-fit) distribution in $ttH$-Had-enriched category with $NN_{tXX}$<0.4 for an integrated luminosity of 139fb$^{-1}$ at $\sqrt{s}$=13TeV. The SM Higgs boson signal is assumed to have a mass $m_{H}$=125 GeV.
The expected and the observed $NN_{tXX}$ output (post-fit) distribution in $ttH$-Had-enriched category with $NN_{tXX}$>0.4 for an integrated luminosity of 139fb$^{-1}$ at $\sqrt{s}$=13TeV. The SM Higgs boson signal is assumed to have a mass $m_{H}$=125 GeV.
The expected and the observed $NN_{ttH}$ output (post-fit) distribution in $VH$-Lep-enriched category for an integrated luminosity of 139fb$^{-1}$ at $\sqrt{s}$=13TeV. The SM Higgs boson signal is assumed to have a mass $m_{H}$=125 GeV.
The expected and the observed events in the categories where no NN discriminant is used for an integrated luminosity of 139fb$^{-1}$ at $\sqrt{s}$=13TeV. The SM Higgs boson signal is assumed to have a mass $m_{H}$=125 GeV.
The expected and the observed events in the side bands used to constraint the $ZZ^{*}$ and $tXX$ backgrounds for an integrated luminosity of 139fb$^{-1}$ at $\sqrt{s}$=13TeV. The SM Higgs boson signal is assumed to have a mass $m_{H}$=125 GeV.
The expected SM cross section $(\sigma \cdot BR)_{SM}$, the observed value of $(\sigma \cdot BR)$, and their ratio $(\sigma \cdot BR)/(\sigma \cdot BR)_{SM}$ for the inclusive production and for each Production Mode and Reduced Stage-1.1 production bin for an integrated luminosity of 139fb$^{-1}$ at $\sqrt{s}$=13 TeV.
The correlation matrices between the measured cross-sections and the $ZZ$ and $tXX$ normalisation factors for Production Mode Stage.
The correlation matrices between the measured cross-sections and the $ZZ$ and $tXX$ normalisation factors for Reduced Stage 1.1.
Likelihood contours at 68% CLs in the (ggF,VBF) plane. The observed best fit value is the first value of the table.
Likelihood contours at 95% CLs in the (ggF,VBF) plane. The observed best fit value is the first value of the table.
Likelihood contours at 68% CLs in the (ggF,VH) plane. The observed best fit value is the first value of the table.
Likelihood contours at 95% CLs in the (ggF,VH) plane. The observed best fit value is the first value of the table.
Likelihood contours at 68% CLs in the (VBF,VH) plane. The observed best fit value is the first value of the table.
Likelihood contours at 95% CLs in the (VBF,VH) plane. The observed best fit value is the first value of the table.
Likelihood contours at 68% CLs in the ($gg2H-0j-p_T^H-Low$,$gg2H-0j-p_T^H-High$) plane. The observed best fit value is the first value of the table.
Likelihood contours at 95% CLs in the ($gg2H-0j-p_T^H-Low$,$gg2H-0j-p_T^H-High$) plane. The observed best fit value is the first value of the table.
Likelihood contours at 68% CLs in the ($\kappa_{V}$vs.$\kappa_{F}$) plane. The observed best fit value is the first value of the table.
Likelihood contours at 95% CLs in the ($\kappa_{V}$vs.$\kappa_{F}$) plane. The observed best fit value is the first value of the table.
The expected signal yield ratio for chosen CP-even and CP-odd EFT parameter values together with the corresponding cross-section measurement in each production bin of Reduced Stage 1.1. The parameter values correspond approximately to the expected confidence intervals at the 68% CLs obtained from the statistical interpretation of data.
The expected and observed confidence intervals at 68% and 95% CLs of the SMEFT Wilson coefficients for an integrated luminosity of 139fb$^{-1}$ at $\sqrt{s}$=13 TeV. For the coupling with two best fit values, the two values have been splitted in the two different columns 'Two Best-fit value - first' and 'Two Best-fit value - second', and the symbol '-' has been inserted in the missing fields.
Expected 2D-fit likelihood curves at the 95% CLs for the $c_{HW}$ versus $c_{HB}$ coupling parameters at an integrated luminosity of 139 fb$^{-1}$ and $\sqrt{s}$=13 TeV. Except for the two fitted Wilson coefficients, all others are set to zero.
Observed 2D-fit likelihood curves at the 95% CLs for the $c_{HW}$ versus $c_{HB}$ coupling parameters at an integrated luminosity of 139 fb$^{-1}$ and $\sqrt{s}$=13 TeV. Except for the two fitted Wilson coefficients, all others are set to zero.
Expected 2D-fit likelihood curves at the 95% CLs for the $c_{HB}$ versus $c_{HG}$ coupling parameters at an integrated luminosity of 139 fb$^{-1}$ and $\sqrt{s}$=13 TeV. Except for the two fitted Wilson coefficients, all others are set to zero.
Observed 2D-fit likelihood curves at the 95% CLs for the $c_{HB}$ versus $c_{HG}$ coupling parameters at an integrated luminosity of 139 fb$^{-1}$ and $\sqrt{s}$=13 TeV. Except for the two fitted Wilson coefficients, all others are set to zero.
Expected 2D-fit likelihood curves at the 95% CLs for the $c_{uH}$ versus $c_{HG}$ coupling parameters at an integrated luminosity of 139 fb$^{-1}$ and $\sqrt{s}$=13 TeV. Except for the two fitted Wilson coefficients, all others are set to zero.
Observed 2D-fit likelihood curves at the 95% CLs for the $c_{uH}$ versus $c_{HG}$ coupling parameters at an integrated luminosity of 139 fb$^{-1}$ and $\sqrt{s}$=13 TeV. Except for the two fitted Wilson coefficients, all others are set to zero.
The best-fit values and the corresponding deviation from the SM prediction obtained from two-dimensional likelihood scans of the CP-odd BSM coupling parameters with 139fb$^{-1}$ data at $\sqrt{s}$=13 TeV. For the coupling with two best fit values, the two values have been splitted in the two different columns 'Two Observed best-fit first/second_POI - first' and 'Two Observed best-fit first/second_POI - second', and the symbol '-' has been inserted in the missing fields.
Expected 2D-fit likelihood curves at the 95% CLs for the $c_{H\tilde{W}}$ versus $c_{H\tilde{B}}$ coupling parameters at an integrated luminosity of 139 fb$^{-1}$ and $\sqrt{s}$=13 TeV. Except for the two fitted Wilson coefficients, all others are set to zero.
Observed 2D-fit likelihood curves at the 95% CLs for the $c_{H\tilde{W}}$ versus $c_{H\tilde{B}}$ coupling parameters at an integrated luminosity of 139 fb$^{-1}$ and $\sqrt{s}$=13 TeV. Except for the two fitted Wilson coefficients, all others are set to zero.
Expected 2D-fit likelihood curves at the 95% CLs for the $c_{H\tilde{B}}$ versus $c_{H\tilde{G}}$ coupling parameters at an integrated luminosity of 139 fb$^{-1}$ and $\sqrt{s}$=13 TeV. Except for the two fitted Wilson coefficients, all others are set to zero.
Observed 2D-fit likelihood curves at the 95% CLs for the $c_{H\tilde{B}}$ versus $c_{H\tilde{G}}$ coupling parameters at an integrated luminosity of 139 fb$^{-1}$ and $\sqrt{s}$=13 TeV. Except for the two fitted Wilson coefficients, all others are set to zero.
Expected 2D-fit likelihood curves at the 95% CLs for the $c_{\tilde{u}H}$ versus $c_{H\tilde{G}}$ coupling parameters at an integrated luminosity of 139 fb$^{-1}$ and $\sqrt{s}$=13 TeV. Except for the two fitted Wilson coefficients, all others are set to zero.
Observed 2D-fit likelihood curves at the 95% CLs for the $c_{\tilde{u}H}$ versus $c_{H\tilde{G}}$ coupling parameters at an integrated luminosity of 139 fb$^{-1}$ and $\sqrt{s}$=13 TeV. Except for the two fitted Wilson coefficients, all others are set to zero.
Signal acceptance times efficiency, expressed as a percentage, obtained from the ratio of the number of simulated signal events satisfying the event selection criteria in each reconstructed category to the total number of events generated in the phase space specified by a given Production model bin.
Signal acceptance times efficiency, expressed as a percentage, obtained from the ratio of the number of simulated signal events satisfying the event selection criteria in each reconstructed category to the total number of events generated in the phase space specified by a given Reduced Stage-1.1 production bin.
Observed covariance matrix for the different parameters of interest when fitting the for Production Mode Stage.
Observed covariance matrix for the different parameters of interest when fitting the for Reduced Stage 1.1.
The expected SM cross section $(\sigma\cdot BR)_{SM}$, the observed value of $(\sigma\cdot BR)$, and their ratio $(\sigma\cdot BR)/(\sigma\cdot BR)_{SM}$ for the alternate Reduced Stage-1.1 scheme for an integrated luminosity of 139fb$^{-1}$ at $\sqrt{s}$=13 TeV.
The correlation matrices between the measured cross-sections and the ZZ and $tXX$ normalisation factors for alternative Reduced Stage 1.1.
Expected 2D-fit likelihood curves at the 95% CLs for the $c_{HW}$ versus $c_{HWB}$ coupling parameters at an integrated luminosity of 139 fb$^{-1}$ and $\sqrt{s}$=13 TeV. Except for the two fitted Wilson coefficients, all others are set to zero.
Observed 2D-fit likelihood curves at the 95% CLs for the $c_{HW}$ versus $c_{HWB}$ coupling parameters at an integrated luminosity of 139 fb$^{-1}$ and $\sqrt{s}$=13 TeV. Except for the two fitted Wilson coefficients, all others are set to zero.
Expected 2D-fit likelihood curves at the 95% CLs for the $c_{HB}$ versus $c_{HWB}$ coupling parameters at an integrated luminosity of 139 fb$^{-1}$ and $\sqrt{s}$=13 TeV. Except for the two fitted Wilson coefficients, all others are set to zero.
Observed 2D-fit likelihood curves at the 95% CLs for the $c_{HB}$ versus $c_{HWB}$ coupling parameters at an integrated luminosity of 139 fb$^{-1}$ and $\sqrt{s}$=13 TeV. Except for the two fitted Wilson coefficients, all others are set to zero.
Expected 2D-fit likelihood curves at the 95% CLs for the $c_{HW}$ versus $c_{HG}$ coupling parameters at an integrated luminosity of 139 fb$^{-1}$ and $\sqrt{s}$=13 TeV. Except for the two fitted Wilson coefficients, all others are set to zero.
Observed 2D-fit likelihood curves at the 95% CLs for the $c_{HW}$ versus $c_{HG}$ coupling parameters at an integrated luminosity of 139 fb$^{-1}$ and $\sqrt{s}$=13 TeV. Except for the two fitted Wilson coefficients, all others are set to zero.
Expected 2D-fit likelihood curves at the 95% CLs for the $c_{HWB}$ versus $c_{HG}$ coupling parameters at an integrated luminosity of 139 fb$^{-1}$ and $\sqrt{s}$=13 TeV. Except for the two fitted Wilson coefficients, all others are set to zero.
Observed 2D-fit likelihood curves at the 95% CLs for the $c_{HWB}$ versus $c_{HG}$ coupling parameters at an integrated luminosity of 139 fb$^{-1}$ and $\sqrt{s}$=13 TeV. Except for the two fitted Wilson coefficients, all others are set to zero.
Expected 2D-fit likelihood curves at the 95% CLs for the $c_{H\tilde{W}}$ versus $c_{H\tilde{W}B}$ coupling parameters at an integrated luminosity of 139 fb$^{-1}$ and $\sqrt{s}$=13 TeV. Except for the two fitted Wilson coefficients, all others are set to zero.
Observed 2D-fit likelihood curves at the 95% CLs for the $c_{H\tilde{W}}$ versus $c_{H\tilde{W}B}$ coupling parameters at an integrated luminosity of 139 fb$^{-1}$ and $\sqrt{s}$=13 TeV. Except for the two fitted Wilson coefficients, all others are set to zero.
Expected 2D-fit likelihood curves at the 95% CLs for the $c_{H\tilde{B}}$ versus $c_{H\tilde{W}B}$ coupling parameters at an integrated luminosity of 139 fb$^{-1}$ and $\sqrt{s}$=13 TeV. Except for the two fitted Wilson coefficients, all others are set to zero.
Observed 2D-fit likelihood curves at the 95% CLs for the $c_{H\tilde{B}}$ versus $c_{H\tilde{W}B}$ coupling parameters at an integrated luminosity of 139 fb$^{-1}$ and $\sqrt{s}$=13 TeV. Except for the two fitted Wilson coefficients, all others are set to zero.
Expected 2D-fit likelihood curves at the 95% CLs for the $c_{H\tilde{W}}$ versus $c_{H\tilde{G}}$ coupling parameters at an integrated luminosity of 139 fb$^{-1}$ and $\sqrt{s}$=13 TeV. Except for the two fitted Wilson coefficients, all others are set to zero.
Observed 2D-fit likelihood curves at the 95% CLs for the $c_{H\tilde{W}}$ versus $c_{H\tilde{G}}$ coupling parameters at an integrated luminosity of 139 fb$^{-1}$ and $\sqrt{s}$=13 TeV. Except for the two fitted Wilson coefficients, all others are set to zero.
Expected 2D-fit likelihood curves at the 95% CLs for the $c_{H\tilde{W}B}$ versus $c_{H\tilde{G}}$ coupling parameters at an integrated luminosity of 139 fb$^{-1}$ and $\sqrt{s}$=13 TeV. Except for the two fitted Wilson coefficients, all others are set to zero.
Observed 2D-fit likelihood curves at the 95% CLs for the $c_{H\tilde{W}B}$ versus $c_{H\tilde{G}}$ coupling parameters at an integrated luminosity of 139 fb$^{-1}$ and $\sqrt{s}$=13 TeV. Except for the two fitted Wilson coefficients, all others are set to zero.
Inclusive and differential fiducial cross sections of the Higgs boson are measured in the $H \to ZZ^{*} \to 4\ell$ ($\ell = e,\mu$) decay channel. The results are based on proton$-$proton collision data produced at the Large Hadron Collider at a centre-of-mass energy of 13 TeV and recorded by the ATLAS detector from 2015 to 2018, equivalent to an integrated luminosity of 139 fb$^{-1}$. The inclusive fiducial cross section for the $H \to ZZ^{*} \to 4\ell$ process is measured to be $\sigma_\mathrm{fid} = 3.28 \pm 0.32$ fb, in agreement with the Standard Model prediction of $\sigma_\mathrm{fid, SM} = 3.41 \pm 0.18 $ fb. Differential fiducial cross sections are measured for a variety of observables which are sensitive to the production and decay of the Higgs boson. All measurements are in agreement with the Standard Model predictions. The results are used to constrain anomalous Higgs boson interactions with Standard Model particles.
Fractional uncertainties for the inclusive fiducial and total cross sections, and range of systematic uncertainties for the differential measurements. The columns e/$\mu$ and jets represent the experimental uncertainties in lepton and jet reconstruction and identification, respectively. The Z + jets, $t\bar{t}$, tXX (Other Bkg.) column includes uncertainties related to the estimation of these background sources. The $ZZ^{*}$ theory ($ZZ^{*}$ th.) uncertainties include the PDF and scale variations. Signal theory (Sig th.) uncertainties include PDF choice, QCD scale, and shower modelling of the signal. Finally, the column labelled Comp. contains uncertainties related to production mode composition and unfolding bias which affect the response matrices. The uncertainties have been rounded to the nearest 0.5%, except for the luminosity uncertainty which has been measured to be 1.7%.
Expected (pre-fit) and observed number of events in the four decay final states after the event selection, in the mass range 115< $m_{4l}$ < 130 GeV. The sum of the expected number of SM Higgs boson events and the estimated background yields is compared to the data. Combined statistical and systematic uncertainties are included for the predictions.
The fiducial and total cross sections of Higgs boson production measured in the 4l final state. The fiducial cross sections are given separately for each decay final state, and for same- and different-flavour decays. The inclusive fiducial cross section is measured as the sum of all final states ($\sigma_{sum}$), as well as by combining the per-final state measurements assuming SM $ZZ^{*} \to 4l$ relative branching ratios ($\sigma_{comb}$). For the total cross section ($\sigma_{tot}$), the Higgs boson branching ratio at $m_{H}$= 125 GeV is assumed. The total SM prediction is accurate to N3LO in QCD and NLO EW for the ggF process. The cross sections for all other Higgs boson production modes XH are added. For the fiducial cross section predictions, the SM cross sections are multiplied by the acceptances determined using the NNLOPS sample for ggF. The p-values indicating the compatibility of the measurement and the SM prediction are shown as well. They do not include the systematic uncertainty in the theoretical predictions.
Correlation matrix between the fiducial cross sections for the four individual decay final states and the $ZZ^{*}$ normalisation factor.
Differential fiducial cross section for the transverse momentum $p_{T}^{4l}$ of the Higgs boson. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 . Measured value in the last bin is un upper limit at 95% CL.
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the transverse momentum $p_{T}^{4l}$ of the Higgs boson.
Differential fiducial cross section for the invariant mass $m_{12}$ of the leading Z boson. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the invariant mass $m_{12}$ of the leading Z boson.
Differential fiducial cross section for the invariant mass $m_{34}$ of the subleading Z boson. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the invariant mass $m_{34}$ of the subleading Z boson.
Differential fiducial cross section for the rapidity $|y_{4l}|$ of the Higgs boson. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the rapidity $|y_{4l}|$ of the Higgs boson.
Differential fiducial cross section for the production angle $|\cos\theta^{*}|$ of the leading Z boson. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the production angle $|\cos\theta^{*}|$ of the leading Z boson.
Differential fiducial cross section for the production angle $\cos\theta_{1}$ of the anti-lepton from the leading Z boson. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the production angle $\cos\theta_{1}$ of the anti-lepton from the leading Z boson.
Differential fiducial cross section for the production angle $\cos\theta_{2}$ of the anti-lepton from the subleading Z boson. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the production angle $\cos\theta_{2}$ of the anti-lepton from the subleading Z boson.
Differential fiducial cross section for the azimuthal angle $\phi$ of the decay planes of the two reconstructed Z bosons. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the azimuthal angle $\phi$ of the decay planes of the two reconstructed Z bosons.
Differential fiducial cross section for the azimuthal angle $\phi_{1}$ of the decay plane of the leading Z boson and the plane formed between its four-momentum and the z-axis. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the azimuthal angle $\phi_{1}$ of the decay plane of the leading Z boson and the plane formed between its four-momentum and the z-axis.
Differential fiducial cross section for the jet multiplicity $N_{jets}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the jet multiplicity $N_{jets}$.
Differential fiducial cross section for the inclusive jet multiplicity $N_{jets}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Differential fiducial cross section for the number of b-quark initiated jets $N_{b-jets}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the number of b-quark initiated jets $N_{b-jets}$.
Differential fiducial cross section for the transverse momentum of the leading jet $p_{T}^{lead.jet}$ in events with at least one jet. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the transverse momentum of the leading jet $p_{T}^{lead.jet}$ in events with at least one jet.
Differential fiducial cross section for the transverse momentum of the subleading jet $p_{T}^{sublead.jet}$ in events with at least two jets. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the transverse momentum of the subleading jet $p_{T}^{sublead.jet}$ in events with at least two jets.
Differential fiducial cross section for the invariant mass of the two highest-pT jets $m_{jj}$ in events with at least two jets. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the invariant mass of the two highest-pT jets $m_{jj}$ in events with at least two jets.
Differential fiducial cross section for the distance between the two highest-pT jets in pseudorapidity $\Delta\eta_{jj}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the distance between the two highest-pT jets in pseudorapidity $\Delta\eta_{jj}$.
Differential fiducial cross section for the distance between the two highest-pT jets in $\phi$ $\Delta\phi_{jj}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the distance between the two highest-pT jets in $\phi$ $\Delta\phi_{jj}$.
Differential fiducial cross section for the transverse momentum of the four lepton plus jet system, in events with at least one jet $p_{T}^{4lj}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the transverse momentum of the four lepton plus jet system, in events with at least one jet $p_{T}^{4lj}$.
Differential fiducial cross section for the transverse momentum of the four lepton plus di-jet system, in events with at least two jets $p_{T}^{4ljj}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 . Measured value in the last bin is un upper limit at 95% CL.
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the transverse momentum of the four lepton plus di-jet system, in events with at least two jets $p_{T}^{4ljj}$.
Differential fiducial cross section for the invariant mass of the four lepton plus jet system in events with at least one jet $m_{4lj}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the invariant mass of the four lepton plus jet system in events with at least one jet $m_{4lj}$.
Differential fiducial cross section for the invariant mass of the four lepton plus di-jet system in events with at least two jets $m_{4ljj}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the invariant mass of the four lepton plus di-jet system in events with at least two jets $m_{4ljj}$.
Differential fiducial cross section for the leading vs. subleading Z boson mass $m_{12}$vs.$m_{34}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the leading vs. subleading Z boson mass $m_{12}$vs.$m_{34}$.
Differential fiducial cross section for the leading vs. subleading Z boson mass $m_{12}$vs.$m_{34}$ in $ll\mu\mu$ final states. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Differential fiducial cross section for the leading vs. subleading Z boson mass $m_{12}$vs.$m_{34}$ in $llee$ final states. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the leading vs. subleading Z boson mass m12 vs. m34 in $ll\mu\mu$ and $llee$ final states.
Differential fiducial cross section of the $p_{T}^{4l}$ distribution in $|y_{4l}|$ bins. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section of the $p_{T}^{4l}$ distribution in $|y_{4l}|$ bins.
Differential fiducial cross section of the $p_{T}^{4l}$ distribution in $N_{jets}$ bins. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section of the $p_{T}^{4l}$ distribution in $N_{jets}$ bins.
Differential fiducial cross section for transverse momentum of the four lepton system vs. the transverse momentum of the four lepton plus jet system $p_{T}^{4l}$vs.$p_{T}^{4lj}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for transverse momentum of the four lepton system vs. the transverse momentum of the four lepton plus jet system $p_{T}^{4l}$vs.$p_{T}^{4lj}$.
Differential fiducial cross section for the transverse momentum of the four lepton plus jet system vs the invariant mass of the four lepton plus jet system $p_{T}^{4l}$vs.$m_{4lj}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the transverse momentum of the four lepton plus jet system vs the invariant mass of the four lepton plus jet system $p_{T}^{4l}$vs.$m_{4lj}$.
Differential fiducial cross section for the transverse momentum of the four lepton vs the transverse momentum of the leading jet $p_{T}^{4l}$vs.$p_{T}^{l.jet}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the transverse momentum of the four lepton vs the transverse momentum of the leading jet $p_{T}^{4l}$vs.$p_{T}^{lead.jet}$.
Differential fiducial cross section for the transverse momentum of the leading jet vs the rapidity of the leading jet $p_{T}^{lead.jet}$vs.$|y^{lead.jet}|$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the transverse momentum of the leading jet vs the rapidity of the leading jet $p_{T}^{lead.jet}$vs.$|y^{lead.jet}|$.
Differential fiducial cross section for the transverse momentum of the leading jet vs the transverse momentum of the subleading jet $p_{T}^{lead.jet}$vs.$p_{T}^{sublead.jet}$. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the transverse momentum of the leading jet vs the transverse momentum of the subleading jet $p_{T}^{lead.jet}$vs.$p_{T}^{sublead.jet}$.
Differential fiducial cross section for the leading Z boson mass $m_{12}$ in $4\mu$ and $4e$ final states. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Differential fiducial cross section for the leading Z boson mass $m_{12}$ in $2e2\mu$ and $2\mu2e$ final states. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the leading Z boson mass $m_{12}$ in $4l$ and $2l2l$ final states.
Differential fiducial cross section for the subleading Z boson mass $m_{34}$ in $4\mu$ and $4e$ final states. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Differential fiducial cross section for the subleading Z boson mass $m_{34}$ in $2e2\mu$ and $2\mu2e$ final states. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the subleading Z boson mass $m_{34}$ in $4l$ and $2l2l$ final states.
Differential fiducial cross section for the azimuthal angle $\phi$ of the decay planes of the two reconstructed Z bosons in $4\mu$ and $4e$ final states. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Differential fiducial cross section for the azimuthal angle $\phi$ of the decay planes of the two reconstructed Z bosons in $2e2\mu$ and $2\mu2e$ final states. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the azimuthal angle $\phi$ of the decay planes of the two reconstructed Z bosons in $4l$ and $2l2l$ final states.
Differential fiducial cross section for the leading vs. subleading Z boson mass $m_{12}$vs.$m_{34}$ in $4\mu$ and $4e$ final states. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Differential fiducial cross section for the leading vs. subleading Z boson mass $m_{12}$vs.$m_{34}$ in $2\mu2e$ and $2e2\mu$ final states. The measured cross sections are compared to predictions provided by NNLOPS + XH. NNLOPS is normalised to the N3LO total cross section with a K-factor = 1.1 .
Correlation matrix between the measured cross sections and the $ZZ^{*}$ background normalization corresponding to the differential fiducial cross section for the leading vs. subleading Z boson mass $m_{12}$vs.$m_{34}$ in $4l$ and $2l2l$ final states.
This paper reports on a search for the electroweak diboson ($WW/WZ/ZZ$) production in association with a high-mass dijet system, using data from proton-proton collisions at a center-of-mass energy of $\sqrt{s}=13$ TeV. The data, corresponding to an integrated luminosity of 35.5 fb$^{-1}$, were recorded with the ATLAS detector in 2015 and 2016 at the Large Hadron Collider. The search is performed in final states in which one boson decays leptonically, and the other boson decays hadronically. The hadronically decaying $W/Z$ boson is reconstructed as either two small-radius jets or one large-radius jet using jet substructure techniques. The electroweak production of $WW/WZ/ZZ$ in association with two jets is measured with an observed (expected) significance of 2.7 (2.5) standard deviations, and the fiducial cross section is measured to be $45.1 \pm 8.6(\mathrm{stat.}) ^{+15.9} _{-14.6} (\mathrm{syst.})$ fb.
Summary of predicted and measured fiducial cross sections for EW $VVjj$ production. The three lepton channels are combined. For the measured fiducial cross sections in the merged and resolved categories, two signal-strength parameters are used in the combined fit, one for the merged category and the other one for the resolved category; while for the measured fiducial cross section in the inclusive fiducial phase space, a single signal-strength parameter is used. For the SM predicted cross section, the error is the theoretical uncertainty (theo.). For the measured cross section, the first error is the statistical uncertainty (stat.), and the second error is the systematic uncertainty (syst.).
Summary of predicted and measured fiducial cross sections for EW $VVjj$ production. in the three lepton channels. The measured values are obtained from a simultaneous fit where each lepton channel has its own signal-strength parameter, and in each lepton channel the same signal-strength parameter is applied to both the merged and resolved categories. For the SM predicted cross section, the error is the theoretical uncertainty (theo.). For the measured cross section, the first error is the statistical uncertainty (stat.), and the second error is the systematic uncertainty (syst.).
A search for heavy neutral Higgs bosons is performed using the LHC Run 2 data, corresponding to an integrated luminosity of 139 fb$^{-1}$ of proton-proton collisions at $\sqrt{s}=13$ TeV recorded with the ATLAS detector. The search for heavy resonances is performed over the mass range 0.2-2.5 TeV for the $\tau^+\tau^-$ decay with at least one $\tau$-lepton decaying into final states with hadrons. The data are in good agreement with the background prediction of the Standard Model. In the $M_{h}^{125}$ scenario of the Minimal Supersymmetric Standard Model, values of $\tan\beta>8$ and $\tan\beta>21$ are excluded at the 95% confidence level for neutral Higgs boson masses of 1.0 TeV and 1.5 TeV, respectively, where $\tan\beta$ is the ratio of the vacuum expectation values of the two Higgs doublets.
Observed and predicted mTtot distribution in the b-veto category of the 1l1tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table.The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-veto category of the 1l1tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table.The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-veto category of the 1l1tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table.The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-veto category of the 1l1tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table.The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of the 1l1tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of the 1l1tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of the 1l1tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of the 1l1tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-veto category of the 2tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-veto category of the 2tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-veto category of the 2tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-veto category of the 2tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of the 2tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of the 2tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of the 2tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of the 2tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and expected 95% CL upper limits on the gluon-gluon fusion Higgs boson production cross section times ditau branching fraction as a function of the Higgs boson mass.
Observed and expected 95% CL upper limits on the gluon-gluon fusion Higgs boson production cross section times ditau branching fraction as a function of the Higgs boson mass.
Observed and expected 95% CL upper limits on the gluon-gluon fusion Higgs boson production cross section times ditau branching fraction as a function of the Higgs boson mass.
Observed and expected 95% CL upper limits on the gluon-gluon fusion Higgs boson production cross section times ditau branching fraction as a function of the Higgs boson mass.
Observed and expected 95% CL upper limits on the b-associated Higgs boson production cross section times ditau branching fraction as a function of the boson mass.
Observed and expected 95% CL upper limits on the b-associated Higgs boson production cross section times ditau branching fraction as a function of the boson mass.
Observed and expected 95% CL upper limits on the b-associated Higgs boson production cross section times ditau branching fraction as a function of the boson mass.
Observed and expected 95% CL upper limits on the b-associated Higgs boson production cross section times ditau branching fraction as a function of the boson mass.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
Acceptance times efficiency for a scalar boson produced by gluon-gluon fusion as a function of the scalar boson mass.
Acceptance times efficiency for a scalar boson produced by gluon-gluon fusion as a function of the scalar boson mass.
Acceptance times efficiency for a scalar boson produced by gluon-gluon fusion as a function of the scalar boson mass.
Acceptance times efficiency for a scalar boson produced by gluon-gluon fusion as a function of the scalar boson mass.
Acceptance times efficiency for a scalar boson produced by b-associated production as a function of the scalar boson mass.
Acceptance times efficiency for a scalar boson produced by b-associated production as a function of the scalar boson mass.
Acceptance times efficiency for a scalar boson produced by b-associated production as a function of the scalar boson mass.
Acceptance times efficiency for a scalar boson produced by b-associated production as a function of the scalar boson mass.
Observed 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Observed 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Observed 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Observed 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Expected 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Expected 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Expected 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Expected 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\chi})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\chi})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\chi})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\chi})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\chi})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\chi})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\chi})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\chi})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\chi})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\chi})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\chi})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\chi})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\tau})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\tau})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\tau})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\tau})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\tau})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\tau})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\tau})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\tau})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\tau})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\tau})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\tau})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\tau})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The observed 95% CL upper limits with one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(alignment)$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 1.0. The highest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 20.0. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(alignment)$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 1.0. The highest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 20.0. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(alignment)$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 1.0. The highest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 20.0. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(alignment)$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 1.0. The highest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 20.0. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(alignment)$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 1.0. The highest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 20.0. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(alignment)$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 1.0. The highest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 20.0. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The theoretical uncertainty of signal cross section is considered.
Jet substructure quantities are measured using jets groomed with the soft-drop grooming procedure in dijet events from 32.9 fb$^{-1}$ of $pp$ collisions collected with the ATLAS detector at $\sqrt{s} = 13$ TeV. These observables are sensitive to a wide range of QCD phenomena. Some observables, such as the jet mass and opening angle between the two subjets which pass the soft-drop condition, can be described by a high-order (resummed) series in the strong coupling constant $\alpha_S$. Other observables, such as the momentum sharing between the two subjets, are nearly independent of $\alpha_S$. These observables can be constructed using all interacting particles or using only charged particles reconstructed in the inner tracking detectors. Track-based versions of these observables are not collinear safe, but are measured more precisely, and universal non-perturbative functions can absorb the collinear singularities. The unfolded data are directly compared with QCD calculations and hadron-level Monte Carlo simulations. The measurements are performed in different pseudorapidity regions, which are then used to extract quark and gluon jet shapes using the predicted quark and gluon fractions in each region. All of the parton shower and analytical calculations provide an excellent description of the data in most regions of phase space.
Data from Fig 6a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 6a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 6b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 6b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 6c. The unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 6c. The unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 6d. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 6d. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 6e. The unfolded $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 6e. The unfolded $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 6f. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 6f. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 7a. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 7a. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 7b. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 7b. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 7c. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 7c. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 7d. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 7d. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 7e. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 7e. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 7f. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 7f. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 8a. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 8a. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 8b. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 8b. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 8c. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 8c. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 8d. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 8d. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 8e. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 8e. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 8f. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 8f. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 14a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 14b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 14b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 4b. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 4b. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 21b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 21b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 5a. The unfolded $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 5a. The unfolded $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 5b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 5b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 14c. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14c. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14d. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14d. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4c. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4c. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4d. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4d. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5c. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5c. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5d. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5d. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14e. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14e. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14f. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14f. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4e. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4e. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4f. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4f. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5e. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5e. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5f. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5f. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 14a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 14b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 14b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 4a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 4a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 4b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 4b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 5a. The unfolded $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 5a. The unfolded $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 5b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 5b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 14c. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14c. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14d. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14d. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4c. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4c. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4d. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4d. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5c. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5c. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5d. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5d. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14e. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14e. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14f. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14f. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4e. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4e. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4f. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4f. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5e. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5e. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5f. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5f. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 36-40a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 36-40a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 81-85a. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 81-85a. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 36-40b. The unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 36-40b. The unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 81-85b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 81-85b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 36-40c. The unfolded $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 36-40c. The unfolded $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 81-85c. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 81-85c. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 51-55a. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 51-55a. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 101-105a. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 101-105a. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 51-55b. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 51-55b. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 101-105b. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 101-105b. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 51-55c. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 51-55c. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 101-105c. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 101-105c. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 66-70a. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 66-70a. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 106-110a. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 106-110a. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 66-70b. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 66-70b. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 106-110b. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 106-110b. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 66-70c. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 66-70c. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 106-110c. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 106-110c. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 26-30a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 26-30a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 71-75a. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 71-75a. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 26-30b. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 26-30b. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 71-75b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 71-75b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 26-30c. The unfolded $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 26-30c. The unfolded $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 71-75c. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 71-75c. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 41-45a. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 41-45a. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 86-90a. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 86-90a. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 41-45b. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 41-45b. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 86-90b. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 86-90b. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 41-45c. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 41-45c. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 86-90c. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 86-90c. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 56-60a. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 56-60a. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 101-105a. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 101-105a. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 56-60b. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 56-60b. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 101-105b. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 101-105b. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 56-60c. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 56-60c. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 101-105c. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 101-105c. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 31-35a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 31-35a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 76-80a. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 76-80a. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 31-35b. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 31-35b. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 76-80b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 76-80b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 31-35c. The unfolded $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 31-35c. The unfolded $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 76-80c. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 76-80c. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 46-50a. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 46-50a. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 91-95a. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 91-95a. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 46-50b. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 46-50b. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 91-95b. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 91-95b. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 46-50c. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 46-50c. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 91-95c. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 91-95c. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 61-65a. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 61-65a. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 106-110a. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 106-110a. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 61-65b. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 61-65b. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 106-110b. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 106-110b. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 61-65c. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 61-65c. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 106-110c. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 106-110c. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 6a. The extracted quark-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 6a. The extracted quark-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 15a. Theextracted quark-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 15a. Theextracted quark-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 6b. The extracted quark-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 6b. The extracted quark-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 15b. The extracted quark-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 15b. The extracted quark-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 6c. The extracted quark-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 6c. The extracted quark-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 15c. The extracted quark-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 15c. The extracted quark-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 7a. The extracted quark-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 7a. The extracted quark-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 16a. The extracted quark-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 16a. The extracted quark-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 7b. The extracted quark-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 7b. The extracted quark-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 16b. The extracted quark-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 16b. The extracted quark-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 7c. The extracted quark-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 7c. The extracted quark-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 16c. The extracted quark-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 16c. The extracted quark-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 8a. The extracted quark-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 8a. The extracted quark-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 17a. The extracted quark-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 17a. The extracted quark-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 8b. The extracted quark-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 8b. The extracted quark-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 17b. The extracted quark-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 17b. The extracted quark-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 8c. The extracted quark-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 8c. The extracted quark-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 17c. The extracted quark-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 17c. The extracted quark-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 6a. The extracted gluon-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 6a. The extracted gluon-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 15a. Theextracted gluon-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 15a. Theextracted gluon-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 6b. The extracted gluon-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 6b. The extracted gluon-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 15b. The extracted gluon-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 15b. The extracted gluon-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 6c. The extracted gluon-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 6c. The extracted gluon-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 15c. The extracted gluon-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 15c. The extracted gluon-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 7a. The extracted gluon-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 7a. The extracted gluon-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 16a. The extracted gluon-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 16a. The extracted gluon-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 7b. The extracted gluon-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 7b. The extracted gluon-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 16b. The extracted gluon-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 16b. The extracted gluon-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 7c. The extracted gluon-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 7c. The extracted gluon-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 16c. The extracted gluon-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 16c. The extracted gluon-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 8a. The extracted gluon-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 8a. The extracted gluon-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 17a. The extracted gluon-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 17a. The extracted gluon-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 8b. The extracted gluon-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 8b. The extracted gluon-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 17b. The extracted gluon-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 17b. The extracted gluon-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 8c. The extracted gluon-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 8c. The extracted gluon-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 17c. The extracted gluon-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 17c. The extracted gluon-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 99a. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 99a. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 100a. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 100a. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 99b. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 99b. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 100b. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 100b. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 99c. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 99c. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 100c. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 100c. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 101a. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 101a. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 102a. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 102a. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 101b. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 101b. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 102b. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 102b. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 101c. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 101c. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 102c. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 102c. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 103a. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 103a. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 104a. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 104a. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 103b. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 103b. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 104b. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 104b. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 103c. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 103c. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 104c. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 104c. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 105a. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 105a. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 106a. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 106a. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 105b. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 105b. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 106b. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 106b. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 105c. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 105c. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 106c. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 106c. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 107a. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 107a. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 108a. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 108a. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 107b. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 107b. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 108b. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 108b. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 107c. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 107c. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 108c. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 108c. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 109a. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 109a. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 110a. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 110a. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 109b. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 109b. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 110b. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 110b. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 109c. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 109c. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 110c. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 110c. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 111a. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 111a. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 112a. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 112a. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 111b. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 111b. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 112b. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 112b. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 111c. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 111c. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 112c. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 112c. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 113a. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 113a. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 114a. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 114a. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 113b. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 113b. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 114b. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 114b. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 113c. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 113c. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 114c. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 114c. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 115a. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 115a. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 116a. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 116a. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 115b. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 115b. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 116b. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 116b. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 115c. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 115c. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 116c. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 116c. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 99d. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 99d. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 100d. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 100d. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 99e. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 99e. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 100e. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 100e. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 99f. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 99f. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 100f. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 100f. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 101d. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 101d. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 102d. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 102d. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 101e. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 101e. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 102e. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 102e. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 101f. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 101f. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 102f. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 102f. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 103d. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 103d. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 104d. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 104d. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 103e. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 103e. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 104e. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 104e. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 103f. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 103f. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 104f. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 104f. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 105d. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 105d. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 106d. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 106d. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 105e. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 105e. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 106e. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 106e. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 105f. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 105f. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 106f. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 106f. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 107d. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 107d. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 108d. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 108d. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 107e. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 107e. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 108e. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 108e. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 107f. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 107f. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 108f. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 108f. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 109d. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 109d. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 110d. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 110d. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 109e. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 109e. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 110e. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 110e. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 109f. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 109f. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 110f. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 110f. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 111d. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 111d. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 112d. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 112d. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 111e. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 111e. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 112e. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 112e. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 111f. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 111f. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 112f. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 112f. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 113d. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 113d. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 114d. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 114d. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 113e. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 113e. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 114e. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 114e. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 113f. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 113f. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 114f. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 114f. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 115d. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 115d. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 116d. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 116d. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 115e. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 115e. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 116e. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 116e. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 115f. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 115f. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 116f. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 116f. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
A search for direct pair production of scalar partners of the top quark (top squarks or scalar third-generation up-type leptoquarks) in the all-hadronic $t\bar{t}$ plus missing transverse momentum final state is presented. The analysis of 139 fb$^{-1}$ of ${\sqrt{s}=13}$ TeV proton-proton collision data collected using the ATLAS detector at the LHC yields no significant excess over the Standard Model background expectation. To interpret the results, a supersymmetric model is used where the top squark decays via $\tilde{t} \to t^{(*)} \tilde{\chi}^0_1$, with $t^{(*)}$ denoting an on-shell (off-shell) top quark and $\tilde{\chi}^0_1$ the lightest neutralino. Three specific event selections are optimised for the following scenarios. In the scenario where $m_{\tilde{t}}> m_t+m_{\tilde{\chi}^0_1}$, top squark masses are excluded in the range 400-1250 GeV for $\tilde{\chi}^0_1$ masses below $200$ GeV at 95 % confidence level. In the situation where $m_{\tilde{t}}\sim m_t+m_{\tilde{\chi}^0_1}$, top squark masses in the range 300-630 GeV are excluded, while in the case where $m_{\tilde{t}}< m_W+m_b+m_{\tilde{\chi}^0_1}$ (with $m_{\tilde{t}}-m_{\tilde{\chi}^0_1}\ge 5$ GeV), considered for the first time in an ATLAS all-hadronic search, top squark masses in the range 300-660 GeV are excluded. Limits are also set for scalar third-generation up-type leptoquarks, excluding leptoquarks with masses below $1240$ GeV when considering only leptoquark decays into a top quark and a neutrino.
<b>- - - - - - - - Overview of HEPData Record - - - - - - - -</b> <br><br> <b>Exclusion contours:</b> <ul> <li><a href="?table=stop_obs">Stop exclusion contour (Obs.)</a> <li><a href="?table=stop_obs_down">Stop exclusion contour (Obs. Down)</a> <li><a href="?table=stop_obs_up">Stop exclusion contour (Obs. Up)</a> <li><a href="?table=stop_exp">Stop exclusion contour (Exp.)</a> <li><a href="?table=stop_exp_down">Stop exclusion contour (Exp. Down)</a> <li><a href="?table=stop_exp_up">Stop exclusion contour (Exp. Up)</a> <li><a href="?table=LQ3u_obs">LQ3u exclusion contour (Obs.)</a> <li><a href="?table=LQ3u_obs_down">LQ3u exclusion contour (Obs. Down)</a> <li><a href="?table=LQ3u_obs_up">LQ3u exclusion contour (Obs. Up)</a> <li><a href="?table=LQ3u_exp">LQ3u exclusion contour (Exp.)</a> <li><a href="?table=LQ3u_exp_down">LQ3u exclusion contour (Exp. Down)</a> <li><a href="?table=LQ3u_exp_up">LQ3u exclusion contour (Exp. Up)</a> </ul> <b>Upper limits:</b> <ul> <li><a href="?table=stop_xSecUpperLimit_obs">stop_xSecUpperLimit_obs</a> <li><a href="?table=stop_xSecUpperLimit_exp">stop_xSecUpperLimit_exp</a> <li><a href="?table=LQ3u_xSecUpperLimit_obs">LQ3u_xSecUpperLimit_obs</a> <li><a href="?table=LQ3u_xSecUpperLimit_exp">LQ3u_xSecUpperLimit_exp</a> </ul> <b>Kinematic distributions:</b> <ul> <li><a href="?table=SRATW_metsigST">SRATW_metsigST</a> <li><a href="?table=SRBTT_m_1fatjet_kt12">SRBTT_m_1fatjet_kt12</a> <li><a href="?table=SRC_RISR">SRC_RISR</a> <li><a href="?table=SRD0_htSig">SRD0_htSig</a> <li><a href="?table=SRD1_htSig">SRD1_htSig</a> <li><a href="?table=SRD2_htSig">SRD2_htSig</a> </ul> <b>Cut flows:</b> <ul> <li><a href="?table=cutflow_SRATT">cutflow_SRATT</a> <li><a href="?table=cutflow_SRATW">cutflow_SRATW</a> <li><a href="?table=cutflow_SRAT0">cutflow_SRAT0</a> <li><a href="?table=cutflow_SRB">cutflow_SRB</a> <li><a href="?table=cutflow_SRC">cutflow_SRC</a> <li><a href="?table=cutflow_SRD0">cutflow_SRD0</a> <li><a href="?table=cutflow_SRD1">cutflow_SRD1</a> <li><a href="?table=cutflow_SRD2">cutflow_SRD2</a> </ul> <b>Acceptance and efficiencies:</b> As explained in <a href="https://twiki.cern.ch/twiki/bin/view/AtlasPublic/SupersymmetryPublicResults#summary_of_auxiliary_material">the twiki</a>. <ul> <li> <b>SRATT:</b> <a href="?table=Acc_SRATT">Acc_SRATT</a> <a href="?table=Eff_SRATT">Eff_SRATT</a> <li> <b>SRATW:</b> <a href="?table=Acc_SRATW">Acc_SRATW</a> <a href="?table=Eff_SRATW">Eff_SRATW</a> <li> <b>SRAT0:</b> <a href="?table=Acc_SRAT0">Acc_SRAT0</a> <a href="?table=Eff_SRAT0">Eff_SRAT0</a> <li> <b>SRBTT:</b> <a href="?table=Acc_SRBTT">Acc_SRBTT</a> <a href="?table=Eff_SRBTT">Eff_SRBTT</a> <li> <b>SRBTW:</b> <a href="?table=Acc_SRBTW">Acc_SRBTW</a> <a href="?table=Eff_SRBTW">Eff_SRBTW</a> <li> <b>SRBT0:</b> <a href="?table=Acc_SRBT0">Acc_SRBT0</a> <a href="?table=Eff_SRBT0">Eff_SRBT0</a> <li> <b>SRC1:</b> <a href="?table=Acc_SRC1">Acc_SRC1</a> <a href="?table=Eff_SRC1">Eff_SRC1</a> <li> <b>SRC2:</b> <a href="?table=Acc_SRC2">Acc_SRC2</a> <a href="?table=Eff_SRC2">Eff_SRC2</a> <li> <b>SRC3:</b> <a href="?table=Acc_SRC3">Acc_SRC3</a> <a href="?table=Eff_SRC3">Eff_SRC3</a> <li> <b>SRC4:</b> <a href="?table=Acc_SRC4">Acc_SRC4</a> <a href="?table=Eff_SRC4">Eff_SRC4</a> <li> <b>SRC5:</b> <a href="?table=Acc_SRC5">Acc_SRC5</a> <a href="?table=Eff_SRC5">Eff_SRC5</a> <li> <b>SRD0:</b> <a href="?table=Acc_SRD0">Acc_SRD0</a> <a href="?table=Eff_SRD0">Eff_SRD0</a> <li> <b>SRD1:</b> <a href="?table=Acc_SRD1">Acc_SRD1</a> <a href="?table=Eff_SRD1">Eff_SRD1</a> <li> <b>SRD2:</b> <a href="?table=Acc_SRD2">Acc_SRD2</a> <a href="?table=Eff_SRD2">Eff_SRD2</a> </ul> <b>Truth Code snippets</b> and <b>SLHA</a> files are available under "Resources" (purple button on the left)
<b>- - - - - - - - Overview of HEPData Record - - - - - - - -</b> <br><br> <b>Exclusion contours:</b> <ul> <li><a href="?table=stop_obs">Stop exclusion contour (Obs.)</a> <li><a href="?table=stop_obs_down">Stop exclusion contour (Obs. Down)</a> <li><a href="?table=stop_obs_up">Stop exclusion contour (Obs. Up)</a> <li><a href="?table=stop_exp">Stop exclusion contour (Exp.)</a> <li><a href="?table=stop_exp_down">Stop exclusion contour (Exp. Down)</a> <li><a href="?table=stop_exp_up">Stop exclusion contour (Exp. Up)</a> <li><a href="?table=LQ3u_obs">LQ3u exclusion contour (Obs.)</a> <li><a href="?table=LQ3u_obs_down">LQ3u exclusion contour (Obs. Down)</a> <li><a href="?table=LQ3u_obs_up">LQ3u exclusion contour (Obs. Up)</a> <li><a href="?table=LQ3u_exp">LQ3u exclusion contour (Exp.)</a> <li><a href="?table=LQ3u_exp_down">LQ3u exclusion contour (Exp. Down)</a> <li><a href="?table=LQ3u_exp_up">LQ3u exclusion contour (Exp. Up)</a> </ul> <b>Upper limits:</b> <ul> <li><a href="?table=stop_xSecUpperLimit_obs">stop_xSecUpperLimit_obs</a> <li><a href="?table=stop_xSecUpperLimit_exp">stop_xSecUpperLimit_exp</a> <li><a href="?table=LQ3u_xSecUpperLimit_obs">LQ3u_xSecUpperLimit_obs</a> <li><a href="?table=LQ3u_xSecUpperLimit_exp">LQ3u_xSecUpperLimit_exp</a> </ul> <b>Kinematic distributions:</b> <ul> <li><a href="?table=SRATW_metsigST">SRATW_metsigST</a> <li><a href="?table=SRBTT_m_1fatjet_kt12">SRBTT_m_1fatjet_kt12</a> <li><a href="?table=SRC_RISR">SRC_RISR</a> <li><a href="?table=SRD0_htSig">SRD0_htSig</a> <li><a href="?table=SRD1_htSig">SRD1_htSig</a> <li><a href="?table=SRD2_htSig">SRD2_htSig</a> </ul> <b>Cut flows:</b> <ul> <li><a href="?table=cutflow_SRATT">cutflow_SRATT</a> <li><a href="?table=cutflow_SRATW">cutflow_SRATW</a> <li><a href="?table=cutflow_SRAT0">cutflow_SRAT0</a> <li><a href="?table=cutflow_SRB">cutflow_SRB</a> <li><a href="?table=cutflow_SRC">cutflow_SRC</a> <li><a href="?table=cutflow_SRD0">cutflow_SRD0</a> <li><a href="?table=cutflow_SRD1">cutflow_SRD1</a> <li><a href="?table=cutflow_SRD2">cutflow_SRD2</a> </ul> <b>Acceptance and efficiencies:</b> As explained in <a href="https://twiki.cern.ch/twiki/bin/view/AtlasPublic/SupersymmetryPublicResults#summary_of_auxiliary_material">the twiki</a>. <ul> <li> <b>SRATT:</b> <a href="?table=Acc_SRATT">Acc_SRATT</a> <a href="?table=Eff_SRATT">Eff_SRATT</a> <li> <b>SRATW:</b> <a href="?table=Acc_SRATW">Acc_SRATW</a> <a href="?table=Eff_SRATW">Eff_SRATW</a> <li> <b>SRAT0:</b> <a href="?table=Acc_SRAT0">Acc_SRAT0</a> <a href="?table=Eff_SRAT0">Eff_SRAT0</a> <li> <b>SRBTT:</b> <a href="?table=Acc_SRBTT">Acc_SRBTT</a> <a href="?table=Eff_SRBTT">Eff_SRBTT</a> <li> <b>SRBTW:</b> <a href="?table=Acc_SRBTW">Acc_SRBTW</a> <a href="?table=Eff_SRBTW">Eff_SRBTW</a> <li> <b>SRBT0:</b> <a href="?table=Acc_SRBT0">Acc_SRBT0</a> <a href="?table=Eff_SRBT0">Eff_SRBT0</a> <li> <b>SRC1:</b> <a href="?table=Acc_SRC1">Acc_SRC1</a> <a href="?table=Eff_SRC1">Eff_SRC1</a> <li> <b>SRC2:</b> <a href="?table=Acc_SRC2">Acc_SRC2</a> <a href="?table=Eff_SRC2">Eff_SRC2</a> <li> <b>SRC3:</b> <a href="?table=Acc_SRC3">Acc_SRC3</a> <a href="?table=Eff_SRC3">Eff_SRC3</a> <li> <b>SRC4:</b> <a href="?table=Acc_SRC4">Acc_SRC4</a> <a href="?table=Eff_SRC4">Eff_SRC4</a> <li> <b>SRC5:</b> <a href="?table=Acc_SRC5">Acc_SRC5</a> <a href="?table=Eff_SRC5">Eff_SRC5</a> <li> <b>SRD0:</b> <a href="?table=Acc_SRD0">Acc_SRD0</a> <a href="?table=Eff_SRD0">Eff_SRD0</a> <li> <b>SRD1:</b> <a href="?table=Acc_SRD1">Acc_SRD1</a> <a href="?table=Eff_SRD1">Eff_SRD1</a> <li> <b>SRD2:</b> <a href="?table=Acc_SRD2">Acc_SRD2</a> <a href="?table=Eff_SRD2">Eff_SRD2</a> </ul> <b>Truth Code snippets</b> and <b>SLHA</a> files are available under "Resources" (purple button on the left)
The observed exclusion contour at 95% CL as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$. Masses that are within the contours are excluded.
The observed exclusion contour at 95% CL as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$. Masses that are within the contours are excluded.
The expected exclusion contour at 95% CL as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$. Masses that are within the contour are excluded.
The expected exclusion contour at 95% CL as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$. Masses that are within the contour are excluded.
The minus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.
The minus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.
The plus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.
The plus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.
The minus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.
The minus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.
The plus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.
The plus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.
The observed exclusion contour at 95% CL as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$. Points that are within the contours are excluded.
The observed exclusion contour at 95% CL as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$. Points that are within the contours are excluded.
The expected exclusion contour at 95% CL as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$. Points that are within the contours are excluded.
The expected exclusion contour at 95% CL as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$. Points that are within the contours are excluded.
The minus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$
The minus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$
The plus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$
The plus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$
The plus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$
The plus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$
The minus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$
The minus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$
Model dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{0}_{1})$ signal grid. The column titled 'Leading Region' stores information on which of the fit regions (SRA-B, SRC or SRD) is the dominant based on the expected CLs values.
Model dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{0}_{1})$ signal grid. The column titled 'Leading Region' stores information on which of the fit regions (SRA-B, SRC or SRD) is the dominant based on the expected CLs values.
Expected model dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{0}_{1})$ signal grid. The column titled 'Leading Region' stores information on which of the fit regions (SRA-B, SRC or SRD) is the dominant based on the expected CLs values.
Expected model dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{0}_{1})$ signal grid. The column titled 'Leading Region' stores information on which of the fit regions (SRA-B, SRC or SRD) is the dominant based on the expected CLs values.
Model dependent upper limit on the cross section for the $LQ_{3}^{u}$ signal grid with $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau))=0$ %. Only the SRA-B fit region is considered in this interpretation.
Model dependent upper limit on the cross section for the $LQ_{3}^{u}$ signal grid with $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau))=0$ %. Only the SRA-B fit region is considered in this interpretation.
Expected model dependent upper limit on the cross section for the $LQ_{3}^{u}$ signal grid with $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau))=0$ %. Only the SRA-B fit region is considered in this interpretation.
Expected model dependent upper limit on the cross section for the $LQ_{3}^{u}$ signal grid with $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau))=0$ %. Only the SRA-B fit region is considered in this interpretation.
The distributions of $S$ in SRA-TW. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.
The distributions of $S$ in SRA-TW. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.
The distributions of $\it{m}^{\mathrm{R=1.2}}_{1}$ in SRB-TT. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.
The distributions of $\it{m}^{\mathrm{R=1.2}}_{1}$ in SRB-TT. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.
The distributions of R$_{ISR}$ in SRC signal regions before R$_{ISR}$ cuts are applied. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.
The distributions of R$_{ISR}$ in SRC signal regions before R$_{ISR}$ cuts are applied. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.
The distributions of $E^{miss}_{T}/\sqrt{H_{T}}$ in SRD0. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.
The distributions of $E^{miss}_{T}/\sqrt{H_{T}}$ in SRD0. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.
The distributions of $E^{miss}_{T}/\sqrt{H_{T}}$ in SRD1. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.
The distributions of $E^{miss}_{T}/\sqrt{H_{T}}$ in SRD1. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.
The distributions of $E^{miss}_{T}/\sqrt{H_{T}}$ in SRD2. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.
The distributions of $E^{miss}_{T}/\sqrt{H_{T}}$ in SRD2. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (1300,1)\ \mathrm{GeV} $ in SRA-TT. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 30000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (1300,1)\ \mathrm{GeV} $ in SRA-TT. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 30000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (1300,1)\ \mathrm{GeV} $ in SRA-TW. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 30000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (1300,1)\ \mathrm{GeV} $ in SRA-TW. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 30000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (1300,1)\ \mathrm{GeV} $ in SRA-T0. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 30000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (1300,1)\ \mathrm{GeV} $ in SRA-T0. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 30000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (700,400)\ \mathrm{GeV} $ in signal regions SRB-TT, SRB-TW and SRB-T0. The regions differ by the last cut applied. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 60000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (700,400)\ \mathrm{GeV} $ in signal regions SRB-TT, SRB-TW and SRB-T0. The regions differ by the last cut applied. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 60000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (500,327)\ \mathrm{GeV} $ in regions SRC-1, SRC-2, SRC-3, SRC-4 and SRC-5. The regions differ by the last cut applied. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 150000 raw MC events with filter efficiency of 0.384 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (500,327)\ \mathrm{GeV} $ in regions SRC-1, SRC-2, SRC-3, SRC-4 and SRC-5. The regions differ by the last cut applied. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 150000 raw MC events with filter efficiency of 0.384 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (550,500)\ \mathrm{GeV} $ in SRD0. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 90000 raw MC events with filter efficiency of 0.428 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (550,500)\ \mathrm{GeV} $ in SRD0. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 90000 raw MC events with filter efficiency of 0.428 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (550,500)\ \mathrm{GeV} $ in SRD1. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 90000 raw MC events with filter efficiency of 0.428 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (550,500)\ \mathrm{GeV} $ in SRD1. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 90000 raw MC events with filter efficiency of 0.428 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (550,500)\ \mathrm{GeV} $ in SRD2. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 90000 raw MC events with filter efficiency of 0.428 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (550,500)\ \mathrm{GeV} $ in SRD2. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 90000 raw MC events with filter efficiency of 0.428 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Signal acceptance in SRA-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal acceptance in SRA-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in SRA-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.
Signal efficiency in SRA-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.
Signal acceptance in SRA-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal acceptance in SRA-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in SRA-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.
Signal efficiency in SRA-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.
Signal acceptance in SRA-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal acceptance in SRA-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in SRA-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.
Signal efficiency in SRA-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.
Signal acceptance in SRB-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal acceptance in SRB-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in SRB-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.
Signal efficiency in SRB-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.
Signal acceptance in SRB-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal acceptance in SRB-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in SRB-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.
Signal efficiency in SRB-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.
Signal acceptance in SRB-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal acceptance in SRB-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in SRB-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.
Signal efficiency in SRB-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.
Signal acceptance in SRC1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRC1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRC1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRC1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRC2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRC2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRC2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRC2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRC3 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRC3 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRC3 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRC3 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRC4 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRC4 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRC4 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ plane showed in the paper plot.
Signal efficiency in SRC4 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ plane showed in the paper plot.
Signal acceptance in SRC5 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ plane showed in the paper plot.
Signal acceptance in SRC5 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ plane showed in the paper plot.
Signal efficiency in SRC5 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRC5 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRD0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRD0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRD0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRD0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRD1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRD1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRD1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRD1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRD2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRD2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRD2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRD2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
In this paper, a new technique for reconstructing and identifying hadronically decaying $\tau^+\tau^-$ pairs with a large Lorentz boost, referred to as the di-$\tau$ tagger, is developed and used for the first time in the ATLAS experiment at the Large Hadron Collider. A benchmark di-$\tau$ tagging selection is employed in the search for resonant Higgs boson pair production, where one Higgs boson decays into a boosted $b\bar{b}$ pair and the other into a boosted $\tau^+\tau^-$ pair, with two hadronically decaying $\tau$-leptons in the final state. Using 139 fb$^{-1}$ of proton$-$proton collision data recorded at a centre-of-mass energy of 13 TeV, the efficiency of the di-$\tau$ tagger is determined and the background with quark- or gluon-initiated jets misidentified as di-$\tau$ objects is estimated. The search for a heavy, narrow, scalar resonance produced via gluon$-$gluon fusion and decaying into two Higgs bosons is carried out in the mass range 1$-$3 TeV using the same dataset. No deviations from the Standard Model predictions are observed, and 95% confidence-level exclusion limits are set on this model.
Signal acceptance times selection efficiency as a function of the resonance mass, at various stages of the event selection. From top to bottom: an event pre-selection (trigger, object definitions and $E_{T}^{miss}>10$ GeV) is performed first; the requirements on the di-$\tau$ object and large-$R$ jet detailed in the text are then applied; finally, the $HH$ SR definition must be satisfied.
Signal acceptance times selection efficiency as a function of the resonance mass, at various stages of the event selection. From top to bottom: an event pre-selection (trigger, object definitions and $E_{T}^{miss}>10$ GeV) is performed first; the requirements on the di-$\tau$ object and large-$R$ jet detailed in the text are then applied; finally, the $HH$ SR definition must be satisfied.
Distribution of $m^{vis}_{HH}$ after applying all the event selection that define the $HH$ SR, except the requirement on $m^{vis}_{HH}$. The background labelled as "Others" contains $W$+jets, diboson, $t\bar{t}$ and single-top-quark processes. The $X\rightarrow HH \rightarrow b\bar{b}\tau^{+}\tau^{-}$ signal is overlaid for two resonance mass hypotheses with a cross-section set to the expected limit, while all backgrounds are pre-fit. The first and the last bins contains the under-flow and over-flow bin entries, respectively. The hatched bands represent combined statistical and systematic uncertainties.
Distribution of $m^{vis}_{HH}$ after applying all the event selection that define the $HH$ SR, except the requirement on $m^{vis}_{HH}$. The background labelled as "Others" contains $W$+jets, diboson, $t\bar{t}$ and single-top-quark processes. The $X\rightarrow HH \rightarrow b\bar{b}\tau^{+}\tau^{-}$ signal is overlaid for two resonance mass hypotheses with a cross-section set to the expected limit, while all backgrounds are pre-fit. The first and the last bins contains the under-flow and over-flow bin entries, respectively. The hatched bands represent combined statistical and systematic uncertainties.
Event yields of the various estimated backgrounds and data, computed in the signal region of the search for $X\rightarrow HH \rightarrow b\bar{b}\tau^{+}\tau^{-}$. The background labelled as "Others" contains $W$+jets, diboson, $t\bar{t}$ and single-top-quark processes. Statistical and systematic uncertainties are quoted. The background yields and uncertainties are pre-fit and are found to be similar to those post-fit.
Event yields of the various estimated backgrounds and data, computed in the signal region of the search for $X\rightarrow HH \rightarrow b\bar{b}\tau^{+}\tau^{-}$. The background labelled as "Others" contains $W$+jets, diboson, $t\bar{t}$ and single-top-quark processes. Statistical and systematic uncertainties are quoted. The background yields and uncertainties are pre-fit and are found to be similar to those post-fit.
Expected and observed 95% CL upper limits on the production of a heavy, narrow-width, scalar resonance decaying to a pair of Higgs bosons ($X\rightarrow HH$). The final state used in the search consists of a boosted $b\bar{b}$ pair and a boosted hadronically decaying $\tau^{+}\tau^{-}$ pair, and the SM braching ratio of the Higgs boson are assumed. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit are indicated by the error bands. Two different requirements are applied on the visible mass of the two boosted Higgs boson candidates for the resonance mass hypotheses of 1.6 TeV and 2.5 TeV, leading to discontinuities in the limits (at 1.6 TeV, the difference between imposing no requirement and $m^{vis}_{HH}>900$ GeV is less than 1% though).
Expected and observed 95% CL upper limits on the production of a heavy, narrow-width, scalar resonance decaying to a pair of Higgs bosons ($X\rightarrow HH$). The final state used in the search consists of a boosted $b\bar{b}$ pair and a boosted hadronically decaying $\tau^{+}\tau^{-}$ pair, and the SM braching ratio of the Higgs boson are assumed. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit are indicated by the error bands. Two different requirements are applied on the visible mass of the two boosted Higgs boson candidates for the resonance mass hypotheses of 1.6 TeV and 2.5 TeV, leading to discontinuities in the limits (at 1.6 TeV, the difference between imposing no requirement and $m^{vis}_{HH}>900$ GeV is less than 1% though).
Differential cross-sections are measured for top-quark pair production in the all-hadronic decay mode, using proton$-$proton collision events collected by the ATLAS experiment in which all six decay jets are separately resolved. Absolute and normalised single- and double-differential cross-sections are measured at particle and parton level as a function of various kinematic variables. Emphasis is placed on well-measured observables in fully reconstructed final states, as well as on the study of correlations between the top-quark pair system and additional jet radiation identified in the event. The study is performed using data from proton$-$proton collisions at $\sqrt{s}=13~\mbox{TeV}$ collected by the ATLAS detector at CERN's Large Hadron Collider in 2015 and 2016, corresponding to an integrated luminosity of $\mbox{36.1 fb}^{-1}$. The rapidities of the individual top quarks and of the top-quark pair are well modelled by several independent event generators. Significant mismodelling is observed in the transverse momenta of the leading three jet emissions, while the leading top-quark transverse momentum and top-quark pair transverse momentum are both found to be incompatible with several theoretical predictions.
- - - - - - - - Overview of HEPData Record - - - - - - - - <br/><br/> <b>Fiducial phase space definition:</b><br/> <ul> <li> NLEP = 0, either E or MU, PT > 15 GeV, ABS ETA < 1.37 <li> NJETS >= 6, PT > 25 GeV, ABS ETA < 2.5 <li> NBJETS >= 2 </ul><br/> <b>Particle level:</b><br/> <u>1D:</u><br/> Spectra: <ul> <li><a href="103063?version=1&table=Table 1">1/SIG*DSIG/DDR_E1J1</a> (Table 1) <li><a href="103063?version=1&table=Table 3">DSIG/DDR_E1J1</a> (Table 3) <li><a href="103063?version=1&table=Table 5">1/SIG*DSIG/DABS_T1_Y</a> (Table 5) <li><a href="103063?version=1&table=Table 7">DSIG/DABS_T1_Y</a> (Table 7) <li><a href="103063?version=1&table=Table 9">1/SIG*DSIG/DTT_M</a> (Table 9) <li><a href="103063?version=1&table=Table 11">DSIG/DTT_M</a> (Table 11) <li><a href="103063?version=1&table=Table 13">1/SIG*DSIG/DABS_T2_Y</a> (Table 13) <li><a href="103063?version=1&table=Table 15">DSIG/DABS_T2_Y</a> (Table 15) <li><a href="103063?version=1&table=Table 17">1/SIG*DSIG/DABS_TT_Y</a> (Table 17) <li><a href="103063?version=1&table=Table 19">DSIG/DABS_TT_Y</a> (Table 19) <li><a href="103063?version=1&table=Table 21">1/SIG*DSIG/DT1_PT</a> (Table 21) <li><a href="103063?version=1&table=Table 23">DSIG/DT1_PT</a> (Table 23) <li><a href="103063?version=1&table=Table 25">1/SIG*DSIG/DT2_PT</a> (Table 25) <li><a href="103063?version=1&table=Table 27">DSIG/DT2_PT</a> (Table 27) <li><a href="103063?version=1&table=Table 29">1/SIG*DSIG/DTT_PT</a> (Table 29) <li><a href="103063?version=1&table=Table 31">DSIG/DTT_PT</a> (Table 31) <li><a href="103063?version=1&table=Table 33">1/SIG*DSIG/DN_JETS</a> (Table 33) <li><a href="103063?version=1&table=Table 35">DSIG/DN_JETS</a> (Table 35) <li><a href="103063?version=1&table=Table 37">1/SIG*DSIG/DDELTAPHI</a> (Table 37) <li><a href="103063?version=1&table=Table 39">DSIG/DDELTAPHI</a> (Table 39) <li><a href="103063?version=1&table=Table 41">1/SIG*DSIG/DABSPOUT</a> (Table 41) <li><a href="103063?version=1&table=Table 43">DSIG/DABSPOUT</a> (Table 43) <li><a href="103063?version=1&table=Table 45">1/SIG*DSIG/DABSPCROSS</a> (Table 45) <li><a href="103063?version=1&table=Table 47">DSIG/DABSPCROSS</a> (Table 47) <li><a href="103063?version=1&table=Table 49">1/SIG*DSIG/DZ_TT</a> (Table 49) <li><a href="103063?version=1&table=Table 51">DSIG/DZ_TT</a> (Table 51) <li><a href="103063?version=1&table=Table 53">1/SIG*DSIG/DHT_TT</a> (Table 53) <li><a href="103063?version=1&table=Table 55">DSIG/DHT_TT</a> (Table 55) <li><a href="103063?version=1&table=Table 57">1/SIG*DSIG/DABS_Y_BOOST </a> (Table 57) <li><a href="103063?version=1&table=Table 59">DSIG/DABS_Y_BOOST </a> (Table 59) <li><a href="103063?version=1&table=Table 61">1/SIG*DSIG/DCHI_TT</a> (Table 61) <li><a href="103063?version=1&table=Table 63">DSIG/DCHI_TT</a> (Table 63) <li><a href="103063?version=1&table=Table 65">1/SIG*DSIG/DRWT1</a> (Table 65) <li><a href="103063?version=1&table=Table 67">DSIG/DRWT1</a> (Table 67) <li><a href="103063?version=1&table=Table 69">1/SIG*DSIG/DRWT2</a> (Table 69) <li><a href="103063?version=1&table=Table 71">DSIG/DRWT2</a> (Table 71) <li><a href="103063?version=1&table=Table 73">1/SIG*DSIG/DRWB1</a> (Table 73) <li><a href="103063?version=1&table=Table 75">DSIG/DRWB1</a> (Table 75) <li><a href="103063?version=1&table=Table 77">1/SIG*DSIG/DRWB2</a> (Table 77) <li><a href="103063?version=1&table=Table 79">DSIG/DRWB2</a> (Table 79) <li><a href="103063?version=1&table=Table 81">1/SIG*DSIG/DDR_E1TC</a> (Table 81) <li><a href="103063?version=1&table=Table 83">DSIG/DDR_E1TC</a> (Table 83) <li><a href="103063?version=1&table=Table 85">1/SIG*DSIG/DDR_E2TC</a> (Table 85) <li><a href="103063?version=1&table=Table 87">DSIG/DDR_E2TC</a> (Table 87) <li><a href="103063?version=1&table=Table 89">1/SIG*DSIG/DDR_E3TC</a> (Table 89) <li><a href="103063?version=1&table=Table 91">DSIG/DDR_E3TC</a> (Table 91) <li><a href="103063?version=1&table=Table 93">1/SIG*DSIG/DRPT_E1T1</a> (Table 93) <li><a href="103063?version=1&table=Table 95">DSIG/DRPT_E1T1</a> (Table 95) <li><a href="103063?version=1&table=Table 97">1/SIG*DSIG/DRPT_E2T1</a> (Table 97) <li><a href="103063?version=1&table=Table 99">DSIG/DRPT_E2T1</a> (Table 99) <li><a href="103063?version=1&table=Table 101">1/SIG*DSIG/DRPT_E3T1</a> (Table 101) <li><a href="103063?version=1&table=Table 103">DSIG/DRPT_E3T1</a> (Table 103) <li><a href="103063?version=1&table=Table 105">1/SIG*DSIG/DRPT_TTE1</a> (Table 105) <li><a href="103063?version=1&table=Table 107">DSIG/DRPT_TTE1</a> (Table 107) <li><a href="103063?version=1&table=Table 109">1/SIG*DSIG/DRPT_E1J1</a> (Table 109) <li><a href="103063?version=1&table=Table 111">DSIG/DRPT_E1J1</a> (Table 111) <li><a href="103063?version=1&table=Table 113">1/SIG*DSIG/DRPT_E2J1</a> (Table 113) <li><a href="103063?version=1&table=Table 115">DSIG/DRPT_E2J1</a> (Table 115) <li><a href="103063?version=1&table=Table 117">1/SIG*DSIG/DRPT_E3J1</a> (Table 117) <li><a href="103063?version=1&table=Table 119">DSIG/DRPT_E3J1</a> (Table 119) <li><a href="103063?version=1&table=Table 121">1/SIG*DSIG/DDR_E2E1</a> (Table 121) <li><a href="103063?version=1&table=Table 123">DSIG/DDR_E2E1</a> (Table 123) <li><a href="103063?version=1&table=Table 125">1/SIG*DSIG/DDR_E3E1</a> (Table 125) <li><a href="103063?version=1&table=Table 127">DSIG/DDR_E3E1</a> (Table 127) <li><a href="103063?version=1&table=Table 129">1/SIG*DSIG/DRPT_E2E1</a> (Table 129) <li><a href="103063?version=1&table=Table 131">DSIG/DRPT_E2E1</a> (Table 131) <li><a href="103063?version=1&table=Table 133">1/SIG*DSIG/DRPT_E3E1</a> (Table 133) <li><a href="103063?version=1&table=Table 135">DSIG/DRPT_E3E1</a> (Table 135) <li><a href="103063?version=1&table=Table 137">SIG</a> (Table 137) </ul><br/> Covariances: <ul> <li><a href="103063?version=1&table=Table 2">1/SIG*DSIG/DDR_E1J1</a> (Table 2) <li><a href="103063?version=1&table=Table 4">DSIG/DDR_E1J1</a> (Table 4) <li><a href="103063?version=1&table=Table 6">1/SIG*DSIG/DABS_T1_Y</a> (Table 6) <li><a href="103063?version=1&table=Table 8">DSIG/DABS_T1_Y</a> (Table 8) <li><a href="103063?version=1&table=Table 10">1/SIG*DSIG/DTT_M</a> (Table 10) <li><a href="103063?version=1&table=Table 12">DSIG/DTT_M</a> (Table 12) <li><a href="103063?version=1&table=Table 14">1/SIG*DSIG/DABS_T2_Y</a> (Table 14) <li><a href="103063?version=1&table=Table 16">DSIG/DABS_T2_Y</a> (Table 16) <li><a href="103063?version=1&table=Table 18">1/SIG*DSIG/DABS_TT_Y</a> (Table 18) <li><a href="103063?version=1&table=Table 20">DSIG/DABS_TT_Y</a> (Table 20) <li><a href="103063?version=1&table=Table 22">1/SIG*DSIG/DT1_PT</a> (Table 22) <li><a href="103063?version=1&table=Table 24">DSIG/DT1_PT</a> (Table 24) <li><a href="103063?version=1&table=Table 26">1/SIG*DSIG/DT2_PT</a> (Table 26) <li><a href="103063?version=1&table=Table 28">DSIG/DT2_PT</a> (Table 28) <li><a href="103063?version=1&table=Table 30">1/SIG*DSIG/DTT_PT</a> (Table 30) <li><a href="103063?version=1&table=Table 32">DSIG/DTT_PT</a> (Table 32) <li><a href="103063?version=1&table=Table 34">1/SIG*DSIG/DN_JETS</a> (Table 34) <li><a href="103063?version=1&table=Table 36">DSIG/DN_JETS</a> (Table 36) <li><a href="103063?version=1&table=Table 38">1/SIG*DSIG/DDELTAPHI</a> (Table 38) <li><a href="103063?version=1&table=Table 40">DSIG/DDELTAPHI</a> (Table 40) <li><a href="103063?version=1&table=Table 42">1/SIG*DSIG/DABSPOUT</a> (Table 42) <li><a href="103063?version=1&table=Table 44">DSIG/DABSPOUT</a> (Table 44) <li><a href="103063?version=1&table=Table 46">1/SIG*DSIG/DABSPCROSS</a> (Table 46) <li><a href="103063?version=1&table=Table 48">DSIG/DABSPCROSS</a> (Table 48) <li><a href="103063?version=1&table=Table 50">1/SIG*DSIG/DZ_TT</a> (Table 50) <li><a href="103063?version=1&table=Table 52">DSIG/DZ_TT</a> (Table 52) <li><a href="103063?version=1&table=Table 54">1/SIG*DSIG/DHT_TT</a> (Table 54) <li><a href="103063?version=1&table=Table 56">DSIG/DHT_TT</a> (Table 56) <li><a href="103063?version=1&table=Table 58">1/SIG*DSIG/DABS_Y_BOOST </a> (Table 58) <li><a href="103063?version=1&table=Table 60">DSIG/DABS_Y_BOOST </a> (Table 60) <li><a href="103063?version=1&table=Table 62">1/SIG*DSIG/DCHI_TT</a> (Table 62) <li><a href="103063?version=1&table=Table 64">DSIG/DCHI_TT</a> (Table 64) <li><a href="103063?version=1&table=Table 66">1/SIG*DSIG/DRWT1</a> (Table 66) <li><a href="103063?version=1&table=Table 68">DSIG/DRWT1</a> (Table 68) <li><a href="103063?version=1&table=Table 70">1/SIG*DSIG/DRWT2</a> (Table 70) <li><a href="103063?version=1&table=Table 72">DSIG/DRWT2</a> (Table 72) <li><a href="103063?version=1&table=Table 74">1/SIG*DSIG/DRWB1</a> (Table 74) <li><a href="103063?version=1&table=Table 76">DSIG/DRWB1</a> (Table 76) <li><a href="103063?version=1&table=Table 78">1/SIG*DSIG/DRWB2</a> (Table 78) <li><a href="103063?version=1&table=Table 80">DSIG/DRWB2</a> (Table 80) <li><a href="103063?version=1&table=Table 82">1/SIG*DSIG/DDR_E1TC</a> (Table 82) <li><a href="103063?version=1&table=Table 84">DSIG/DDR_E1TC</a> (Table 84) <li><a href="103063?version=1&table=Table 86">1/SIG*DSIG/DDR_E2TC</a> (Table 86) <li><a href="103063?version=1&table=Table 88">DSIG/DDR_E2TC</a> (Table 88) <li><a href="103063?version=1&table=Table 90">1/SIG*DSIG/DDR_E3TC</a> (Table 90) <li><a href="103063?version=1&table=Table 92">DSIG/DDR_E3TC</a> (Table 92) <li><a href="103063?version=1&table=Table 94">1/SIG*DSIG/DRPT_E1T1</a> (Table 94) <li><a href="103063?version=1&table=Table 96">DSIG/DRPT_E1T1</a> (Table 96) <li><a href="103063?version=1&table=Table 98">1/SIG*DSIG/DRPT_E2T1</a> (Table 98) <li><a href="103063?version=1&table=Table 100">DSIG/DRPT_E2T1</a> (Table 100) <li><a href="103063?version=1&table=Table 102">1/SIG*DSIG/DRPT_E3T1</a> (Table 102) <li><a href="103063?version=1&table=Table 104">DSIG/DRPT_E3T1</a> (Table 104) <li><a href="103063?version=1&table=Table 106">1/SIG*DSIG/DRPT_TTE1</a> (Table 106) <li><a href="103063?version=1&table=Table 108">DSIG/DRPT_TTE1</a> (Table 108) <li><a href="103063?version=1&table=Table 110">1/SIG*DSIG/DRPT_E1J1</a> (Table 110) <li><a href="103063?version=1&table=Table 112">DSIG/DRPT_E1J1</a> (Table 112) <li><a href="103063?version=1&table=Table 114">1/SIG*DSIG/DRPT_E2J1</a> (Table 114) <li><a href="103063?version=1&table=Table 116">DSIG/DRPT_E2J1</a> (Table 116) <li><a href="103063?version=1&table=Table 118">1/SIG*DSIG/DRPT_E3J1</a> (Table 118) <li><a href="103063?version=1&table=Table 120">DSIG/DRPT_E3J1</a> (Table 120) <li><a href="103063?version=1&table=Table 122">1/SIG*DSIG/DDR_E2E1</a> (Table 122) <li><a href="103063?version=1&table=Table 124">DSIG/DDR_E2E1</a> (Table 124) <li><a href="103063?version=1&table=Table 126">1/SIG*DSIG/DDR_E3E1</a> (Table 126) <li><a href="103063?version=1&table=Table 128">DSIG/DDR_E3E1</a> (Table 128) <li><a href="103063?version=1&table=Table 130">1/SIG*DSIG/DRPT_E2E1</a> (Table 130) <li><a href="103063?version=1&table=Table 132">DSIG/DRPT_E2E1</a> (Table 132) <li><a href="103063?version=1&table=Table 134">1/SIG*DSIG/DRPT_E3E1</a> (Table 134) <li><a href="103063?version=1&table=Table 136">DSIG/DRPT_E3E1</a> (Table 136) </ul><br/> <u>2D:</u><br/> Spectra: <ul> <li><a href="103063?version=1&table=Table 138">1/SIG*D2SIG/DT1_PT/DN_JETS (N_JETS = 6)</a> (Table 138) <li><a href="103063?version=1&table=Table 139">1/SIG*D2SIG/DT1_PT/DN_JETS (N_JETS = 7)</a> (Table 139) <li><a href="103063?version=1&table=Table 140">1/SIG*D2SIG/DT1_PT/DN_JETS (N_JETS = 8)</a> (Table 140) <li><a href="103063?version=1&table=Table 141">1/SIG*D2SIG/DT1_PT/DN_JETS (N_JETS > 8)</a> (Table 141) <li><a href="103063?version=1&table=Table 152">D2SIG/DT1_PT/DN_JETS (N_JETS = 6)</a> (Table 152) <li><a href="103063?version=1&table=Table 153">D2SIG/DT1_PT/DN_JETS (N_JETS = 7)</a> (Table 153) <li><a href="103063?version=1&table=Table 154">D2SIG/DT1_PT/DN_JETS (N_JETS = 8)</a> (Table 154) <li><a href="103063?version=1&table=Table 155">D2SIG/DT1_PT/DN_JETS (N_JETS > 8)</a> (Table 155) <li><a href="103063?version=1&table=Table 166">1/SIG*D2SIG/DT2_PT/DN_JETS (N_JETS = 6)</a> (Table 166) <li><a href="103063?version=1&table=Table 167">1/SIG*D2SIG/DT2_PT/DN_JETS (N_JETS = 7)</a> (Table 167) <li><a href="103063?version=1&table=Table 168">1/SIG*D2SIG/DT2_PT/DN_JETS (N_JETS = 8)</a> (Table 168) <li><a href="103063?version=1&table=Table 169">1/SIG*D2SIG/DT2_PT/DN_JETS (N_JETS > 8)</a> (Table 169) <li><a href="103063?version=1&table=Table 180">D2SIG/DT2_PT/DN_JETS (N_JETS = 6)</a> (Table 180) <li><a href="103063?version=1&table=Table 181">D2SIG/DT2_PT/DN_JETS (N_JETS = 7)</a> (Table 181) <li><a href="103063?version=1&table=Table 182">D2SIG/DT2_PT/DN_JETS (N_JETS = 8)</a> (Table 182) <li><a href="103063?version=1&table=Table 183">D2SIG/DT2_PT/DN_JETS (N_JETS > 8)</a> (Table 183) <li><a href="103063?version=1&table=Table 194">1/SIG*D2SIG/DTT_PT/DN_JETS (N_JETS = 6)</a> (Table 194) <li><a href="103063?version=1&table=Table 195">1/SIG*D2SIG/DTT_PT/DN_JETS (N_JETS = 7)</a> (Table 195) <li><a href="103063?version=1&table=Table 196">1/SIG*D2SIG/DTT_PT/DN_JETS (N_JETS = 8)</a> (Table 196) <li><a href="103063?version=1&table=Table 197">1/SIG*D2SIG/DTT_PT/DN_JETS (N_JETS > 8)</a> (Table 197) <li><a href="103063?version=1&table=Table 208">D2SIG/DTT_PT/DN_JETS (N_JETS = 6)</a> (Table 208) <li><a href="103063?version=1&table=Table 209">D2SIG/DTT_PT/DN_JETS (N_JETS = 7)</a> (Table 209) <li><a href="103063?version=1&table=Table 210">D2SIG/DTT_PT/DN_JETS (N_JETS = 8)</a> (Table 210) <li><a href="103063?version=1&table=Table 211">D2SIG/DTT_PT/DN_JETS (N_JETS > 8)</a> (Table 211) <li><a href="103063?version=1&table=Table 222">1/SIG*D2SIG/DABSPOUT/DN_JETS (N_JETS = 6)</a> (Table 222) <li><a href="103063?version=1&table=Table 223">1/SIG*D2SIG/DABSPOUT/DN_JETS (N_JETS = 7)</a> (Table 223) <li><a href="103063?version=1&table=Table 224">1/SIG*D2SIG/DABSPOUT/DN_JETS (N_JETS = 8)</a> (Table 224) <li><a href="103063?version=1&table=Table 225">1/SIG*D2SIG/DABSPOUT/DN_JETS (N_JETS > 8)</a> (Table 225) <li><a href="103063?version=1&table=Table 236">D2SIG/DABSPOUT/DN_JETS (N_JETS = 6)</a> (Table 236) <li><a href="103063?version=1&table=Table 237">D2SIG/DABSPOUT/DN_JETS (N_JETS = 7)</a> (Table 237) <li><a href="103063?version=1&table=Table 238">D2SIG/DABSPOUT/DN_JETS (N_JETS = 8)</a> (Table 238) <li><a href="103063?version=1&table=Table 239">D2SIG/DABSPOUT/DN_JETS (N_JETS > 8)</a> (Table 239) <li><a href="103063?version=1&table=Table 250">1/SIG*D2SIG/DDELTAPHI/DN_JETS (N_JETS = 6)</a> (Table 250) <li><a href="103063?version=1&table=Table 251">1/SIG*D2SIG/DDELTAPHI/DN_JETS (N_JETS = 7)</a> (Table 251) <li><a href="103063?version=1&table=Table 252">1/SIG*D2SIG/DDELTAPHI/DN_JETS (N_JETS = 8)</a> (Table 252) <li><a href="103063?version=1&table=Table 253">1/SIG*D2SIG/DDELTAPHI/DN_JETS (N_JETS > 8)</a> (Table 253) <li><a href="103063?version=1&table=Table 264">D2SIG/DDELTAPHI/DN_JETS (N_JETS = 6)</a> (Table 264) <li><a href="103063?version=1&table=Table 265">D2SIG/DDELTAPHI/DN_JETS (N_JETS = 7)</a> (Table 265) <li><a href="103063?version=1&table=Table 266">D2SIG/DDELTAPHI/DN_JETS (N_JETS = 8)</a> (Table 266) <li><a href="103063?version=1&table=Table 267">D2SIG/DDELTAPHI/DN_JETS (N_JETS > 8)</a> (Table 267) <li><a href="103063?version=1&table=Table 278">1/SIG*D2SIG/DABSPCROSS/DN_JETS (N_JETS = 6)</a> (Table 278) <li><a href="103063?version=1&table=Table 279">1/SIG*D2SIG/DABSPCROSS/DN_JETS (N_JETS = 7)</a> (Table 279) <li><a href="103063?version=1&table=Table 280">1/SIG*D2SIG/DABSPCROSS/DN_JETS (N_JETS = 8)</a> (Table 280) <li><a href="103063?version=1&table=Table 281">1/SIG*D2SIG/DABSPCROSS/DN_JETS (N_JETS > 8)</a> (Table 281) <li><a href="103063?version=1&table=Table 292">D2SIG/DABSPCROSS/DN_JETS (N_JETS = 6)</a> (Table 292) <li><a href="103063?version=1&table=Table 293">D2SIG/DABSPCROSS/DN_JETS (N_JETS = 7)</a> (Table 293) <li><a href="103063?version=1&table=Table 294">D2SIG/DABSPCROSS/DN_JETS (N_JETS = 8)</a> (Table 294) <li><a href="103063?version=1&table=Table 295">D2SIG/DABSPCROSS/DN_JETS (N_JETS > 8)</a> (Table 295) <li><a href="103063?version=1&table=Table 306">1/SIG*D2SIG/DT2_PT/DTT_M ( 0.0 GeV < TT_M < 620.0 GeV)</a> (Table 306) <li><a href="103063?version=1&table=Table 307">1/SIG*D2SIG/DT2_PT/DTT_M ( 620.0 GeV < TT_M < 835.0 GeV)</a> (Table 307) <li><a href="103063?version=1&table=Table 308">1/SIG*D2SIG/DT2_PT/DTT_M ( 835.0 GeV < TT_M < 1050.0 GeV)</a> (Table 308) <li><a href="103063?version=1&table=Table 309">1/SIG*D2SIG/DT2_PT/DTT_M ( 1050.0 GeV < TT_M < 3000.0 GeV)</a> (Table 309) <li><a href="103063?version=1&table=Table 320">D2SIG/DT2_PT/DTT_M ( 0.0 GeV < TT_M < 620.0 GeV)</a> (Table 320) <li><a href="103063?version=1&table=Table 321">D2SIG/DT2_PT/DTT_M ( 620.0 GeV < TT_M < 835.0 GeV)</a> (Table 321) <li><a href="103063?version=1&table=Table 322">D2SIG/DT2_PT/DTT_M ( 835.0 GeV < TT_M < 1050.0 GeV)</a> (Table 322) <li><a href="103063?version=1&table=Table 323">D2SIG/DT2_PT/DTT_M ( 1050.0 GeV < TT_M < 3000.0 GeV)</a> (Table 323) <li><a href="103063?version=1&table=Table 334">1/SIG*D2SIG/DTT_PT/DTT_M ( 0.0 GeV < TT_M < 620.0 GeV)</a> (Table 334) <li><a href="103063?version=1&table=Table 335">1/SIG*D2SIG/DTT_PT/DTT_M ( 620.0 GeV < TT_M < 835.0 GeV)</a> (Table 335) <li><a href="103063?version=1&table=Table 336">1/SIG*D2SIG/DTT_PT/DTT_M ( 835.0 GeV < TT_M < 1050.0 GeV)</a> (Table 336) <li><a href="103063?version=1&table=Table 337">1/SIG*D2SIG/DTT_PT/DTT_M ( 1050.0 GeV < TT_M < 3000.0 GeV)</a> (Table 337) <li><a href="103063?version=1&table=Table 348">D2SIG/DTT_PT/DTT_M ( 0.0 GeV < TT_M < 620.0 GeV)</a> (Table 348) <li><a href="103063?version=1&table=Table 349">D2SIG/DTT_PT/DTT_M ( 620.0 GeV < TT_M < 835.0 GeV)</a> (Table 349) <li><a href="103063?version=1&table=Table 350">D2SIG/DTT_PT/DTT_M ( 835.0 GeV < TT_M < 1050.0 GeV)</a> (Table 350) <li><a href="103063?version=1&table=Table 351">D2SIG/DTT_PT/DTT_M ( 1050.0 GeV < TT_M < 3000.0 GeV)</a> (Table 351) <li><a href="103063?version=1&table=Table 362">1/SIG*D2SIG/DABS_TT_Y/DTT_M ( 0.0 GeV < TT_M < 620.0 GeV)</a> (Table 362) <li><a href="103063?version=1&table=Table 363">1/SIG*D2SIG/DABS_TT_Y/DTT_M ( 620.0 GeV < TT_M < 835.0 GeV)</a> (Table 363) <li><a href="103063?version=1&table=Table 364">1/SIG*D2SIG/DABS_TT_Y/DTT_M ( 835.0 GeV < TT_M < 1050.0 GeV)</a> (Table 364) <li><a href="103063?version=1&table=Table 365">1/SIG*D2SIG/DABS_TT_Y/DTT_M ( 1050.0 GeV < TT_M < 3000.0 GeV)</a> (Table 365) <li><a href="103063?version=1&table=Table 376">D2SIG/DABS_TT_Y/DTT_M ( 0.0 GeV < TT_M < 620.0 GeV)</a> (Table 376) <li><a href="103063?version=1&table=Table 377">D2SIG/DABS_TT_Y/DTT_M ( 620.0 GeV < TT_M < 835.0 GeV)</a> (Table 377) <li><a href="103063?version=1&table=Table 378">D2SIG/DABS_TT_Y/DTT_M ( 835.0 GeV < TT_M < 1050.0 GeV)</a> (Table 378) <li><a href="103063?version=1&table=Table 379">D2SIG/DABS_TT_Y/DTT_M ( 1050.0 GeV < TT_M < 3000.0 GeV)</a> (Table 379) <li><a href="103063?version=1&table=Table 390">1/SIG*D2SIG/DT1_PT/DT2_PT ( 0.0 GeV < T2_PT < 175.0 GeV)</a> (Table 390) <li><a href="103063?version=1&table=Table 391">1/SIG*D2SIG/DT1_PT/DT2_PT ( 175.0 GeV < T2_PT < 275.0 GeV)</a> (Table 391) <li><a href="103063?version=1&table=Table 392">1/SIG*D2SIG/DT1_PT/DT2_PT ( 275.0 GeV < T2_PT < 385.0 GeV)</a> (Table 392) <li><a href="103063?version=1&table=Table 393">1/SIG*D2SIG/DT1_PT/DT2_PT ( 385.0 GeV < T2_PT < 1000.0 GeV)</a> (Table 393) <li><a href="103063?version=1&table=Table 404">D2SIG/DT1_PT/DT2_PT ( 0.0 GeV < T2_PT < 175.0 GeV)</a> (Table 404) <li><a href="103063?version=1&table=Table 405">D2SIG/DT1_PT/DT2_PT ( 175.0 GeV < T2_PT < 275.0 GeV)</a> (Table 405) <li><a href="103063?version=1&table=Table 406">D2SIG/DT1_PT/DT2_PT ( 275.0 GeV < T2_PT < 385.0 GeV)</a> (Table 406) <li><a href="103063?version=1&table=Table 407">D2SIG/DT1_PT/DT2_PT ( 385.0 GeV < T2_PT < 1000.0 GeV)</a> (Table 407) <li><a href="103063?version=1&table=Table 418">1/SIG*D2SIG/DT1_PT/DTT_M ( 0.0 GeV < TT_M < 645.0 GeV)</a> (Table 418) <li><a href="103063?version=1&table=Table 419">1/SIG*D2SIG/DT1_PT/DTT_M ( 645.0 GeV < TT_M < 795.0 GeV)</a> (Table 419) <li><a href="103063?version=1&table=Table 420">1/SIG*D2SIG/DT1_PT/DTT_M ( 795.0 GeV < TT_M < 1080.0 GeV)</a> (Table 420) <li><a href="103063?version=1&table=Table 421">1/SIG*D2SIG/DT1_PT/DTT_M ( 1080.0 GeV < TT_M < 3000.0 GeV)</a> (Table 421) <li><a href="103063?version=1&table=Table 432">D2SIG/DT1_PT/DTT_M ( 0.0 GeV < TT_M < 645.0 GeV)</a> (Table 432) <li><a href="103063?version=1&table=Table 433">D2SIG/DT1_PT/DTT_M ( 645.0 GeV < TT_M < 795.0 GeV)</a> (Table 433) <li><a href="103063?version=1&table=Table 434">D2SIG/DT1_PT/DTT_M ( 795.0 GeV < TT_M < 1080.0 GeV)</a> (Table 434) <li><a href="103063?version=1&table=Table 435">D2SIG/DT1_PT/DTT_M ( 1080.0 GeV < TT_M < 3000.0 GeV)</a> (Table 435) </ul><br/> Covariances:<br/><ul> <li><a href="103063?version=1&table=Table 142">Matrix for 1/SIG*D2SIG/DT1_PT/DN_JETS between the 1th and 1th bins of N_JETS</a> (Table 142) <li><a href="103063?version=1&table=Table 143">Matrix for 1/SIG*D2SIG/DT1_PT/DN_JETS between the 2th and 1th bins of N_JETS</a> (Table 143) <li><a href="103063?version=1&table=Table 144">Matrix for 1/SIG*D2SIG/DT1_PT/DN_JETS between the 2th and 2th bins of N_JETS</a> (Table 144) <li><a href="103063?version=1&table=Table 145">Matrix for 1/SIG*D2SIG/DT1_PT/DN_JETS between the 3th and 1th bins of N_JETS</a> (Table 145) <li><a href="103063?version=1&table=Table 146">Matrix for 1/SIG*D2SIG/DT1_PT/DN_JETS between the 3th and 2th bins of N_JETS</a> (Table 146) <li><a href="103063?version=1&table=Table 147">Matrix for 1/SIG*D2SIG/DT1_PT/DN_JETS between the 3th and 3th bins of N_JETS</a> (Table 147) <li><a href="103063?version=1&table=Table 148">Matrix for 1/SIG*D2SIG/DT1_PT/DN_JETS between the 4th and 1th bins of N_JETS</a> (Table 148) <li><a href="103063?version=1&table=Table 149">Matrix for 1/SIG*D2SIG/DT1_PT/DN_JETS between the 4th and 2th bins of N_JETS</a> (Table 149) <li><a href="103063?version=1&table=Table 150">Matrix for 1/SIG*D2SIG/DT1_PT/DN_JETS between the 4th and 3th bins of N_JETS</a> (Table 150) <li><a href="103063?version=1&table=Table 151">Matrix for 1/SIG*D2SIG/DT1_PT/DN_JETS between the 4th and 4th bins of N_JETS</a> (Table 151) <li><a href="103063?version=1&table=Table 156">Matrix for D2SIG/DT1_PT/DN_JETS between the 1th and 1th bins of N_JETS</a> (Table 156) <li><a href="103063?version=1&table=Table 157">Matrix for D2SIG/DT1_PT/DN_JETS between the 2th and 1th bins of N_JETS</a> (Table 157) <li><a href="103063?version=1&table=Table 158">Matrix for D2SIG/DT1_PT/DN_JETS between the 2th and 2th bins of N_JETS</a> (Table 158) <li><a href="103063?version=1&table=Table 159">Matrix for D2SIG/DT1_PT/DN_JETS between the 3th and 1th bins of N_JETS</a> (Table 159) <li><a href="103063?version=1&table=Table 160">Matrix for D2SIG/DT1_PT/DN_JETS between the 3th and 2th bins of N_JETS</a> (Table 160) <li><a href="103063?version=1&table=Table 161">Matrix for D2SIG/DT1_PT/DN_JETS between the 3th and 3th bins of N_JETS</a> (Table 161) <li><a href="103063?version=1&table=Table 162">Matrix for D2SIG/DT1_PT/DN_JETS between the 4th and 1th bins of N_JETS</a> (Table 162) <li><a href="103063?version=1&table=Table 163">Matrix for D2SIG/DT1_PT/DN_JETS between the 4th and 2th bins of N_JETS</a> (Table 163) <li><a href="103063?version=1&table=Table 164">Matrix for D2SIG/DT1_PT/DN_JETS between the 4th and 3th bins of N_JETS</a> (Table 164) <li><a href="103063?version=1&table=Table 165">Matrix for D2SIG/DT1_PT/DN_JETS between the 4th and 4th bins of N_JETS</a> (Table 165) <li><a href="103063?version=1&table=Table 170">Matrix for 1/SIG*D2SIG/DT2_PT/DN_JETS between the 1th and 1th bins of N_JETS</a> (Table 170) <li><a href="103063?version=1&table=Table 171">Matrix for 1/SIG*D2SIG/DT2_PT/DN_JETS between the 2th and 1th bins of N_JETS</a> (Table 171) <li><a href="103063?version=1&table=Table 172">Matrix for 1/SIG*D2SIG/DT2_PT/DN_JETS between the 2th and 2th bins of N_JETS</a> (Table 172) <li><a href="103063?version=1&table=Table 173">Matrix for 1/SIG*D2SIG/DT2_PT/DN_JETS between the 3th and 1th bins of N_JETS</a> (Table 173) <li><a href="103063?version=1&table=Table 174">Matrix for 1/SIG*D2SIG/DT2_PT/DN_JETS between the 3th and 2th bins of N_JETS</a> (Table 174) <li><a href="103063?version=1&table=Table 175">Matrix for 1/SIG*D2SIG/DT2_PT/DN_JETS between the 3th and 3th bins of N_JETS</a> (Table 175) <li><a href="103063?version=1&table=Table 176">Matrix for 1/SIG*D2SIG/DT2_PT/DN_JETS between the 4th and 1th bins of N_JETS</a> (Table 176) <li><a href="103063?version=1&table=Table 177">Matrix for 1/SIG*D2SIG/DT2_PT/DN_JETS between the 4th and 2th bins of N_JETS</a> (Table 177) <li><a href="103063?version=1&table=Table 178">Matrix for 1/SIG*D2SIG/DT2_PT/DN_JETS between the 4th and 3th bins of N_JETS</a> (Table 178) <li><a href="103063?version=1&table=Table 179">Matrix for 1/SIG*D2SIG/DT2_PT/DN_JETS between the 4th and 4th bins of N_JETS</a> (Table 179) <li><a href="103063?version=1&table=Table 184">Matrix for D2SIG/DT2_PT/DN_JETS between the 1th and 1th bins of N_JETS</a> (Table 184) <li><a href="103063?version=1&table=Table 185">Matrix for D2SIG/DT2_PT/DN_JETS between the 2th and 1th bins of N_JETS</a> (Table 185) <li><a href="103063?version=1&table=Table 186">Matrix for D2SIG/DT2_PT/DN_JETS between the 2th and 2th bins of N_JETS</a> (Table 186) <li><a href="103063?version=1&table=Table 187">Matrix for D2SIG/DT2_PT/DN_JETS between the 3th and 1th bins of N_JETS</a> (Table 187) <li><a href="103063?version=1&table=Table 188">Matrix for D2SIG/DT2_PT/DN_JETS between the 3th and 2th bins of N_JETS</a> (Table 188) <li><a href="103063?version=1&table=Table 189">Matrix for D2SIG/DT2_PT/DN_JETS between the 3th and 3th bins of N_JETS</a> (Table 189) <li><a href="103063?version=1&table=Table 190">Matrix for D2SIG/DT2_PT/DN_JETS between the 4th and 1th bins of N_JETS</a> (Table 190) <li><a href="103063?version=1&table=Table 191">Matrix for D2SIG/DT2_PT/DN_JETS between the 4th and 2th bins of N_JETS</a> (Table 191) <li><a href="103063?version=1&table=Table 192">Matrix for D2SIG/DT2_PT/DN_JETS between the 4th and 3th bins of N_JETS</a> (Table 192) <li><a href="103063?version=1&table=Table 193">Matrix for D2SIG/DT2_PT/DN_JETS between the 4th and 4th bins of N_JETS</a> (Table 193) <li><a href="103063?version=1&table=Table 198">Matrix for 1/SIG*D2SIG/DTT_PT/DN_JETS between the 1th and 1th bins of N_JETS</a> (Table 198) <li><a href="103063?version=1&table=Table 199">Matrix for 1/SIG*D2SIG/DTT_PT/DN_JETS between the 2th and 1th bins of N_JETS</a> (Table 199) <li><a href="103063?version=1&table=Table 200">Matrix for 1/SIG*D2SIG/DTT_PT/DN_JETS between the 2th and 2th bins of N_JETS</a> (Table 200) <li><a href="103063?version=1&table=Table 201">Matrix for 1/SIG*D2SIG/DTT_PT/DN_JETS between the 3th and 1th bins of N_JETS</a> (Table 201) <li><a href="103063?version=1&table=Table 202">Matrix for 1/SIG*D2SIG/DTT_PT/DN_JETS between the 3th and 2th bins of N_JETS</a> (Table 202) <li><a href="103063?version=1&table=Table 203">Matrix for 1/SIG*D2SIG/DTT_PT/DN_JETS between the 3th and 3th bins of N_JETS</a> (Table 203) <li><a href="103063?version=1&table=Table 204">Matrix for 1/SIG*D2SIG/DTT_PT/DN_JETS between the 4th and 1th bins of N_JETS</a> (Table 204) <li><a href="103063?version=1&table=Table 205">Matrix for 1/SIG*D2SIG/DTT_PT/DN_JETS between the 4th and 2th bins of N_JETS</a> (Table 205) <li><a href="103063?version=1&table=Table 206">Matrix for 1/SIG*D2SIG/DTT_PT/DN_JETS between the 4th and 3th bins of N_JETS</a> (Table 206) <li><a href="103063?version=1&table=Table 207">Matrix for 1/SIG*D2SIG/DTT_PT/DN_JETS between the 4th and 4th bins of N_JETS</a> (Table 207) <li><a href="103063?version=1&table=Table 212">Matrix for D2SIG/DTT_PT/DN_JETS between the 1th and 1th bins of N_JETS</a> (Table 212) <li><a href="103063?version=1&table=Table 213">Matrix for D2SIG/DTT_PT/DN_JETS between the 2th and 1th bins of N_JETS</a> (Table 213) <li><a href="103063?version=1&table=Table 214">Matrix for D2SIG/DTT_PT/DN_JETS between the 2th and 2th bins of N_JETS</a> (Table 214) <li><a href="103063?version=1&table=Table 215">Matrix for D2SIG/DTT_PT/DN_JETS between the 3th and 1th bins of N_JETS</a> (Table 215) <li><a href="103063?version=1&table=Table 216">Matrix for D2SIG/DTT_PT/DN_JETS between the 3th and 2th bins of N_JETS</a> (Table 216) <li><a href="103063?version=1&table=Table 217">Matrix for D2SIG/DTT_PT/DN_JETS between the 3th and 3th bins of N_JETS</a> (Table 217) <li><a href="103063?version=1&table=Table 218">Matrix for D2SIG/DTT_PT/DN_JETS between the 4th and 1th bins of N_JETS</a> (Table 218) <li><a href="103063?version=1&table=Table 219">Matrix for D2SIG/DTT_PT/DN_JETS between the 4th and 2th bins of N_JETS</a> (Table 219) <li><a href="103063?version=1&table=Table 220">Matrix for D2SIG/DTT_PT/DN_JETS between the 4th and 3th bins of N_JETS</a> (Table 220) <li><a href="103063?version=1&table=Table 221">Matrix for D2SIG/DTT_PT/DN_JETS between the 4th and 4th bins of N_JETS</a> (Table 221) <li><a href="103063?version=1&table=Table 226">Matrix for 1/SIG*D2SIG/DABSPOUT/DN_JETS between the 1th and 1th bins of N_JETS</a> (Table 226) <li><a href="103063?version=1&table=Table 227">Matrix for 1/SIG*D2SIG/DABSPOUT/DN_JETS between the 2th and 1th bins of N_JETS</a> (Table 227) <li><a href="103063?version=1&table=Table 228">Matrix for 1/SIG*D2SIG/DABSPOUT/DN_JETS between the 2th and 2th bins of N_JETS</a> (Table 228) <li><a href="103063?version=1&table=Table 229">Matrix for 1/SIG*D2SIG/DABSPOUT/DN_JETS between the 3th and 1th bins of N_JETS</a> (Table 229) <li><a href="103063?version=1&table=Table 230">Matrix for 1/SIG*D2SIG/DABSPOUT/DN_JETS between the 3th and 2th bins of N_JETS</a> (Table 230) <li><a href="103063?version=1&table=Table 231">Matrix for 1/SIG*D2SIG/DABSPOUT/DN_JETS between the 3th and 3th bins of N_JETS</a> (Table 231) <li><a href="103063?version=1&table=Table 232">Matrix for 1/SIG*D2SIG/DABSPOUT/DN_JETS between the 4th and 1th bins of N_JETS</a> (Table 232) <li><a href="103063?version=1&table=Table 233">Matrix for 1/SIG*D2SIG/DABSPOUT/DN_JETS between the 4th and 2th bins of N_JETS</a> (Table 233) <li><a href="103063?version=1&table=Table 234">Matrix for 1/SIG*D2SIG/DABSPOUT/DN_JETS between the 4th and 3th bins of N_JETS</a> (Table 234) <li><a href="103063?version=1&table=Table 235">Matrix for 1/SIG*D2SIG/DABSPOUT/DN_JETS between the 4th and 4th bins of N_JETS</a> (Table 235) <li><a href="103063?version=1&table=Table 240">Matrix for D2SIG/DABSPOUT/DN_JETS between the 1th and 1th bins of N_JETS</a> (Table 240) <li><a href="103063?version=1&table=Table 241">Matrix for D2SIG/DABSPOUT/DN_JETS between the 2th and 1th bins of N_JETS</a> (Table 241) <li><a href="103063?version=1&table=Table 242">Matrix for D2SIG/DABSPOUT/DN_JETS between the 2th and 2th bins of N_JETS</a> (Table 242) <li><a href="103063?version=1&table=Table 243">Matrix for D2SIG/DABSPOUT/DN_JETS between the 3th and 1th bins of N_JETS</a> (Table 243) <li><a href="103063?version=1&table=Table 244">Matrix for D2SIG/DABSPOUT/DN_JETS between the 3th and 2th bins of N_JETS</a> (Table 244) <li><a href="103063?version=1&table=Table 245">Matrix for D2SIG/DABSPOUT/DN_JETS between the 3th and 3th bins of N_JETS</a> (Table 245) <li><a href="103063?version=1&table=Table 246">Matrix for D2SIG/DABSPOUT/DN_JETS between the 4th and 1th bins of N_JETS</a> (Table 246) <li><a href="103063?version=1&table=Table 247">Matrix for D2SIG/DABSPOUT/DN_JETS between the 4th and 2th bins of N_JETS</a> (Table 247) <li><a href="103063?version=1&table=Table 248">Matrix for D2SIG/DABSPOUT/DN_JETS between the 4th and 3th bins of N_JETS</a> (Table 248) <li><a href="103063?version=1&table=Table 249">Matrix for D2SIG/DABSPOUT/DN_JETS between the 4th and 4th bins of N_JETS</a> (Table 249) <li><a href="103063?version=1&table=Table 254">Matrix for 1/SIG*D2SIG/DDELTAPHI/DN_JETS between the 1th and 1th bins of N_JETS</a> (Table 254) <li><a href="103063?version=1&table=Table 255">Matrix for 1/SIG*D2SIG/DDELTAPHI/DN_JETS between the 2th and 1th bins of N_JETS</a> (Table 255) <li><a href="103063?version=1&table=Table 256">Matrix for 1/SIG*D2SIG/DDELTAPHI/DN_JETS between the 2th and 2th bins of N_JETS</a> (Table 256) <li><a href="103063?version=1&table=Table 257">Matrix for 1/SIG*D2SIG/DDELTAPHI/DN_JETS between the 3th and 1th bins of N_JETS</a> (Table 257) <li><a href="103063?version=1&table=Table 258">Matrix for 1/SIG*D2SIG/DDELTAPHI/DN_JETS between the 3th and 2th bins of N_JETS</a> (Table 258) <li><a href="103063?version=1&table=Table 259">Matrix for 1/SIG*D2SIG/DDELTAPHI/DN_JETS between the 3th and 3th bins of N_JETS</a> (Table 259) <li><a href="103063?version=1&table=Table 260">Matrix for 1/SIG*D2SIG/DDELTAPHI/DN_JETS between the 4th and 1th bins of N_JETS</a> (Table 260) <li><a href="103063?version=1&table=Table 261">Matrix for 1/SIG*D2SIG/DDELTAPHI/DN_JETS between the 4th and 2th bins of N_JETS</a> (Table 261) <li><a href="103063?version=1&table=Table 262">Matrix for 1/SIG*D2SIG/DDELTAPHI/DN_JETS between the 4th and 3th bins of N_JETS</a> (Table 262) <li><a href="103063?version=1&table=Table 263">Matrix for 1/SIG*D2SIG/DDELTAPHI/DN_JETS between the 4th and 4th bins of N_JETS</a> (Table 263) <li><a href="103063?version=1&table=Table 268">Matrix for D2SIG/DDELTAPHI/DN_JETS between the 1th and 1th bins of N_JETS</a> (Table 268) <li><a href="103063?version=1&table=Table 269">Matrix for D2SIG/DDELTAPHI/DN_JETS between the 2th and 1th bins of N_JETS</a> (Table 269) <li><a href="103063?version=1&table=Table 270">Matrix for D2SIG/DDELTAPHI/DN_JETS between the 2th and 2th bins of N_JETS</a> (Table 270) <li><a href="103063?version=1&table=Table 271">Matrix for D2SIG/DDELTAPHI/DN_JETS between the 3th and 1th bins of N_JETS</a> (Table 271) <li><a href="103063?version=1&table=Table 272">Matrix for D2SIG/DDELTAPHI/DN_JETS between the 3th and 2th bins of N_JETS</a> (Table 272) <li><a href="103063?version=1&table=Table 273">Matrix for D2SIG/DDELTAPHI/DN_JETS between the 3th and 3th bins of N_JETS</a> (Table 273) <li><a href="103063?version=1&table=Table 274">Matrix for D2SIG/DDELTAPHI/DN_JETS between the 4th and 1th bins of N_JETS</a> (Table 274) <li><a href="103063?version=1&table=Table 275">Matrix for D2SIG/DDELTAPHI/DN_JETS between the 4th and 2th bins of N_JETS</a> (Table 275) <li><a href="103063?version=1&table=Table 276">Matrix for D2SIG/DDELTAPHI/DN_JETS between the 4th and 3th bins of N_JETS</a> (Table 276) <li><a href="103063?version=1&table=Table 277">Matrix for D2SIG/DDELTAPHI/DN_JETS between the 4th and 4th bins of N_JETS</a> (Table 277) <li><a href="103063?version=1&table=Table 282">Matrix for 1/SIG*D2SIG/DABSPCROSS/DN_JETS between the 1th and 1th bins of N_JETS</a> (Table 282) <li><a href="103063?version=1&table=Table 283">Matrix for 1/SIG*D2SIG/DABSPCROSS/DN_JETS between the 2th and 1th bins of N_JETS</a> (Table 283) <li><a href="103063?version=1&table=Table 284">Matrix for 1/SIG*D2SIG/DABSPCROSS/DN_JETS between the 2th and 2th bins of N_JETS</a> (Table 284) <li><a href="103063?version=1&table=Table 285">Matrix for 1/SIG*D2SIG/DABSPCROSS/DN_JETS between the 3th and 1th bins of N_JETS</a> (Table 285) <li><a href="103063?version=1&table=Table 286">Matrix for 1/SIG*D2SIG/DABSPCROSS/DN_JETS between the 3th and 2th bins of N_JETS</a> (Table 286) <li><a href="103063?version=1&table=Table 287">Matrix for 1/SIG*D2SIG/DABSPCROSS/DN_JETS between the 3th and 3th bins of N_JETS</a> (Table 287) <li><a href="103063?version=1&table=Table 288">Matrix for 1/SIG*D2SIG/DABSPCROSS/DN_JETS between the 4th and 1th bins of N_JETS</a> (Table 288) <li><a href="103063?version=1&table=Table 289">Matrix for 1/SIG*D2SIG/DABSPCROSS/DN_JETS between the 4th and 2th bins of N_JETS</a> (Table 289) <li><a href="103063?version=1&table=Table 290">Matrix for 1/SIG*D2SIG/DABSPCROSS/DN_JETS between the 4th and 3th bins of N_JETS</a> (Table 290) <li><a href="103063?version=1&table=Table 291">Matrix for 1/SIG*D2SIG/DABSPCROSS/DN_JETS between the 4th and 4th bins of N_JETS</a> (Table 291) <li><a href="103063?version=1&table=Table 296">Matrix for D2SIG/DABSPCROSS/DN_JETS between the 1th and 1th bins of N_JETS</a> (Table 296) <li><a href="103063?version=1&table=Table 297">Matrix for D2SIG/DABSPCROSS/DN_JETS between the 2th and 1th bins of N_JETS</a> (Table 297) <li><a href="103063?version=1&table=Table 298">Matrix for D2SIG/DABSPCROSS/DN_JETS between the 2th and 2th bins of N_JETS</a> (Table 298) <li><a href="103063?version=1&table=Table 299">Matrix for D2SIG/DABSPCROSS/DN_JETS between the 3th and 1th bins of N_JETS</a> (Table 299) <li><a href="103063?version=1&table=Table 300">Matrix for D2SIG/DABSPCROSS/DN_JETS between the 3th and 2th bins of N_JETS</a> (Table 300) <li><a href="103063?version=1&table=Table 301">Matrix for D2SIG/DABSPCROSS/DN_JETS between the 3th and 3th bins of N_JETS</a> (Table 301) <li><a href="103063?version=1&table=Table 302">Matrix for D2SIG/DABSPCROSS/DN_JETS between the 4th and 1th bins of N_JETS</a> (Table 302) <li><a href="103063?version=1&table=Table 303">Matrix for D2SIG/DABSPCROSS/DN_JETS between the 4th and 2th bins of N_JETS</a> (Table 303) <li><a href="103063?version=1&table=Table 304">Matrix for D2SIG/DABSPCROSS/DN_JETS between the 4th and 3th bins of N_JETS</a> (Table 304) <li><a href="103063?version=1&table=Table 305">Matrix for D2SIG/DABSPCROSS/DN_JETS between the 4th and 4th bins of N_JETS</a> (Table 305) <li><a href="103063?version=1&table=Table 310">Matrix for 1/SIG*D2SIG/DT2_PT/DTT_M between the 1th and 1th bins of TT_M</a> (Table 310) <li><a href="103063?version=1&table=Table 311">Matrix for 1/SIG*D2SIG/DT2_PT/DTT_M between the 2th and 1th bins of TT_M</a> (Table 311) <li><a href="103063?version=1&table=Table 312">Matrix for 1/SIG*D2SIG/DT2_PT/DTT_M between the 2th and 2th bins of TT_M</a> (Table 312) <li><a href="103063?version=1&table=Table 313">Matrix for 1/SIG*D2SIG/DT2_PT/DTT_M between the 3th and 1th bins of TT_M</a> (Table 313) <li><a href="103063?version=1&table=Table 314">Matrix for 1/SIG*D2SIG/DT2_PT/DTT_M between the 3th and 2th bins of TT_M</a> (Table 314) <li><a href="103063?version=1&table=Table 315">Matrix for 1/SIG*D2SIG/DT2_PT/DTT_M between the 3th and 3th bins of TT_M</a> (Table 315) <li><a href="103063?version=1&table=Table 316">Matrix for 1/SIG*D2SIG/DT2_PT/DTT_M between the 4th and 1th bins of TT_M</a> (Table 316) <li><a href="103063?version=1&table=Table 317">Matrix for 1/SIG*D2SIG/DT2_PT/DTT_M between the 4th and 2th bins of TT_M</a> (Table 317) <li><a href="103063?version=1&table=Table 318">Matrix for 1/SIG*D2SIG/DT2_PT/DTT_M between the 4th and 3th bins of TT_M</a> (Table 318) <li><a href="103063?version=1&table=Table 319">Matrix for 1/SIG*D2SIG/DT2_PT/DTT_M between the 4th and 4th bins of TT_M</a> (Table 319) <li><a href="103063?version=1&table=Table 324">Matrix for D2SIG/DT2_PT/DTT_M between the 1th and 1th bins of TT_M</a> (Table 324) <li><a href="103063?version=1&table=Table 325">Matrix for D2SIG/DT2_PT/DTT_M between the 2th and 1th bins of TT_M</a> (Table 325) <li><a href="103063?version=1&table=Table 326">Matrix for D2SIG/DT2_PT/DTT_M between the 2th and 2th bins of TT_M</a> (Table 326) <li><a href="103063?version=1&table=Table 327">Matrix for D2SIG/DT2_PT/DTT_M between the 3th and 1th bins of TT_M</a> (Table 327) <li><a href="103063?version=1&table=Table 328">Matrix for D2SIG/DT2_PT/DTT_M between the 3th and 2th bins of TT_M</a> (Table 328) <li><a href="103063?version=1&table=Table 329">Matrix for D2SIG/DT2_PT/DTT_M between the 3th and 3th bins of TT_M</a> (Table 329) <li><a href="103063?version=1&table=Table 330">Matrix for D2SIG/DT2_PT/DTT_M between the 4th and 1th bins of TT_M</a> (Table 330) <li><a href="103063?version=1&table=Table 331">Matrix for D2SIG/DT2_PT/DTT_M between the 4th and 2th bins of TT_M</a> (Table 331) <li><a href="103063?version=1&table=Table 332">Matrix for D2SIG/DT2_PT/DTT_M between the 4th and 3th bins of TT_M</a> (Table 332) <li><a href="103063?version=1&table=Table 333">Matrix for D2SIG/DT2_PT/DTT_M between the 4th and 4th bins of TT_M</a> (Table 333) <li><a href="103063?version=1&table=Table 338">Matrix for 1/SIG*D2SIG/DTT_PT/DTT_M between the 1th and 1th bins of TT_M</a> (Table 338) <li><a href="103063?version=1&table=Table 339">Matrix for 1/SIG*D2SIG/DTT_PT/DTT_M between the 2th and 1th bins of TT_M</a> (Table 339) <li><a href="103063?version=1&table=Table 340">Matrix for 1/SIG*D2SIG/DTT_PT/DTT_M between the 2th and 2th bins of TT_M</a> (Table 340) <li><a href="103063?version=1&table=Table 341">Matrix for 1/SIG*D2SIG/DTT_PT/DTT_M between the 3th and 1th bins of TT_M</a> (Table 341) <li><a href="103063?version=1&table=Table 342">Matrix for 1/SIG*D2SIG/DTT_PT/DTT_M between the 3th and 2th bins of TT_M</a> (Table 342) <li><a href="103063?version=1&table=Table 343">Matrix for 1/SIG*D2SIG/DTT_PT/DTT_M between the 3th and 3th bins of TT_M</a> (Table 343) <li><a href="103063?version=1&table=Table 344">Matrix for 1/SIG*D2SIG/DTT_PT/DTT_M between the 4th and 1th bins of TT_M</a> (Table 344) <li><a href="103063?version=1&table=Table 345">Matrix for 1/SIG*D2SIG/DTT_PT/DTT_M between the 4th and 2th bins of TT_M</a> (Table 345) <li><a href="103063?version=1&table=Table 346">Matrix for 1/SIG*D2SIG/DTT_PT/DTT_M between the 4th and 3th bins of TT_M</a> (Table 346) <li><a href="103063?version=1&table=Table 347">Matrix for 1/SIG*D2SIG/DTT_PT/DTT_M between the 4th and 4th bins of TT_M</a> (Table 347) <li><a href="103063?version=1&table=Table 352">Matrix for D2SIG/DTT_PT/DTT_M between the 1th and 1th bins of TT_M</a> (Table 352) <li><a href="103063?version=1&table=Table 353">Matrix for D2SIG/DTT_PT/DTT_M between the 2th and 1th bins of TT_M</a> (Table 353) <li><a href="103063?version=1&table=Table 354">Matrix for D2SIG/DTT_PT/DTT_M between the 2th and 2th bins of TT_M</a> (Table 354) <li><a href="103063?version=1&table=Table 355">Matrix for D2SIG/DTT_PT/DTT_M between the 3th and 1th bins of TT_M</a> (Table 355) <li><a href="103063?version=1&table=Table 356">Matrix for D2SIG/DTT_PT/DTT_M between the 3th and 2th bins of TT_M</a> (Table 356) <li><a href="103063?version=1&table=Table 357">Matrix for D2SIG/DTT_PT/DTT_M between the 3th and 3th bins of TT_M</a> (Table 357) <li><a href="103063?version=1&table=Table 358">Matrix for D2SIG/DTT_PT/DTT_M between the 4th and 1th bins of TT_M</a> (Table 358) <li><a href="103063?version=1&table=Table 359">Matrix for D2SIG/DTT_PT/DTT_M between the 4th and 2th bins of TT_M</a> (Table 359) <li><a href="103063?version=1&table=Table 360">Matrix for D2SIG/DTT_PT/DTT_M between the 4th and 3th bins of TT_M</a> (Table 360) <li><a href="103063?version=1&table=Table 361">Matrix for D2SIG/DTT_PT/DTT_M between the 4th and 4th bins of TT_M</a> (Table 361) <li><a href="103063?version=1&table=Table 366">Matrix for 1/SIG*D2SIG/DABS_TT_Y/DTT_M between the 1th and 1th bins of TT_M</a> (Table 366) <li><a href="103063?version=1&table=Table 367">Matrix for 1/SIG*D2SIG/DABS_TT_Y/DTT_M between the 2th and 1th bins of TT_M</a> (Table 367) <li><a href="103063?version=1&table=Table 368">Matrix for 1/SIG*D2SIG/DABS_TT_Y/DTT_M between the 2th and 2th bins of TT_M</a> (Table 368) <li><a href="103063?version=1&table=Table 369">Matrix for 1/SIG*D2SIG/DABS_TT_Y/DTT_M between the 3th and 1th bins of TT_M</a> (Table 369) <li><a href="103063?version=1&table=Table 370">Matrix for 1/SIG*D2SIG/DABS_TT_Y/DTT_M between the 3th and 2th bins of TT_M</a> (Table 370) <li><a href="103063?version=1&table=Table 371">Matrix for 1/SIG*D2SIG/DABS_TT_Y/DTT_M between the 3th and 3th bins of TT_M</a> (Table 371) <li><a href="103063?version=1&table=Table 372">Matrix for 1/SIG*D2SIG/DABS_TT_Y/DTT_M between the 4th and 1th bins of TT_M</a> (Table 372) <li><a href="103063?version=1&table=Table 373">Matrix for 1/SIG*D2SIG/DABS_TT_Y/DTT_M between the 4th and 2th bins of TT_M</a> (Table 373) <li><a href="103063?version=1&table=Table 374">Matrix for 1/SIG*D2SIG/DABS_TT_Y/DTT_M between the 4th and 3th bins of TT_M</a> (Table 374) <li><a href="103063?version=1&table=Table 375">Matrix for 1/SIG*D2SIG/DABS_TT_Y/DTT_M between the 4th and 4th bins of TT_M</a> (Table 375) <li><a href="103063?version=1&table=Table 380">Matrix for D2SIG/DABS_TT_Y/DTT_M between the 1th and 1th bins of TT_M</a> (Table 380) <li><a href="103063?version=1&table=Table 381">Matrix for D2SIG/DABS_TT_Y/DTT_M between the 2th and 1th bins of TT_M</a> (Table 381) <li><a href="103063?version=1&table=Table 382">Matrix for D2SIG/DABS_TT_Y/DTT_M between the 2th and 2th bins of TT_M</a> (Table 382) <li><a href="103063?version=1&table=Table 383">Matrix for D2SIG/DABS_TT_Y/DTT_M between the 3th and 1th bins of TT_M</a> (Table 383) <li><a href="103063?version=1&table=Table 384">Matrix for D2SIG/DABS_TT_Y/DTT_M between the 3th and 2th bins of TT_M</a> (Table 384) <li><a href="103063?version=1&table=Table 385">Matrix for D2SIG/DABS_TT_Y/DTT_M between the 3th and 3th bins of TT_M</a> (Table 385) <li><a href="103063?version=1&table=Table 386">Matrix for D2SIG/DABS_TT_Y/DTT_M between the 4th and 1th bins of TT_M</a> (Table 386) <li><a href="103063?version=1&table=Table 387">Matrix for D2SIG/DABS_TT_Y/DTT_M between the 4th and 2th bins of TT_M</a> (Table 387) <li><a href="103063?version=1&table=Table 388">Matrix for D2SIG/DABS_TT_Y/DTT_M between the 4th and 3th bins of TT_M</a> (Table 388) <li><a href="103063?version=1&table=Table 389">Matrix for D2SIG/DABS_TT_Y/DTT_M between the 4th and 4th bins of TT_M</a> (Table 389) <li><a href="103063?version=1&table=Table 394">Matrix for 1/SIG*D2SIG/DT1_PT/DT2_PT between the 1th and 1th bins of T2_PT</a> (Table 394) <li><a href="103063?version=1&table=Table 395">Matrix for 1/SIG*D2SIG/DT1_PT/DT2_PT between the 2th and 1th bins of T2_PT</a> (Table 395) <li><a href="103063?version=1&table=Table 396">Matrix for 1/SIG*D2SIG/DT1_PT/DT2_PT between the 2th and 2th bins of T2_PT</a> (Table 396) <li><a href="103063?version=1&table=Table 397">Matrix for 1/SIG*D2SIG/DT1_PT/DT2_PT between the 3th and 1th bins of T2_PT</a> (Table 397) <li><a href="103063?version=1&table=Table 398">Matrix for 1/SIG*D2SIG/DT1_PT/DT2_PT between the 3th and 2th bins of T2_PT</a> (Table 398) <li><a href="103063?version=1&table=Table 399">Matrix for 1/SIG*D2SIG/DT1_PT/DT2_PT between the 3th and 3th bins of T2_PT</a> (Table 399) <li><a href="103063?version=1&table=Table 400">Matrix for 1/SIG*D2SIG/DT1_PT/DT2_PT between the 4th and 1th bins of T2_PT</a> (Table 400) <li><a href="103063?version=1&table=Table 401">Matrix for 1/SIG*D2SIG/DT1_PT/DT2_PT between the 4th and 2th bins of T2_PT</a> (Table 401) <li><a href="103063?version=1&table=Table 402">Matrix for 1/SIG*D2SIG/DT1_PT/DT2_PT between the 4th and 3th bins of T2_PT</a> (Table 402) <li><a href="103063?version=1&table=Table 403">Matrix for 1/SIG*D2SIG/DT1_PT/DT2_PT between the 4th and 4th bins of T2_PT</a> (Table 403) <li><a href="103063?version=1&table=Table 408">Matrix for D2SIG/DT1_PT/DT2_PT between the 1th and 1th bins of T2_PT</a> (Table 408) <li><a href="103063?version=1&table=Table 409">Matrix for D2SIG/DT1_PT/DT2_PT between the 2th and 1th bins of T2_PT</a> (Table 409) <li><a href="103063?version=1&table=Table 410">Matrix for D2SIG/DT1_PT/DT2_PT between the 2th and 2th bins of T2_PT</a> (Table 410) <li><a href="103063?version=1&table=Table 411">Matrix for D2SIG/DT1_PT/DT2_PT between the 3th and 1th bins of T2_PT</a> (Table 411) <li><a href="103063?version=1&table=Table 412">Matrix for D2SIG/DT1_PT/DT2_PT between the 3th and 2th bins of T2_PT</a> (Table 412) <li><a href="103063?version=1&table=Table 413">Matrix for D2SIG/DT1_PT/DT2_PT between the 3th and 3th bins of T2_PT</a> (Table 413) <li><a href="103063?version=1&table=Table 414">Matrix for D2SIG/DT1_PT/DT2_PT between the 4th and 1th bins of T2_PT</a> (Table 414) <li><a href="103063?version=1&table=Table 415">Matrix for D2SIG/DT1_PT/DT2_PT between the 4th and 2th bins of T2_PT</a> (Table 415) <li><a href="103063?version=1&table=Table 416">Matrix for D2SIG/DT1_PT/DT2_PT between the 4th and 3th bins of T2_PT</a> (Table 416) <li><a href="103063?version=1&table=Table 417">Matrix for D2SIG/DT1_PT/DT2_PT between the 4th and 4th bins of T2_PT</a> (Table 417) <li><a href="103063?version=1&table=Table 422">Matrix for 1/SIG*D2SIG/DT1_PT/DTT_M between the 1th and 1th bins of TT_M</a> (Table 422) <li><a href="103063?version=1&table=Table 423">Matrix for 1/SIG*D2SIG/DT1_PT/DTT_M between the 2th and 1th bins of TT_M</a> (Table 423) <li><a href="103063?version=1&table=Table 424">Matrix for 1/SIG*D2SIG/DT1_PT/DTT_M between the 2th and 2th bins of TT_M</a> (Table 424) <li><a href="103063?version=1&table=Table 425">Matrix for 1/SIG*D2SIG/DT1_PT/DTT_M between the 3th and 1th bins of TT_M</a> (Table 425) <li><a href="103063?version=1&table=Table 426">Matrix for 1/SIG*D2SIG/DT1_PT/DTT_M between the 3th and 2th bins of TT_M</a> (Table 426) <li><a href="103063?version=1&table=Table 427">Matrix for 1/SIG*D2SIG/DT1_PT/DTT_M between the 3th and 3th bins of TT_M</a> (Table 427) <li><a href="103063?version=1&table=Table 428">Matrix for 1/SIG*D2SIG/DT1_PT/DTT_M between the 4th and 1th bins of TT_M</a> (Table 428) <li><a href="103063?version=1&table=Table 429">Matrix for 1/SIG*D2SIG/DT1_PT/DTT_M between the 4th and 2th bins of TT_M</a> (Table 429) <li><a href="103063?version=1&table=Table 430">Matrix for 1/SIG*D2SIG/DT1_PT/DTT_M between the 4th and 3th bins of TT_M</a> (Table 430) <li><a href="103063?version=1&table=Table 431">Matrix for 1/SIG*D2SIG/DT1_PT/DTT_M between the 4th and 4th bins of TT_M</a> (Table 431) <li><a href="103063?version=1&table=Table 436">Matrix for D2SIG/DT1_PT/DTT_M between the 1th and 1th bins of TT_M</a> (Table 436) <li><a href="103063?version=1&table=Table 437">Matrix for D2SIG/DT1_PT/DTT_M between the 2th and 1th bins of TT_M</a> (Table 437) <li><a href="103063?version=1&table=Table 438">Matrix for D2SIG/DT1_PT/DTT_M between the 2th and 2th bins of TT_M</a> (Table 438) <li><a href="103063?version=1&table=Table 439">Matrix for D2SIG/DT1_PT/DTT_M between the 3th and 1th bins of TT_M</a> (Table 439) <li><a href="103063?version=1&table=Table 440">Matrix for D2SIG/DT1_PT/DTT_M between the 3th and 2th bins of TT_M</a> (Table 440) <li><a href="103063?version=1&table=Table 441">Matrix for D2SIG/DT1_PT/DTT_M between the 3th and 3th bins of TT_M</a> (Table 441) <li><a href="103063?version=1&table=Table 442">Matrix for D2SIG/DT1_PT/DTT_M between the 4th and 1th bins of TT_M</a> (Table 442) <li><a href="103063?version=1&table=Table 443">Matrix for D2SIG/DT1_PT/DTT_M between the 4th and 2th bins of TT_M</a> (Table 443) <li><a href="103063?version=1&table=Table 444">Matrix for D2SIG/DT1_PT/DTT_M between the 4th and 3th bins of TT_M</a> (Table 444) <li><a href="103063?version=1&table=Table 445">Matrix for D2SIG/DT1_PT/DTT_M between the 4th and 4th bins of TT_M</a> (Table 445) </ul><br/> <b>Parton level:</b><br/> <u>1D:</u><br/> Spectra:<br/> <ul><br/> <li><a href="103063?version=1&table=Table 446">1/SIG*DSIG/DCHI_TT</a> (Table 446) <li><a href="103063?version=1&table=Table 448">DSIG/DCHI_TT</a> (Table 448) <li><a href="103063?version=1&table=Table 450">1/SIG*DSIG/DTT_PT</a> (Table 450) <li><a href="103063?version=1&table=Table 452">DSIG/DTT_PT</a> (Table 452) <li><a href="103063?version=1&table=Table 454">1/SIG*DSIG/DDELTAPHI</a> (Table 454) <li><a href="103063?version=1&table=Table 456">DSIG/DDELTAPHI</a> (Table 456) <li><a href="103063?version=1&table=Table 458">1/SIG*DSIG/DT2_PT</a> (Table 458) <li><a href="103063?version=1&table=Table 460">DSIG/DT2_PT</a> (Table 460) <li><a href="103063?version=1&table=Table 462">1/SIG*DSIG/DTT_M</a> (Table 462) <li><a href="103063?version=1&table=Table 464">DSIG/DTT_M</a> (Table 464) <li><a href="103063?version=1&table=Table 466">1/SIG*DSIG/DABS_Y_BOOST</a> (Table 466) <li><a href="103063?version=1&table=Table 468">DSIG/DABS_Y_BOOST</a> (Table 468) <li><a href="103063?version=1&table=Table 470">1/SIG*DSIG/DT1_PT</a> (Table 470) <li><a href="103063?version=1&table=Table 472">DSIG/DT1_PT</a> (Table 472) <li><a href="103063?version=1&table=Table 474">1/SIG*DSIG/DABS_TT_Y</a> (Table 474) <li><a href="103063?version=1&table=Table 476">DSIG/DABS_TT_Y</a> (Table 476) <li><a href="103063?version=1&table=Table 478">1/SIG*DSIG/DABS_T2_Y</a> (Table 478) <li><a href="103063?version=1&table=Table 480">DSIG/DABS_T2_Y</a> (Table 480) <li><a href="103063?version=1&table=Table 482">1/SIG*DSIG/DHT_TT</a> (Table 482) <li><a href="103063?version=1&table=Table 484">DSIG/DHT_TT</a> (Table 484) <li><a href="103063?version=1&table=Table 486">1/SIG*DSIG/DABS_T1_Y</a> (Table 486) <li><a href="103063?version=1&table=Table 488">DSIG/DABS_T1_Y</a> (Table 488) </ul><br/> Covariances:<br/> <ul><br/> <li><a href="103063?version=1&table=Table 447">1/SIG*DSIG/DCHI_TT</a> (Table 447) <li><a href="103063?version=1&table=Table 449">DSIG/DCHI_TT</a> (Table 449) <li><a href="103063?version=1&table=Table 451">1/SIG*DSIG/DTT_PT</a> (Table 451) <li><a href="103063?version=1&table=Table 453">DSIG/DTT_PT</a> (Table 453) <li><a href="103063?version=1&table=Table 455">1/SIG*DSIG/DDELTAPHI</a> (Table 455) <li><a href="103063?version=1&table=Table 457">DSIG/DDELTAPHI</a> (Table 457) <li><a href="103063?version=1&table=Table 459">1/SIG*DSIG/DT2_PT</a> (Table 459) <li><a href="103063?version=1&table=Table 461">DSIG/DT2_PT</a> (Table 461) <li><a href="103063?version=1&table=Table 463">1/SIG*DSIG/DTT_M</a> (Table 463) <li><a href="103063?version=1&table=Table 465">DSIG/DTT_M</a> (Table 465) <li><a href="103063?version=1&table=Table 467">1/SIG*DSIG/DABS_Y_BOOST</a> (Table 467) <li><a href="103063?version=1&table=Table 469">DSIG/DABS_Y_BOOST</a> (Table 469) <li><a href="103063?version=1&table=Table 471">1/SIG*DSIG/DT1_PT</a> (Table 471) <li><a href="103063?version=1&table=Table 473">DSIG/DT1_PT</a> (Table 473) <li><a href="103063?version=1&table=Table 475">1/SIG*DSIG/DABS_TT_Y</a> (Table 475) <li><a href="103063?version=1&table=Table 477">DSIG/DABS_TT_Y</a> (Table 477) <li><a href="103063?version=1&table=Table 479">1/SIG*DSIG/DABS_T2_Y</a> (Table 479) <li><a href="103063?version=1&table=Table 481">DSIG/DABS_T2_Y</a> (Table 481) <li><a href="103063?version=1&table=Table 483">1/SIG*DSIG/DHT_TT</a> (Table 483) <li><a href="103063?version=1&table=Table 485">DSIG/DHT_TT</a> (Table 485) <li><a href="103063?version=1&table=Table 487">1/SIG*DSIG/DABS_T1_Y</a> (Table 487) <li><a href="103063?version=1&table=Table 489">DSIG/DABS_T1_Y</a> (Table 489) </ul><br/> <u>2D:</u><br/> Spectra:<br/> <ul><br/> <li><a href="103063?version=1&table=Table 490">1/SIG*D2SIG/DABS_TT_Y/DTT_M ( 0.0 GeV < TT_M < 700.0 GeV)</a> (Table 490) <li><a href="103063?version=1&table=Table 491">1/SIG*D2SIG/DABS_TT_Y/DTT_M ( 700.0 GeV < TT_M < 970.0 GeV)</a> (Table 491) <li><a href="103063?version=1&table=Table 492">1/SIG*D2SIG/DABS_TT_Y/DTT_M ( 970.0 GeV < TT_M < 3000.0 GeV)</a> (Table 492) <li><a href="103063?version=1&table=Table 499">D2SIG/DABS_TT_Y/DTT_M ( 0.0 GeV < TT_M < 700.0 GeV)</a> (Table 499) <li><a href="103063?version=1&table=Table 500">D2SIG/DABS_TT_Y/DTT_M ( 700.0 GeV < TT_M < 970.0 GeV)</a> (Table 500) <li><a href="103063?version=1&table=Table 501">D2SIG/DABS_TT_Y/DTT_M ( 970.0 GeV < TT_M < 3000.0 GeV)</a> (Table 501) <li><a href="103063?version=1&table=Table 508">1/SIG*D2SIG/DABS_T2_Y/DABS_T1_Y ( 0.0 < ABS_T1_Y < 0.5 )</a> (Table 508) <li><a href="103063?version=1&table=Table 509">1/SIG*D2SIG/DABS_T2_Y/DABS_T1_Y ( 0.5 < ABS_T1_Y < 1.0 )</a> (Table 509) <li><a href="103063?version=1&table=Table 510">1/SIG*D2SIG/DABS_T2_Y/DABS_T1_Y ( 1.0 < ABS_T1_Y < 1.5 )</a> (Table 510) <li><a href="103063?version=1&table=Table 511">1/SIG*D2SIG/DABS_T2_Y/DABS_T1_Y ( 1.5 < ABS_T1_Y < 2.5 )</a> (Table 511) <li><a href="103063?version=1&table=Table 522">D2SIG/DABS_T2_Y/DABS_T1_Y ( 0.0 < ABS_T1_Y < 0.5 )</a> (Table 522) <li><a href="103063?version=1&table=Table 523">D2SIG/DABS_T2_Y/DABS_T1_Y ( 0.5 < ABS_T1_Y < 1.0 )</a> (Table 523) <li><a href="103063?version=1&table=Table 524">D2SIG/DABS_T2_Y/DABS_T1_Y ( 1.0 < ABS_T1_Y < 1.5 )</a> (Table 524) <li><a href="103063?version=1&table=Table 525">D2SIG/DABS_T2_Y/DABS_T1_Y ( 1.5 < ABS_T1_Y < 2.5 )</a> (Table 525) <li><a href="103063?version=1&table=Table 536">1/SIG*D2SIG/DT2_PT/DM ( 0.0 GeV < M < 700.0 GeV)</a> (Table 536) <li><a href="103063?version=1&table=Table 537">1/SIG*D2SIG/DT2_PT/DM ( 700.0 GeV < M < 970.0 GeV)</a> (Table 537) <li><a href="103063?version=1&table=Table 538">1/SIG*D2SIG/DT2_PT/DM ( 970.0 GeV < M < 1315.0 GeV)</a> (Table 538) <li><a href="103063?version=1&table=Table 539">1/SIG*D2SIG/DT2_PT/DM ( 1315.0 GeV < M < 3000.0 GeV)</a> (Table 539) <li><a href="103063?version=1&table=Table 550">D2SIG/DT2_PT/DM ( 0.0 GeV < M < 700.0 GeV)</a> (Table 550) <li><a href="103063?version=1&table=Table 551">D2SIG/DT2_PT/DM ( 700.0 GeV < M < 970.0 GeV)</a> (Table 551) <li><a href="103063?version=1&table=Table 552">D2SIG/DT2_PT/DM ( 970.0 GeV < M < 1315.0 GeV)</a> (Table 552) <li><a href="103063?version=1&table=Table 553">D2SIG/DT2_PT/DM ( 1315.0 GeV < M < 3000.0 GeV)</a> (Table 553) <li><a href="103063?version=1&table=Table 564">1/SIG*D2SIG/DABS_T1_Y/DTT_M ( 0.0 GeV < TT_M < 700.0 GeV)</a> (Table 564) <li><a href="103063?version=1&table=Table 565">1/SIG*D2SIG/DABS_T1_Y/DTT_M ( 700.0 GeV < TT_M < 970.0 GeV)</a> (Table 565) <li><a href="103063?version=1&table=Table 566">1/SIG*D2SIG/DABS_T1_Y/DTT_M ( 970.0 GeV < TT_M < 3000.0 GeV)</a> (Table 566) <li><a href="103063?version=1&table=Table 573">D2SIG/DABS_T1_Y/DTT_M ( 0.0 GeV < TT_M < 700.0 GeV)</a> (Table 573) <li><a href="103063?version=1&table=Table 574">D2SIG/DABS_T1_Y/DTT_M ( 700.0 GeV < TT_M < 970.0 GeV)</a> (Table 574) <li><a href="103063?version=1&table=Table 575">D2SIG/DABS_T1_Y/DTT_M ( 970.0 GeV < TT_M < 3000.0 GeV)</a> (Table 575) <li><a href="103063?version=1&table=Table 582">1/SIG*D2SIG/DABS_T2_Y/DTT_M ( 0.0 GeV < TT_M < 700.0 GeV)</a> (Table 582) <li><a href="103063?version=1&table=Table 583">1/SIG*D2SIG/DABS_T2_Y/DTT_M ( 700.0 GeV < TT_M < 970.0 GeV)</a> (Table 583) <li><a href="103063?version=1&table=Table 584">1/SIG*D2SIG/DABS_T2_Y/DTT_M ( 970.0 GeV < TT_M < 3000.0 GeV)</a> (Table 584) <li><a href="103063?version=1&table=Table 591">D2SIG/DABS_T2_Y/DTT_M ( 0.0 GeV < TT_M < 700.0 GeV)</a> (Table 591) <li><a href="103063?version=1&table=Table 592">D2SIG/DABS_T2_Y/DTT_M ( 700.0 GeV < TT_M < 970.0 GeV)</a> (Table 592) <li><a href="103063?version=1&table=Table 593">D2SIG/DABS_T2_Y/DTT_M ( 970.0 GeV < TT_M < 3000.0 GeV)</a> (Table 593) <li><a href="103063?version=1&table=Table 600">1/SIG*D2SIG/DTT_PT/DTT_M ( 0.0 GeV < TT_M < 700.0 GeV)</a> (Table 600) <li><a href="103063?version=1&table=Table 601">1/SIG*D2SIG/DTT_PT/DTT_M ( 700.0 GeV < TT_M < 970.0 GeV)</a> (Table 601) <li><a href="103063?version=1&table=Table 602">1/SIG*D2SIG/DTT_PT/DTT_M ( 970.0 GeV < TT_M < 1315.0 GeV)</a> (Table 602) <li><a href="103063?version=1&table=Table 603">1/SIG*D2SIG/DTT_PT/DTT_M ( 1315.0 GeV < TT_M < 3000.0 GeV)</a> (Table 603) <li><a href="103063?version=1&table=Table 614">D2SIG/DTT_PT/DTT_M ( 0.0 GeV < TT_M < 700.0 GeV)</a> (Table 614) <li><a href="103063?version=1&table=Table 615">D2SIG/DTT_PT/DTT_M ( 700.0 GeV < TT_M < 970.0 GeV)</a> (Table 615) <li><a href="103063?version=1&table=Table 616">D2SIG/DTT_PT/DTT_M ( 970.0 GeV < TT_M < 1315.0 GeV)</a> (Table 616) <li><a href="103063?version=1&table=Table 617">D2SIG/DTT_PT/DTT_M ( 1315.0 GeV < TT_M < 3000.0 GeV)</a> (Table 617) <li><a href="103063?version=1&table=Table 628">1/SIG*D2SIG/DT1_PT/DTT_M ( 0.0 GeV < TT_M < 700.0 GeV)</a> (Table 628) <li><a href="103063?version=1&table=Table 629">1/SIG*D2SIG/DT1_PT/DTT_M ( 700.0 GeV < TT_M < 970.0 GeV)</a> (Table 629) <li><a href="103063?version=1&table=Table 630">1/SIG*D2SIG/DT1_PT/DTT_M ( 970.0 GeV < TT_M < 3000.0 GeV)</a> (Table 630) <li><a href="103063?version=1&table=Table 637">D2SIG/DT1_PT/DTT_M ( 0.0 GeV < TT_M < 700.0 GeV)</a> (Table 637) <li><a href="103063?version=1&table=Table 638">D2SIG/DT1_PT/DTT_M ( 700.0 GeV < TT_M < 970.0 GeV)</a> (Table 638) <li><a href="103063?version=1&table=Table 639">D2SIG/DT1_PT/DTT_M ( 970.0 GeV < TT_M < 3000.0 GeV)</a> (Table 639) <li><a href="103063?version=1&table=Table 646">1/SIG*D2SIG/DT1_PT/DT2_PT ( 0.0 GeV < T2_PT < 170.0 GeV)</a> (Table 646) <li><a href="103063?version=1&table=Table 647">1/SIG*D2SIG/DT1_PT/DT2_PT ( 170.0 GeV < T2_PT < 290.0 GeV)</a> (Table 647) <li><a href="103063?version=1&table=Table 648">1/SIG*D2SIG/DT1_PT/DT2_PT ( 290.0 GeV < T2_PT < 450.0 GeV)</a> (Table 648) <li><a href="103063?version=1&table=Table 649">1/SIG*D2SIG/DT1_PT/DT2_PT ( 450.0 GeV < T2_PT < 1000.0 GeV)</a> (Table 649) <li><a href="103063?version=1&table=Table 660">D2SIG/DT1_PT/DT2_PT ( 0.0 GeV < T2_PT < 170.0 GeV)</a> (Table 660) <li><a href="103063?version=1&table=Table 661">D2SIG/DT1_PT/DT2_PT ( 170.0 GeV < T2_PT < 290.0 GeV)</a> (Table 661) <li><a href="103063?version=1&table=Table 662">D2SIG/DT1_PT/DT2_PT ( 290.0 GeV < T2_PT < 450.0 GeV)</a> (Table 662) <li><a href="103063?version=1&table=Table 663">D2SIG/DT1_PT/DT2_PT ( 450.0 GeV < T2_PT < 1000.0 GeV)</a> (Table 663) </ul><br/> Covariances:<br/> <ul><br/> <li><a href="103063?version=1&table=Table 493">Matrix for 1/SIG*D2SIG/DABS_TT_Y/DTT_M between the 1th and 1th bins of TT_M</a> (Table 493) <li><a href="103063?version=1&table=Table 494">Matrix for 1/SIG*D2SIG/DABS_TT_Y/DTT_M between the 2th and 1th bins of TT_M</a> (Table 494) <li><a href="103063?version=1&table=Table 495">Matrix for 1/SIG*D2SIG/DABS_TT_Y/DTT_M between the 2th and 2th bins of TT_M</a> (Table 495) <li><a href="103063?version=1&table=Table 496">Matrix for 1/SIG*D2SIG/DABS_TT_Y/DTT_M between the 3th and 1th bins of TT_M</a> (Table 496) <li><a href="103063?version=1&table=Table 497">Matrix for 1/SIG*D2SIG/DABS_TT_Y/DTT_M between the 3th and 2th bins of TT_M</a> (Table 497) <li><a href="103063?version=1&table=Table 498">Matrix for 1/SIG*D2SIG/DABS_TT_Y/DTT_M between the 3th and 3th bins of TT_M</a> (Table 498) <li><a href="103063?version=1&table=Table 502">Matrix for D2SIG/DABS_TT_Y/DTT_M between the 1th and 1th bins of TT_M</a> (Table 502) <li><a href="103063?version=1&table=Table 503">Matrix for D2SIG/DABS_TT_Y/DTT_M between the 2th and 1th bins of TT_M</a> (Table 503) <li><a href="103063?version=1&table=Table 504">Matrix for D2SIG/DABS_TT_Y/DTT_M between the 2th and 2th bins of TT_M</a> (Table 504) <li><a href="103063?version=1&table=Table 505">Matrix for D2SIG/DABS_TT_Y/DTT_M between the 3th and 1th bins of TT_M</a> (Table 505) <li><a href="103063?version=1&table=Table 506">Matrix for D2SIG/DABS_TT_Y/DTT_M between the 3th and 2th bins of TT_M</a> (Table 506) <li><a href="103063?version=1&table=Table 507">Matrix for D2SIG/DABS_TT_Y/DTT_M between the 3th and 3th bins of TT_M</a> (Table 507) <li><a href="103063?version=1&table=Table 512">Matrix for 1/SIG*D2SIG/DABS_T2_Y/DABS_T1_Y between the 1th and 1th bins of ABS_T1_Y</a> (Table 512) <li><a href="103063?version=1&table=Table 513">Matrix for 1/SIG*D2SIG/DABS_T2_Y/DABS_T1_Y between the 2th and 1th bins of ABS_T1_Y</a> (Table 513) <li><a href="103063?version=1&table=Table 514">Matrix for 1/SIG*D2SIG/DABS_T2_Y/DABS_T1_Y between the 2th and 2th bins of ABS_T1_Y</a> (Table 514) <li><a href="103063?version=1&table=Table 515">Matrix for 1/SIG*D2SIG/DABS_T2_Y/DABS_T1_Y between the 3th and 1th bins of ABS_T1_Y</a> (Table 515) <li><a href="103063?version=1&table=Table 516">Matrix for 1/SIG*D2SIG/DABS_T2_Y/DABS_T1_Y between the 3th and 2th bins of ABS_T1_Y</a> (Table 516) <li><a href="103063?version=1&table=Table 517">Matrix for 1/SIG*D2SIG/DABS_T2_Y/DABS_T1_Y between the 3th and 3th bins of ABS_T1_Y</a> (Table 517) <li><a href="103063?version=1&table=Table 518">Matrix for 1/SIG*D2SIG/DABS_T2_Y/DABS_T1_Y between the 4th and 1th bins of ABS_T1_Y</a> (Table 518) <li><a href="103063?version=1&table=Table 519">Matrix for 1/SIG*D2SIG/DABS_T2_Y/DABS_T1_Y between the 4th and 2th bins of ABS_T1_Y</a> (Table 519) <li><a href="103063?version=1&table=Table 520">Matrix for 1/SIG*D2SIG/DABS_T2_Y/DABS_T1_Y between the 4th and 3th bins of ABS_T1_Y</a> (Table 520) <li><a href="103063?version=1&table=Table 521">Matrix for 1/SIG*D2SIG/DABS_T2_Y/DABS_T1_Y between the 4th and 4th bins of ABS_T1_Y</a> (Table 521) <li><a href="103063?version=1&table=Table 526">Matrix for D2SIG/DABS_T2_Y/DABS_T1_Y between the 1th and 1th bins of ABS_T1_Y</a> (Table 526) <li><a href="103063?version=1&table=Table 527">Matrix for D2SIG/DABS_T2_Y/DABS_T1_Y between the 2th and 1th bins of ABS_T1_Y</a> (Table 527) <li><a href="103063?version=1&table=Table 528">Matrix for D2SIG/DABS_T2_Y/DABS_T1_Y between the 2th and 2th bins of ABS_T1_Y</a> (Table 528) <li><a href="103063?version=1&table=Table 529">Matrix for D2SIG/DABS_T2_Y/DABS_T1_Y between the 3th and 1th bins of ABS_T1_Y</a> (Table 529) <li><a href="103063?version=1&table=Table 530">Matrix for D2SIG/DABS_T2_Y/DABS_T1_Y between the 3th and 2th bins of ABS_T1_Y</a> (Table 530) <li><a href="103063?version=1&table=Table 531">Matrix for D2SIG/DABS_T2_Y/DABS_T1_Y between the 3th and 3th bins of ABS_T1_Y</a> (Table 531) <li><a href="103063?version=1&table=Table 532">Matrix for D2SIG/DABS_T2_Y/DABS_T1_Y between the 4th and 1th bins of ABS_T1_Y</a> (Table 532) <li><a href="103063?version=1&table=Table 533">Matrix for D2SIG/DABS_T2_Y/DABS_T1_Y between the 4th and 2th bins of ABS_T1_Y</a> (Table 533) <li><a href="103063?version=1&table=Table 534">Matrix for D2SIG/DABS_T2_Y/DABS_T1_Y between the 4th and 3th bins of ABS_T1_Y</a> (Table 534) <li><a href="103063?version=1&table=Table 535">Matrix for D2SIG/DABS_T2_Y/DABS_T1_Y between the 4th and 4th bins of ABS_T1_Y</a> (Table 535) <li><a href="103063?version=1&table=Table 540">Matrix for 1/SIG*D2SIG/DT2_PT/DM between the 1th and 1th bins of M</a> (Table 540) <li><a href="103063?version=1&table=Table 541">Matrix for 1/SIG*D2SIG/DT2_PT/DM between the 2th and 1th bins of M</a> (Table 541) <li><a href="103063?version=1&table=Table 542">Matrix for 1/SIG*D2SIG/DT2_PT/DM between the 2th and 2th bins of M</a> (Table 542) <li><a href="103063?version=1&table=Table 543">Matrix for 1/SIG*D2SIG/DT2_PT/DM between the 3th and 1th bins of M</a> (Table 543) <li><a href="103063?version=1&table=Table 544">Matrix for 1/SIG*D2SIG/DT2_PT/DM between the 3th and 2th bins of M</a> (Table 544) <li><a href="103063?version=1&table=Table 545">Matrix for 1/SIG*D2SIG/DT2_PT/DM between the 3th and 3th bins of M</a> (Table 545) <li><a href="103063?version=1&table=Table 546">Matrix for 1/SIG*D2SIG/DT2_PT/DM between the 4th and 1th bins of M</a> (Table 546) <li><a href="103063?version=1&table=Table 547">Matrix for 1/SIG*D2SIG/DT2_PT/DM between the 4th and 2th bins of M</a> (Table 547) <li><a href="103063?version=1&table=Table 548">Matrix for 1/SIG*D2SIG/DT2_PT/DM between the 4th and 3th bins of M</a> (Table 548) <li><a href="103063?version=1&table=Table 549">Matrix for 1/SIG*D2SIG/DT2_PT/DM between the 4th and 4th bins of M</a> (Table 549) <li><a href="103063?version=1&table=Table 554">Matrix for D2SIG/DT2_PT/DM between the 1th and 1th bins of M</a> (Table 554) <li><a href="103063?version=1&table=Table 555">Matrix for D2SIG/DT2_PT/DM between the 2th and 1th bins of M</a> (Table 555) <li><a href="103063?version=1&table=Table 556">Matrix for D2SIG/DT2_PT/DM between the 2th and 2th bins of M</a> (Table 556) <li><a href="103063?version=1&table=Table 557">Matrix for D2SIG/DT2_PT/DM between the 3th and 1th bins of M</a> (Table 557) <li><a href="103063?version=1&table=Table 558">Matrix for D2SIG/DT2_PT/DM between the 3th and 2th bins of M</a> (Table 558) <li><a href="103063?version=1&table=Table 559">Matrix for D2SIG/DT2_PT/DM between the 3th and 3th bins of M</a> (Table 559) <li><a href="103063?version=1&table=Table 560">Matrix for D2SIG/DT2_PT/DM between the 4th and 1th bins of M</a> (Table 560) <li><a href="103063?version=1&table=Table 561">Matrix for D2SIG/DT2_PT/DM between the 4th and 2th bins of M</a> (Table 561) <li><a href="103063?version=1&table=Table 562">Matrix for D2SIG/DT2_PT/DM between the 4th and 3th bins of M</a> (Table 562) <li><a href="103063?version=1&table=Table 563">Matrix for D2SIG/DT2_PT/DM between the 4th and 4th bins of M</a> (Table 563) <li><a href="103063?version=1&table=Table 567">Matrix for 1/SIG*D2SIG/DABS_T1_Y/DTT_M between the 1th and 1th bins of TT_M</a> (Table 567) <li><a href="103063?version=1&table=Table 568">Matrix for 1/SIG*D2SIG/DABS_T1_Y/DTT_M between the 2th and 1th bins of TT_M</a> (Table 568) <li><a href="103063?version=1&table=Table 569">Matrix for 1/SIG*D2SIG/DABS_T1_Y/DTT_M between the 2th and 2th bins of TT_M</a> (Table 569) <li><a href="103063?version=1&table=Table 570">Matrix for 1/SIG*D2SIG/DABS_T1_Y/DTT_M between the 3th and 1th bins of TT_M</a> (Table 570) <li><a href="103063?version=1&table=Table 571">Matrix for 1/SIG*D2SIG/DABS_T1_Y/DTT_M between the 3th and 2th bins of TT_M</a> (Table 571) <li><a href="103063?version=1&table=Table 572">Matrix for 1/SIG*D2SIG/DABS_T1_Y/DTT_M between the 3th and 3th bins of TT_M</a> (Table 572) <li><a href="103063?version=1&table=Table 576">Matrix for D2SIG/DABS_T1_Y/DTT_M between the 1th and 1th bins of TT_M</a> (Table 576) <li><a href="103063?version=1&table=Table 577">Matrix for D2SIG/DABS_T1_Y/DTT_M between the 2th and 1th bins of TT_M</a> (Table 577) <li><a href="103063?version=1&table=Table 578">Matrix for D2SIG/DABS_T1_Y/DTT_M between the 2th and 2th bins of TT_M</a> (Table 578) <li><a href="103063?version=1&table=Table 579">Matrix for D2SIG/DABS_T1_Y/DTT_M between the 3th and 1th bins of TT_M</a> (Table 579) <li><a href="103063?version=1&table=Table 580">Matrix for D2SIG/DABS_T1_Y/DTT_M between the 3th and 2th bins of TT_M</a> (Table 580) <li><a href="103063?version=1&table=Table 581">Matrix for D2SIG/DABS_T1_Y/DTT_M between the 3th and 3th bins of TT_M</a> (Table 581) <li><a href="103063?version=1&table=Table 585">Matrix for 1/SIG*D2SIG/DABS_T2_Y/DTT_M between the 1th and 1th bins of TT_M</a> (Table 585) <li><a href="103063?version=1&table=Table 586">Matrix for 1/SIG*D2SIG/DABS_T2_Y/DTT_M between the 2th and 1th bins of TT_M</a> (Table 586) <li><a href="103063?version=1&table=Table 587">Matrix for 1/SIG*D2SIG/DABS_T2_Y/DTT_M between the 2th and 2th bins of TT_M</a> (Table 587) <li><a href="103063?version=1&table=Table 588">Matrix for 1/SIG*D2SIG/DABS_T2_Y/DTT_M between the 3th and 1th bins of TT_M</a> (Table 588) <li><a href="103063?version=1&table=Table 589">Matrix for 1/SIG*D2SIG/DABS_T2_Y/DTT_M between the 3th and 2th bins of TT_M</a> (Table 589) <li><a href="103063?version=1&table=Table 590">Matrix for 1/SIG*D2SIG/DABS_T2_Y/DTT_M between the 3th and 3th bins of TT_M</a> (Table 590) <li><a href="103063?version=1&table=Table 594">Matrix for D2SIG/DABS_T2_Y/DTT_M between the 1th and 1th bins of TT_M</a> (Table 594) <li><a href="103063?version=1&table=Table 595">Matrix for D2SIG/DABS_T2_Y/DTT_M between the 2th and 1th bins of TT_M</a> (Table 595) <li><a href="103063?version=1&table=Table 596">Matrix for D2SIG/DABS_T2_Y/DTT_M between the 2th and 2th bins of TT_M</a> (Table 596) <li><a href="103063?version=1&table=Table 597">Matrix for D2SIG/DABS_T2_Y/DTT_M between the 3th and 1th bins of TT_M</a> (Table 597) <li><a href="103063?version=1&table=Table 598">Matrix for D2SIG/DABS_T2_Y/DTT_M between the 3th and 2th bins of TT_M</a> (Table 598) <li><a href="103063?version=1&table=Table 599">Matrix for D2SIG/DABS_T2_Y/DTT_M between the 3th and 3th bins of TT_M</a> (Table 599) <li><a href="103063?version=1&table=Table 604">Matrix for 1/SIG*D2SIG/DTT_PT/DTT_M between the 1th and 1th bins of TT_M</a> (Table 604) <li><a href="103063?version=1&table=Table 605">Matrix for 1/SIG*D2SIG/DTT_PT/DTT_M between the 2th and 1th bins of TT_M</a> (Table 605) <li><a href="103063?version=1&table=Table 606">Matrix for 1/SIG*D2SIG/DTT_PT/DTT_M between the 2th and 2th bins of TT_M</a> (Table 606) <li><a href="103063?version=1&table=Table 607">Matrix for 1/SIG*D2SIG/DTT_PT/DTT_M between the 3th and 1th bins of TT_M</a> (Table 607) <li><a href="103063?version=1&table=Table 608">Matrix for 1/SIG*D2SIG/DTT_PT/DTT_M between the 3th and 2th bins of TT_M</a> (Table 608) <li><a href="103063?version=1&table=Table 609">Matrix for 1/SIG*D2SIG/DTT_PT/DTT_M between the 3th and 3th bins of TT_M</a> (Table 609) <li><a href="103063?version=1&table=Table 610">Matrix for 1/SIG*D2SIG/DTT_PT/DTT_M between the 4th and 1th bins of TT_M</a> (Table 610) <li><a href="103063?version=1&table=Table 611">Matrix for 1/SIG*D2SIG/DTT_PT/DTT_M between the 4th and 2th bins of TT_M</a> (Table 611) <li><a href="103063?version=1&table=Table 612">Matrix for 1/SIG*D2SIG/DTT_PT/DTT_M between the 4th and 3th bins of TT_M</a> (Table 612) <li><a href="103063?version=1&table=Table 613">Matrix for 1/SIG*D2SIG/DTT_PT/DTT_M between the 4th and 4th bins of TT_M</a> (Table 613) <li><a href="103063?version=1&table=Table 618">Matrix for D2SIG/DTT_PT/DTT_M between the 1th and 1th bins of TT_M</a> (Table 618) <li><a href="103063?version=1&table=Table 619">Matrix for D2SIG/DTT_PT/DTT_M between the 2th and 1th bins of TT_M</a> (Table 619) <li><a href="103063?version=1&table=Table 620">Matrix for D2SIG/DTT_PT/DTT_M between the 2th and 2th bins of TT_M</a> (Table 620) <li><a href="103063?version=1&table=Table 621">Matrix for D2SIG/DTT_PT/DTT_M between the 3th and 1th bins of TT_M</a> (Table 621) <li><a href="103063?version=1&table=Table 622">Matrix for D2SIG/DTT_PT/DTT_M between the 3th and 2th bins of TT_M</a> (Table 622) <li><a href="103063?version=1&table=Table 623">Matrix for D2SIG/DTT_PT/DTT_M between the 3th and 3th bins of TT_M</a> (Table 623) <li><a href="103063?version=1&table=Table 624">Matrix for D2SIG/DTT_PT/DTT_M between the 4th and 1th bins of TT_M</a> (Table 624) <li><a href="103063?version=1&table=Table 625">Matrix for D2SIG/DTT_PT/DTT_M between the 4th and 2th bins of TT_M</a> (Table 625) <li><a href="103063?version=1&table=Table 626">Matrix for D2SIG/DTT_PT/DTT_M between the 4th and 3th bins of TT_M</a> (Table 626) <li><a href="103063?version=1&table=Table 627">Matrix for D2SIG/DTT_PT/DTT_M between the 4th and 4th bins of TT_M</a> (Table 627) <li><a href="103063?version=1&table=Table 631">Matrix for 1/SIG*D2SIG/DT1_PT/DTT_M between the 1th and 1th bins of TT_M</a> (Table 631) <li><a href="103063?version=1&table=Table 632">Matrix for 1/SIG*D2SIG/DT1_PT/DTT_M between the 2th and 1th bins of TT_M</a> (Table 632) <li><a href="103063?version=1&table=Table 633">Matrix for 1/SIG*D2SIG/DT1_PT/DTT_M between the 2th and 2th bins of TT_M</a> (Table 633) <li><a href="103063?version=1&table=Table 634">Matrix for 1/SIG*D2SIG/DT1_PT/DTT_M between the 3th and 1th bins of TT_M</a> (Table 634) <li><a href="103063?version=1&table=Table 635">Matrix for 1/SIG*D2SIG/DT1_PT/DTT_M between the 3th and 2th bins of TT_M</a> (Table 635) <li><a href="103063?version=1&table=Table 636">Matrix for 1/SIG*D2SIG/DT1_PT/DTT_M between the 3th and 3th bins of TT_M</a> (Table 636) <li><a href="103063?version=1&table=Table 640">Matrix for D2SIG/DT1_PT/DTT_M between the 1th and 1th bins of TT_M</a> (Table 640) <li><a href="103063?version=1&table=Table 641">Matrix for D2SIG/DT1_PT/DTT_M between the 2th and 1th bins of TT_M</a> (Table 641) <li><a href="103063?version=1&table=Table 642">Matrix for D2SIG/DT1_PT/DTT_M between the 2th and 2th bins of TT_M</a> (Table 642) <li><a href="103063?version=1&table=Table 643">Matrix for D2SIG/DT1_PT/DTT_M between the 3th and 1th bins of TT_M</a> (Table 643) <li><a href="103063?version=1&table=Table 644">Matrix for D2SIG/DT1_PT/DTT_M between the 3th and 2th bins of TT_M</a> (Table 644) <li><a href="103063?version=1&table=Table 645">Matrix for D2SIG/DT1_PT/DTT_M between the 3th and 3th bins of TT_M</a> (Table 645) <li><a href="103063?version=1&table=Table 650">Matrix for 1/SIG*D2SIG/DT1_PT/DT2_PT between the 1th and 1th bins of T2_PT</a> (Table 650) <li><a href="103063?version=1&table=Table 651">Matrix for 1/SIG*D2SIG/DT1_PT/DT2_PT between the 2th and 1th bins of T2_PT</a> (Table 651) <li><a href="103063?version=1&table=Table 652">Matrix for 1/SIG*D2SIG/DT1_PT/DT2_PT between the 2th and 2th bins of T2_PT</a> (Table 652) <li><a href="103063?version=1&table=Table 653">Matrix for 1/SIG*D2SIG/DT1_PT/DT2_PT between the 3th and 1th bins of T2_PT</a> (Table 653) <li><a href="103063?version=1&table=Table 654">Matrix for 1/SIG*D2SIG/DT1_PT/DT2_PT between the 3th and 2th bins of T2_PT</a> (Table 654) <li><a href="103063?version=1&table=Table 655">Matrix for 1/SIG*D2SIG/DT1_PT/DT2_PT between the 3th and 3th bins of T2_PT</a> (Table 655) <li><a href="103063?version=1&table=Table 656">Matrix for 1/SIG*D2SIG/DT1_PT/DT2_PT between the 4th and 1th bins of T2_PT</a> (Table 656) <li><a href="103063?version=1&table=Table 657">Matrix for 1/SIG*D2SIG/DT1_PT/DT2_PT between the 4th and 2th bins of T2_PT</a> (Table 657) <li><a href="103063?version=1&table=Table 658">Matrix for 1/SIG*D2SIG/DT1_PT/DT2_PT between the 4th and 3th bins of T2_PT</a> (Table 658) <li><a href="103063?version=1&table=Table 659">Matrix for 1/SIG*D2SIG/DT1_PT/DT2_PT between the 4th and 4th bins of T2_PT</a> (Table 659) <li><a href="103063?version=1&table=Table 664">Matrix for D2SIG/DT1_PT/DT2_PT between the 1th and 1th bins of T2_PT</a> (Table 664) <li><a href="103063?version=1&table=Table 665">Matrix for D2SIG/DT1_PT/DT2_PT between the 2th and 1th bins of T2_PT</a> (Table 665) <li><a href="103063?version=1&table=Table 666">Matrix for D2SIG/DT1_PT/DT2_PT between the 2th and 2th bins of T2_PT</a> (Table 666) <li><a href="103063?version=1&table=Table 667">Matrix for D2SIG/DT1_PT/DT2_PT between the 3th and 1th bins of T2_PT</a> (Table 667) <li><a href="103063?version=1&table=Table 668">Matrix for D2SIG/DT1_PT/DT2_PT between the 3th and 2th bins of T2_PT</a> (Table 668) <li><a href="103063?version=1&table=Table 669">Matrix for D2SIG/DT1_PT/DT2_PT between the 3th and 3th bins of T2_PT</a> (Table 669) <li><a href="103063?version=1&table=Table 670">Matrix for D2SIG/DT1_PT/DT2_PT between the 4th and 1th bins of T2_PT</a> (Table 670) <li><a href="103063?version=1&table=Table 671">Matrix for D2SIG/DT1_PT/DT2_PT between the 4th and 2th bins of T2_PT</a> (Table 671) <li><a href="103063?version=1&table=Table 672">Matrix for D2SIG/DT1_PT/DT2_PT between the 4th and 3th bins of T2_PT</a> (Table 672) <li><a href="103063?version=1&table=Table 673">Matrix for D2SIG/DT1_PT/DT2_PT between the 4th and 4th bins of T2_PT</a> (Table 673) </ul><br/>
Relative differential cross-section as a function of $\Delta R^{extra1}_{jet1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $\Delta R^{extra1}_{jet1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $\Delta R^{extra1}_{jet1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $\Delta R^{extra1}_{jet1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $|y^{t,1}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $|y^{t,1}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $|y^{t,1}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t,1}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $|y^{t,2}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $|y^{t,2}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $|y^{t,2}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t,2}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $|y^{t\bar{t}}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $|y^{t\bar{t}}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $|y^{t\bar{t}}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $p_{T}^{t,1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $p_{T}^{t,1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $p_{T}^{t,1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $p_{T}^{t,2}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $p_{T}^{t,2}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $p_{T}^{t,2}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,2}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $p_{T}^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $p_{T}^{t\bar{t}}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $p_{T}^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $N_{jets}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $N_{jets}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $N_{jets}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $N_{jets}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $\Delta\phi^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $\Delta\phi^{t\bar{t}}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $\Delta\phi^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $\Delta\phi^{t\bar{t}}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $|P_{out}^{t,1}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $|P_{out}^{t,1}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $|P_{out}^{t,1}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|P_{out}^{t,1}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $|P_{cross}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $|P_{cross}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $|P_{cross}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|P_{cross}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $Z^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $Z^{t\bar{t}}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $Z^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $Z^{t\bar{t}}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $H_{T}^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $H_{T}^{t\bar{t}}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $H_{T}^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $|y_{boost}^{t\bar{t}}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $|y_{boost}^{t\bar{t}}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $|y_{boost}^{t\bar{t}}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y_{boost}^{t\bar{t}}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $\chi^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $\chi^{t\bar{t}}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $\chi^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $\chi^{t\bar{t}}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $R_{Wt}^{leading}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $R_{Wt}^{leading}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $R_{Wt}^{leading}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $R_{Wt}^{leading}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $R_{Wt}^{subleading}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $R_{Wt}^{subleading}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $R_{Wt}^{subleading}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $R_{Wt}^{subleading}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $R_{Wb}^{leading}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $R_{Wb}^{leading}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $R_{Wb}^{leading}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $R_{Wb}^{leading}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $R_{Wb}^{subleading}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $R_{Wb}^{subleading}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $R_{Wb}^{subleading}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $R_{Wb}^{subleading}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $\Delta R^{extra1}_{t,close}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $\Delta R^{extra1}_{t,close}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $\Delta R^{extra1}_{t,close}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $\Delta R^{extra1}_{t,close}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $\Delta R^{extra2}_{t,close}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $\Delta R^{extra2}_{t,close}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $\Delta R^{extra2}_{t,close}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $\Delta R^{extra2}_{t,close}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $\Delta R^{extra3}_{t,close}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $\Delta R^{extra3}_{t,close}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $\Delta R^{extra3}_{t,close}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $\Delta R^{extra3}_{t,close}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $R^{pT, extra1}_{t,1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $R^{pT, extra1}_{t,1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $R^{pT, extra1}_{t,1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $R^{pT, extra1}_{t,1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $R^{pT, extra2}_{t,1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $R^{pT, extra2}_{t,1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $R^{pT, extra2}_{t,1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $R^{pT, extra2}_{t,1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $R^{pT, extra3}_{t,1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $R^{pT, extra3}_{t,1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $R^{pT, extra3}_{t,1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $R^{pT, extra3}_{t,1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $R^{pT, t\bar{t}}_{extra1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $R^{pT, t\bar{t}}_{extra1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $R^{pT, t\bar{t}}_{extra1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $R^{pT, t\bar{t}}_{extra1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $R^{pT, extra1}_{jet1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $R^{pT, extra1}_{jet1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $R^{pT, extra1}_{jet1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $R^{pT, extra1}_{jet1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $R^{pT, extra2}_{jet1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $R^{pT, extra2}_{jet1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $R^{pT, extra2}_{jet1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $R^{pT, extra2}_{jet1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $R^{pT, extra3}_{jet1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $R^{pT, extra3}_{jet1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $R^{pT, extra3}_{jet1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $R^{pT, extra3}_{jet1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $\Delta R^{extra2}_{extra1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $\Delta R^{extra2}_{extra1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $\Delta R^{extra2}_{extra1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $\Delta R^{extra2}_{extra1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $\Delta R^{extra3}_{extra1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $\Delta R^{extra3}_{extra1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $\Delta R^{extra3}_{extra1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $\Delta R^{extra3}_{extra1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $R^{pT, extra2}_{extra1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $R^{pT, extra2}_{extra1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $R^{pT, extra2}_{extra1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $R^{pT, extra2}_{extra1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $R^{pT, extra3}_{extra1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $R^{pT, extra3}_{extra1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $R^{pT, extra3}_{extra1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $R^{pT, extra3}_{extra1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Total cross-section at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Relative double-differential cross-section as a function of $p_{T}^{t,1}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 6. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 7. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ > 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 6 and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ > 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute double-differential cross-section as a function of $p_{T}^{t,1}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 6. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 7. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ > 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 6 and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $N_{jets}$ in $N_{jets}$ > 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative double-differential cross-section as a function of $p_{T}^{t,2}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 6. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,2}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 7. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,2}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,2}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ > 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 6 and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ > 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute double-differential cross-section as a function of $p_{T}^{t,2}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 6. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,2}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 7. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,2}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,2}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ > 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 6 and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $N_{jets}$ in $N_{jets}$ > 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative double-differential cross-section as a function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 6. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 7. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ > 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute double-differential cross-section as a function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 6. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 7. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ > 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative double-differential cross-section as a function of $|P_{out}^{t,1}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 6. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|P_{out}^{t,1}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 7. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|P_{out}^{t,1}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|P_{out}^{t,1}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ > 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix between the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 6 and the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 7 and the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 7 and the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ > 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute double-differential cross-section as a function of $|P_{out}^{t,1}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 6. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|P_{out}^{t,1}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 7. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|P_{out}^{t,1}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|P_{out}^{t,1}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ > 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 6 and the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 7 and the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 7 and the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $|P_{out}^{t,1}|$ vs $N_{jets}$ in $N_{jets}$ > 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative double-differential cross-section as a function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 6. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 7. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ > 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix between the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 and the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute double-differential cross-section as a function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 6. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 7. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ > 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 and the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 and the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $\Delta\phi^{t\bar{t}}$ vs $N_{jets}$ in $N_{jets}$ > 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative double-differential cross-section as a function of $|P_{cross}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 6. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|P_{cross}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 7. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|P_{cross}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|P_{cross}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ > 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix between the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 6 and the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 7 and the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 7 and the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 8 and the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the relative double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ > 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute double-differential cross-section as a function of $|P_{cross}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 6. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|P_{cross}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 7. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|P_{cross}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ = 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|P_{cross}|$ vs $N_{jets}$ at particle level in the all hadronic resolved topology in $N_{jets}$ > 8. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 6 and the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 7 and the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 7 and the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 8 and the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 6 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 7 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ = 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ > 8 and the absolute double-differential cross-section as function of $|P_{cross}|$ vs $N_{jets}$ in $N_{jets}$ > 8 at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative double-differential cross-section as a function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute double-differential cross-section as a function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative double-differential cross-section as a function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute double-differential cross-section as a function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative double-differential cross-section as a function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV and the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV and the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV and the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV and the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV and the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV and the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute double-differential cross-section as a function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV and the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV and the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV and the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV and the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV and the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV and the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 620.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 620.0 GeV < $m^{t\bar{t}}$ < 835.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 835.0 GeV < $m^{t\bar{t}}$ < 1050.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 1050.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative double-differential cross-section as a function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ at particle level in the all hadronic resolved topology in 0.0 GeV < $p_{T}^{t,2}$ < 175.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ at particle level in the all hadronic resolved topology in 175.0 GeV < $p_{T}^{t,2}$ < 275.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ at particle level in the all hadronic resolved topology in 275.0 GeV < $p_{T}^{t,2}$ < 385.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ at particle level in the all hadronic resolved topology in 385.0 GeV < $p_{T}^{t,2}$ < 1000.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 0.0 GeV < $p_{T}^{t,2}$ < 175.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 0.0 GeV < $p_{T}^{t,2}$ < 175.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 175.0 GeV < $p_{T}^{t,2}$ < 275.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 0.0 GeV < $p_{T}^{t,2}$ < 175.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 175.0 GeV < $p_{T}^{t,2}$ < 275.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 175.0 GeV < $p_{T}^{t,2}$ < 275.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 275.0 GeV < $p_{T}^{t,2}$ < 385.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 0.0 GeV < $p_{T}^{t,2}$ < 175.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 275.0 GeV < $p_{T}^{t,2}$ < 385.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 175.0 GeV < $p_{T}^{t,2}$ < 275.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 275.0 GeV < $p_{T}^{t,2}$ < 385.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 275.0 GeV < $p_{T}^{t,2}$ < 385.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 385.0 GeV < $p_{T}^{t,2}$ < 1000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 0.0 GeV < $p_{T}^{t,2}$ < 175.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 385.0 GeV < $p_{T}^{t,2}$ < 1000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 175.0 GeV < $p_{T}^{t,2}$ < 275.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 385.0 GeV < $p_{T}^{t,2}$ < 1000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 275.0 GeV < $p_{T}^{t,2}$ < 385.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 385.0 GeV < $p_{T}^{t,2}$ < 1000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 385.0 GeV < $p_{T}^{t,2}$ < 1000.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute double-differential cross-section as a function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ at particle level in the all hadronic resolved topology in 0.0 GeV < $p_{T}^{t,2}$ < 175.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ at particle level in the all hadronic resolved topology in 175.0 GeV < $p_{T}^{t,2}$ < 275.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ at particle level in the all hadronic resolved topology in 275.0 GeV < $p_{T}^{t,2}$ < 385.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ at particle level in the all hadronic resolved topology in 385.0 GeV < $p_{T}^{t,2}$ < 1000.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 0.0 GeV < $p_{T}^{t,2}$ < 175.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 0.0 GeV < $p_{T}^{t,2}$ < 175.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 175.0 GeV < $p_{T}^{t,2}$ < 275.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 0.0 GeV < $p_{T}^{t,2}$ < 175.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 175.0 GeV < $p_{T}^{t,2}$ < 275.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 175.0 GeV < $p_{T}^{t,2}$ < 275.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 275.0 GeV < $p_{T}^{t,2}$ < 385.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 0.0 GeV < $p_{T}^{t,2}$ < 175.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 275.0 GeV < $p_{T}^{t,2}$ < 385.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 175.0 GeV < $p_{T}^{t,2}$ < 275.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 275.0 GeV < $p_{T}^{t,2}$ < 385.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 275.0 GeV < $p_{T}^{t,2}$ < 385.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 385.0 GeV < $p_{T}^{t,2}$ < 1000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 0.0 GeV < $p_{T}^{t,2}$ < 175.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 385.0 GeV < $p_{T}^{t,2}$ < 1000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 175.0 GeV < $p_{T}^{t,2}$ < 275.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 385.0 GeV < $p_{T}^{t,2}$ < 1000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 275.0 GeV < $p_{T}^{t,2}$ < 385.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 385.0 GeV < $p_{T}^{t,2}$ < 1000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 385.0 GeV < $p_{T}^{t,2}$ < 1000.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative double-differential cross-section as a function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 0.0 GeV < $m^{t\bar{t}}$ < 645.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 645.0 GeV < $m^{t\bar{t}}$ < 795.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 795.0 GeV < $m^{t\bar{t}}$ < 1080.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 1080.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 645.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 645.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 645.0 GeV < $m^{t\bar{t}}$ < 795.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 645.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 645.0 GeV < $m^{t\bar{t}}$ < 795.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 645.0 GeV < $m^{t\bar{t}}$ < 795.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 795.0 GeV < $m^{t\bar{t}}$ < 1080.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 645.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 795.0 GeV < $m^{t\bar{t}}$ < 1080.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 645.0 GeV < $m^{t\bar{t}}$ < 795.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 795.0 GeV < $m^{t\bar{t}}$ < 1080.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 795.0 GeV < $m^{t\bar{t}}$ < 1080.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 1080.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 645.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 1080.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 645.0 GeV < $m^{t\bar{t}}$ < 795.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 1080.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 795.0 GeV < $m^{t\bar{t}}$ < 1080.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 1080.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 1080.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute double-differential cross-section as a function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 0.0 GeV < $m^{t\bar{t}}$ < 645.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 645.0 GeV < $m^{t\bar{t}}$ < 795.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 795.0 GeV < $m^{t\bar{t}}$ < 1080.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology in 1080.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 645.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 645.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 645.0 GeV < $m^{t\bar{t}}$ < 795.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 645.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 645.0 GeV < $m^{t\bar{t}}$ < 795.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 645.0 GeV < $m^{t\bar{t}}$ < 795.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 795.0 GeV < $m^{t\bar{t}}$ < 1080.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 645.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 795.0 GeV < $m^{t\bar{t}}$ < 1080.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 645.0 GeV < $m^{t\bar{t}}$ < 795.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 795.0 GeV < $m^{t\bar{t}}$ < 1080.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 795.0 GeV < $m^{t\bar{t}}$ < 1080.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 1080.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 645.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 1080.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 645.0 GeV < $m^{t\bar{t}}$ < 795.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 1080.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 795.0 GeV < $m^{t\bar{t}}$ < 1080.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 1080.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 1080.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $\chi^{t\bar{t}}$ at parton level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $\chi^{t\bar{t}}$ at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $\chi^{t\bar{t}}$ at parton level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $\chi^{t\bar{t}}$ at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $p_{T}^{t\bar{t}}$ at parton level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $p_{T}^{t\bar{t}}$ at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $p_{T}^{t\bar{t}}$ at parton level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $\Delta\phi^{t\bar{t}}$ at parton level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $\Delta\phi^{t\bar{t}}$ at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $\Delta\phi^{t\bar{t}}$ at parton level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $\Delta\phi^{t\bar{t}}$ at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $p_{T}^{t,2}$ at parton level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $p_{T}^{t,2}$ at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $p_{T}^{t,2}$ at parton level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,2}$ at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $|y_{boost}^{t\bar{t}}|$ at parton level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $|y_{boost}^{t\bar{t}}|$ at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $|y_{boost}^{t\bar{t}}|$ at parton level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y_{boost}^{t\bar{t}}|$ at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $p_{T}^{t,1}$ at parton level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $p_{T}^{t,1}$ at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $p_{T}^{t,1}$ at parton level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $|y^{t\bar{t}}|$ at parton level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $|y^{t\bar{t}}|$ at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $|y^{t\bar{t}}|$ at parton level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $|y^{t,2}|$ at parton level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $|y^{t,2}|$ at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $|y^{t,2}|$ at parton level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t,2}|$ at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $H_{T}^{t\bar{t}}$ at parton level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $H_{T}^{t\bar{t}}$ at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $H_{T}^{t\bar{t}}$ at parton level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative differential cross-section as a function of $|y^{t,1}|$ at parton level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix of the relative differential cross-section as function of $|y^{t,1}|$ at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute differential cross-section as a function of $|y^{t,1}|$ at parton level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t,1}|$ at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative double-differential cross-section as a function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV and the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV and the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV and the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute double-differential cross-section as a function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV and the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV and the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV and the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $|y^{t\bar{t}}|$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative double-differential cross-section as a function of $|y^{t,2}|$ vs $|y^{t,1}|$ at parton level in the all hadronic resolved topology in 0.0 < $|y^{t,1}|$ < 0.5 . Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t,2}|$ vs $|y^{t,1}|$ at parton level in the all hadronic resolved topology in 0.5 < $|y^{t,1}|$ < 1.0 . Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t,2}|$ vs $|y^{t,1}|$ at parton level in the all hadronic resolved topology in 1.0 < $|y^{t,1}|$ < 1.5 . Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t,2}|$ vs $|y^{t,1}|$ at parton level in the all hadronic resolved topology in 1.5 < $|y^{t,1}|$ < 2.5 . Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 0.0 < $|y^{t,1}|$ < 0.5 and the relative double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 0.0 < $|y^{t,1}|$ < 0.5 at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 0.5 < $|y^{t,1}|$ < 1.0 and the relative double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 0.0 < $|y^{t,1}|$ < 0.5 at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 0.5 < $|y^{t,1}|$ < 1.0 and the relative double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 0.5 < $|y^{t,1}|$ < 1.0 at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 1.0 < $|y^{t,1}|$ < 1.5 and the relative double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 0.0 < $|y^{t,1}|$ < 0.5 at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 1.0 < $|y^{t,1}|$ < 1.5 and the relative double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 0.5 < $|y^{t,1}|$ < 1.0 at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 1.0 < $|y^{t,1}|$ < 1.5 and the relative double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 1.0 < $|y^{t,1}|$ < 1.5 at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 1.5 < $|y^{t,1}|$ < 2.5 and the relative double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 0.0 < $|y^{t,1}|$ < 0.5 at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 1.5 < $|y^{t,1}|$ < 2.5 and the relative double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 0.5 < $|y^{t,1}|$ < 1.0 at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 1.5 < $|y^{t,1}|$ < 2.5 and the relative double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 1.0 < $|y^{t,1}|$ < 1.5 at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 1.5 < $|y^{t,1}|$ < 2.5 and the relative double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 1.5 < $|y^{t,1}|$ < 2.5 at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute double-differential cross-section as a function of $|y^{t,2}|$ vs $|y^{t,1}|$ at parton level in the all hadronic resolved topology in 0.0 < $|y^{t,1}|$ < 0.5 . Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t,2}|$ vs $|y^{t,1}|$ at parton level in the all hadronic resolved topology in 0.5 < $|y^{t,1}|$ < 1.0 . Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t,2}|$ vs $|y^{t,1}|$ at parton level in the all hadronic resolved topology in 1.0 < $|y^{t,1}|$ < 1.5 . Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t,2}|$ vs $|y^{t,1}|$ at parton level in the all hadronic resolved topology in 1.5 < $|y^{t,1}|$ < 2.5 . Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t,2}|$ vs $|y^{t,1}|$ in 0.0 < $|y^{t,1}|$ < 0.5 and the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 0.0 < $|y^{t,1}|$ < 0.5 at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 0.5 < $|y^{t,1}|$ < 1.0 and the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 0.0 < $|y^{t,1}|$ < 0.5 at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 0.5 < $|y^{t,1}|$ < 1.0 and the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 0.5 < $|y^{t,1}|$ < 1.0 at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 1.0 < $|y^{t,1}|$ < 1.5 and the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 0.0 < $|y^{t,1}|$ < 0.5 at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 1.0 < $|y^{t,1}|$ < 1.5 and the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 0.5 < $|y^{t,1}|$ < 1.0 at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 1.0 < $|y^{t,1}|$ < 1.5 and the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 1.0 < $|y^{t,1}|$ < 1.5 at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 1.5 < $|y^{t,1}|$ < 2.5 and the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 0.0 < $|y^{t,1}|$ < 0.5 at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 1.5 < $|y^{t,1}|$ < 2.5 and the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 0.5 < $|y^{t,1}|$ < 1.0 at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 1.5 < $|y^{t,1}|$ < 2.5 and the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 1.0 < $|y^{t,1}|$ < 1.5 at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 1.5 < $|y^{t,1}|$ < 2.5 and the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $|y^{t,1}|$ in 1.5 < $|y^{t,1}|$ < 2.5 at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative double-differential cross-section as a function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 970.0 GeV < $m^{t\bar{t}}$ < 1315.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 1315.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 1315.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 1315.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 1315.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 1315.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 1315.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 1315.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 1315.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 1315.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 1315.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 1315.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute double-differential cross-section as a function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 970.0 GeV < $m^{t\bar{t}}$ < 1315.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 1315.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 1315.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 1315.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 1315.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 1315.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 1315.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 1315.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 1315.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 1315.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 1315.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,2}$ vs $m^{t\bar{t}}$ in 1315.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative double-differential cross-section as a function of $|y^{t,1}|$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t,1}|$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t,1}|$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t,1}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV and the relative double-differential cross-section as function of $|y^{t,1}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t,1}|$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV and the relative double-differential cross-section as function of $|y^{t,1}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t,1}|$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV and the relative double-differential cross-section as function of $|y^{t,1}|$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t,1}|$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $|y^{t,1}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t,1}|$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $|y^{t,1}|$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t,1}|$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $|y^{t,1}|$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute double-differential cross-section as a function of $|y^{t,1}|$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t,1}|$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t,1}|$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t,1}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV and the absolute double-differential cross-section as function of $|y^{t,1}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t,1}|$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV and the absolute double-differential cross-section as function of $|y^{t,1}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t,1}|$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV and the absolute double-differential cross-section as function of $|y^{t,1}|$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t,1}|$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $|y^{t,1}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t,1}|$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $|y^{t,1}|$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t,1}|$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $|y^{t,1}|$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative double-differential cross-section as a function of $|y^{t,2}|$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t,2}|$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t,2}|$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t,2}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV and the relative double-differential cross-section as function of $|y^{t,2}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t,2}|$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV and the relative double-differential cross-section as function of $|y^{t,2}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t,2}|$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV and the relative double-differential cross-section as function of $|y^{t,2}|$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t,2}|$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $|y^{t,2}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t,2}|$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $|y^{t,2}|$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $|y^{t,2}|$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $|y^{t,2}|$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute double-differential cross-section as a function of $|y^{t,2}|$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t,2}|$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t,2}|$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $|y^{t,2}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV and the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV and the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV and the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $|y^{t,2}|$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative double-differential cross-section as a function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 970.0 GeV < $m^{t\bar{t}}$ < 1315.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 1315.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 1315.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 1315.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 1315.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 1315.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 1315.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 1315.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 1315.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 1315.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 1315.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 1315.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute double-differential cross-section as a function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 970.0 GeV < $m^{t\bar{t}}$ < 1315.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 1315.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 1315.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 1315.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 1315.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 1315.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 1315.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 1315.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 1315.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 1315.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 1315.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t\bar{t}}$ vs $m^{t\bar{t}}$ in 1315.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative double-differential cross-section as a function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute double-differential cross-section as a function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ at parton level in the all hadronic resolved topology in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 0.0 GeV < $m^{t\bar{t}}$ < 700.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 700.0 GeV < $m^{t\bar{t}}$ < 970.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $m^{t\bar{t}}$ in 970.0 GeV < $m^{t\bar{t}}$ < 3000.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Relative double-differential cross-section as a function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ at parton level in the all hadronic resolved topology in 0.0 GeV < $p_{T}^{t,2}$ < 170.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ at parton level in the all hadronic resolved topology in 170.0 GeV < $p_{T}^{t,2}$ < 290.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ at parton level in the all hadronic resolved topology in 290.0 GeV < $p_{T}^{t,2}$ < 450.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ at parton level in the all hadronic resolved topology in 450.0 GeV < $p_{T}^{t,2}$ < 1000.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 0.0 GeV < $p_{T}^{t,2}$ < 170.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 0.0 GeV < $p_{T}^{t,2}$ < 170.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 170.0 GeV < $p_{T}^{t,2}$ < 290.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 0.0 GeV < $p_{T}^{t,2}$ < 170.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 170.0 GeV < $p_{T}^{t,2}$ < 290.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 170.0 GeV < $p_{T}^{t,2}$ < 290.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 290.0 GeV < $p_{T}^{t,2}$ < 450.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 0.0 GeV < $p_{T}^{t,2}$ < 170.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 290.0 GeV < $p_{T}^{t,2}$ < 450.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 170.0 GeV < $p_{T}^{t,2}$ < 290.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 290.0 GeV < $p_{T}^{t,2}$ < 450.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 290.0 GeV < $p_{T}^{t,2}$ < 450.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 450.0 GeV < $p_{T}^{t,2}$ < 1000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 0.0 GeV < $p_{T}^{t,2}$ < 170.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 450.0 GeV < $p_{T}^{t,2}$ < 1000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 170.0 GeV < $p_{T}^{t,2}$ < 290.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 450.0 GeV < $p_{T}^{t,2}$ < 1000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 290.0 GeV < $p_{T}^{t,2}$ < 450.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 450.0 GeV < $p_{T}^{t,2}$ < 1000.0 GeV and the relative double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 450.0 GeV < $p_{T}^{t,2}$ < 1000.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Absolute double-differential cross-section as a function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ at parton level in the all hadronic resolved topology in 0.0 GeV < $p_{T}^{t,2}$ < 170.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ at parton level in the all hadronic resolved topology in 170.0 GeV < $p_{T}^{t,2}$ < 290.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ at parton level in the all hadronic resolved topology in 290.0 GeV < $p_{T}^{t,2}$ < 450.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ at parton level in the all hadronic resolved topology in 450.0 GeV < $p_{T}^{t,2}$ < 1000.0 GeV. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured 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 $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 0.0 GeV < $p_{T}^{t,2}$ < 170.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 0.0 GeV < $p_{T}^{t,2}$ < 170.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 170.0 GeV < $p_{T}^{t,2}$ < 290.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 0.0 GeV < $p_{T}^{t,2}$ < 170.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 170.0 GeV < $p_{T}^{t,2}$ < 290.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 170.0 GeV < $p_{T}^{t,2}$ < 290.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 290.0 GeV < $p_{T}^{t,2}$ < 450.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 0.0 GeV < $p_{T}^{t,2}$ < 170.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 290.0 GeV < $p_{T}^{t,2}$ < 450.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 170.0 GeV < $p_{T}^{t,2}$ < 290.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 290.0 GeV < $p_{T}^{t,2}$ < 450.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 290.0 GeV < $p_{T}^{t,2}$ < 450.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 450.0 GeV < $p_{T}^{t,2}$ < 1000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 0.0 GeV < $p_{T}^{t,2}$ < 170.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 450.0 GeV < $p_{T}^{t,2}$ < 1000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 170.0 GeV < $p_{T}^{t,2}$ < 290.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 450.0 GeV < $p_{T}^{t,2}$ < 1000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 290.0 GeV < $p_{T}^{t,2}$ < 450.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
Covariance matrix between the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 450.0 GeV < $p_{T}^{t,2}$ < 1000.0 GeV and the absolute double-differential cross-section as function of $p_{T}^{t,1}$ vs $p_{T}^{t,2}$ in 450.0 GeV < $p_{T}^{t,2}$ < 1000.0 GeV at parton level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.
This paper describes precision measurements of the transverse momentum $p_\mathrm{T}^{\ell\ell}$ ($\ell=e,\mu$) and of the angular variable $\phi^{*}_{\eta}$ distributions of Drell-Yan lepton pairs in a mass range of 66-116 GeV. The analysis uses data from 36.1 fb$^{-1}$ of proton-proton collisions at a centre-of-mass energy of $\sqrt{s}=13$ TeV collected by the ATLAS experiment at the LHC in 2015 and 2016. Measurements in electron-pair and muon-pair final states are performed in the same fiducial volumes, corrected for detector effects, and combined. Compared to previous measurements in proton-proton collisions at $\sqrt{s}=$7 and 8 TeV, these new measurements probe perturbative QCD at a higher centre-of-mass energy with a different composition of initial states. They reach a precision of 0.2% for the normalized spectra at low values of $p_\mathrm{T}^{\ell\ell}$. The data are compared with different QCD predictions, where it is found that predictions based on resummation approaches can describe the full spectrum within uncertainties.
Selected signal candidate events in data for both decay channels as well as the expected background contributions including their total uncertainties.
Selected signal candidate events in data for both decay channels as well as the expected background contributions including their total uncertainties.
Selected signal candidate events in data for both decay channels as well as the expected background contributions including their total uncertainties.
Overview of the detector efficiency correction factors, $C_{Z}$ , for the electron and muon channels and their systematic uncertainty contributions.
Overview of the detector efficiency correction factors, $C_{Z}$ , for the electron and muon channels and their systematic uncertainty contributions.
Overview of the detector efficiency correction factors, $C_{Z}$ , for the electron and muon channels and their systematic uncertainty contributions.
Measured inclusive cross-section in the fiducial volume in the electron and muon decay channels at Born level and their combination as well as the theory prediction at NNLO in $\alpha_{s}$ using the CT14 PDF set.
Measured inclusive cross-section in the fiducial volume in the electron and muon decay channels at Born level and their combination as well as the theory prediction at NNLO in $\alpha_{s}$ using the CT14 PDF set.
Measured inclusive cross-section in the fiducial volume in the electron and muon decay channels at Born level and their combination as well as the theory prediction at NNLO in $\alpha_{s}$ using the CT14 PDF set.
The measured combined normalized differential cross-sections, divided by the bin-width, in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle level.
The measured combined normalized differential cross-sections, divided by the bin-width, in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle level.
The measured combined normalized differential cross-sections, divided by the bin-width, in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle level.
The measured combined normalized differential cross-sections, divided by the bin-width, in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle level.
The measured combined normalized differential cross-sections, divided by the bin-width, in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle level.
The measured combined normalized differential cross-sections, divided by the bin-width, in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle level.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid}\times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}p_{T}^{ll}$ measured on born level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid}\times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}p_{T}^{ll}$ measured on born level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid}\times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}p_{T}^{ll}$ measured on born level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid}\times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}\phi_{\eta}^{*}$ measured on born level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid}\times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}\phi_{\eta}^{*}$ measured on born level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid}\times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}\phi_{\eta}^{*}$ measured on born level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid}\times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}p_{T}^{ll}$ measured on born level for the $Z\rightarrow ee$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) and Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. for the electron momentum scale and resolution uncertainties; Elec. (Reco), Elec. (ID), Isolation, Trigger and Charge-ID denote the correlated uncertainties of the data/MC scale-factors for the electron reconstruction, identification, isolation, trigger and charge-identification efficiencies; The uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid}\times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}p_{T}^{ll}$ measured on born level for the $Z\rightarrow ee$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) and Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. for the electron momentum scale and resolution uncertainties; Elec. (Reco), Elec. (ID), Isolation, Trigger and Charge-ID denote the correlated uncertainties of the data/MC scale-factors for the electron reconstruction, identification, isolation, trigger and charge-identification efficiencies; The uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid}\times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}p_{T}^{ll}$ measured on born level for the $Z\rightarrow ee$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) and Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. for the electron momentum scale and resolution uncertainties; Elec. (Reco), Elec. (ID), Isolation, Trigger and Charge-ID denote the correlated uncertainties of the data/MC scale-factors for the electron reconstruction, identification, isolation, trigger and charge-identification efficiencies; The uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid} \times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}\phi_{\eta}^{*}$ measured on born level for the $Z\rightarrow ee$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) and Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. for the electron momentum scale and resolution uncertainties; Elec. (Reco), Elec. (ID), Isolation, Trigger and Charge-ID denote the correlated uncertainties of the data/MC scale-factors for the electron reconstruction, identification, isolation, trigger and charge-identification efficiencies; The uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid} \times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}\phi_{\eta}^{*}$ measured on born level for the $Z\rightarrow ee$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) and Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. for the electron momentum scale and resolution uncertainties; Elec. (Reco), Elec. (ID), Isolation, Trigger and Charge-ID denote the correlated uncertainties of the data/MC scale-factors for the electron reconstruction, identification, isolation, trigger and charge-identification efficiencies; The uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid} \times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}\phi_{\eta}^{*}$ measured on born level for the $Z\rightarrow ee$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) and Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. for the electron momentum scale and resolution uncertainties; Elec. (Reco), Elec. (ID), Isolation, Trigger and Charge-ID denote the correlated uncertainties of the data/MC scale-factors for the electron reconstruction, identification, isolation, trigger and charge-identification efficiencies; The uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid} \times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}p_{T}^{ll}$ measured on bare level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid} \times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}p_{T}^{ll}$ measured on bare level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid} \times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}p_{T}^{ll}$ measured on bare level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid} \times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}\phi_{\eta}^{*}$ measured on bare level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid} \times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}\phi_{\eta}^{*}$ measured on bare level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid} \times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}\phi_{\eta}^{*}$ measured on bare level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Measured combined normalized differential cross-section in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle.
Measured combined normalized differential cross-section in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle.
Measured combined normalized differential cross-section in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle.
Measured combined normalized differential cross-section in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle.
Measured combined normalized differential cross-section in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle.
Measured combined normalized differential cross-section in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle.
The distribution of events passing the selection requirements in the electron channel as a function of dilepton invariant mass $m_{ll}$ , the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the electron channel as a function of dilepton invariant mass $m_{ll}$ , the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the electron channel as a function of dilepton invariant mass $m_{ll}$ , the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of dilepton invariant mass $m_{ll}$, the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of dilepton invariant mass $m_{ll}$, the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of dilepton invariant mass $m_{ll}$, the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the electron channel as a function of lepton pseudorapidity $\eta$, the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the electron channel as a function of lepton pseudorapidity $\eta$, the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the electron channel as a function of lepton pseudorapidity $\eta$, the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of lepton pseudorapidity $\eta$, the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of lepton pseudorapidity $\eta$, the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of lepton pseudorapidity $\eta$, the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the electron channel as a function of dilepton transverse momentum. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the electron channel as a function of dilepton transverse momentum. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the electron channel as a function of dilepton transverse momentum. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of dilepton transverse momentum. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of dilepton transverse momentum. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of dilepton transverse momentum. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the electron channel as a function of $\phi_{\eta}^{*}$. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the electron channel as a function of $\phi_{\eta}^{*}$. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the electron channel as a function of $\phi_{\eta}^{*}$. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of $\phi_{\eta}^{*}$. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of $\phi_{\eta}^{*}$. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of $\phi_{\eta}^{*}$. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The measured normalized cross section as a function of $p_{ll}$ for the electron and muon channels and the combined result as well as their ratio together with the total uncertainties, shown as a blue band. The pull distribution between the electron and muon channels, defined as the difference between the two channels divided by the combined uncorrelated uncertainty, is also shown. The $p_{ll}$ distribution is split into linear and logarithmic scales at 30 GeV.
The measured normalized cross section as a function of $p_{ll}$ for the electron and muon channels and the combined result as well as their ratio together with the total uncertainties, shown as a blue band. The pull distribution between the electron and muon channels, defined as the difference between the two channels divided by the combined uncorrelated uncertainty, is also shown. The $p_{ll}$ distribution is split into linear and logarithmic scales at 30 GeV.
The measured normalized cross section as a function of $p_{ll}$ for the electron and muon channels and the combined result as well as their ratio together with the total uncertainties, shown as a blue band. The pull distribution between the electron and muon channels, defined as the difference between the two channels divided by the combined uncorrelated uncertainty, is also shown. The $p_{ll}$ distribution is split into linear and logarithmic scales at 30 GeV.
The measured normalized cross section as a function of $\phi_{\eta}^{*}$ for the electron and muon channels and the combined result as well as their ratio together with the total uncertainties, shown as a blue band. The pull distribution between the electron and muon channels, defined as the difference between the two channels divided by the combined uncorrelated uncertainty, is also shown.
The measured normalized cross section as a function of $\phi_{\eta}^{*}$ for the electron and muon channels and the combined result as well as their ratio together with the total uncertainties, shown as a blue band. The pull distribution between the electron and muon channels, defined as the difference between the two channels divided by the combined uncorrelated uncertainty, is also shown.
The measured normalized cross section as a function of $\phi_{\eta}^{*}$ for the electron and muon channels and the combined result as well as their ratio together with the total uncertainties, shown as a blue band. The pull distribution between the electron and muon channels, defined as the difference between the two channels divided by the combined uncorrelated uncertainty, is also shown.
Comparison of the normalized $p_{ll}$ distributions predicted by different computations: Pythia8 with the AZ tune, Powheg+Pythia8 with the AZNLO tune, Sherpa v2.2.1 and RadISH with the Born level combined measurement. The uncertainties of the measurement are shown as vertical bars and uncertainties of the Sherpa and RadISH predictions are indicated by the coloured bands.
Comparison of the normalized $p_{ll}$ distributions predicted by different computations: Pythia8 with the AZ tune, Powheg+Pythia8 with the AZNLO tune, Sherpa v2.2.1 and RadISH with the Born level combined measurement. The uncertainties of the measurement are shown as vertical bars and uncertainties of the Sherpa and RadISH predictions are indicated by the coloured bands.
Comparison of the normalized $p_{ll}$ distributions predicted by different computations: Pythia8 with the AZ tune, Powheg+Pythia8 with the AZNLO tune, Sherpa v2.2.1 and RadISH with the Born level combined measurement. The uncertainties of the measurement are shown as vertical bars and uncertainties of the Sherpa and RadISH predictions are indicated by the coloured bands.
Comparison of the normalized $\phi_{\eta}^{*}$ distributions predicted by different computations: Pythia8 with the AZ tune, Powheg+Pythia8 with the AZNLO tune, Sherpa v2.2.1 and RadISH with the Born level combined measurement. The uncertainties of the measurement are shown as vertical bars and uncertainties of the Sherpa and RadISH predictions are indicated by the coloured bands.
Comparison of the normalized $\phi_{\eta}^{*}$ distributions predicted by different computations: Pythia8 with the AZ tune, Powheg+Pythia8 with the AZNLO tune, Sherpa v2.2.1 and RadISH with the Born level combined measurement. The uncertainties of the measurement are shown as vertical bars and uncertainties of the Sherpa and RadISH predictions are indicated by the coloured bands.
Comparison of the normalized $\phi_{\eta}^{*}$ distributions predicted by different computations: Pythia8 with the AZ tune, Powheg+Pythia8 with the AZNLO tune, Sherpa v2.2.1 and RadISH with the Born level combined measurement. The uncertainties of the measurement are shown as vertical bars and uncertainties of the Sherpa and RadISH predictions are indicated by the coloured bands.
Comparison of the normalized $p_{ll}$ distribution in the range $p_{ll}$ > 10 GeV. The Born level combined measurement is compared with predictions by Sherpa v2.2.1, fixed-order NNLOjet and NNLOjet supplied with NLO electroweak corrections. The uncertainties in the measurement are shown as vertical bars and the uncertainties in the predictions are indicated by the coloured bands.
Comparison of the normalized $p_{ll}$ distribution in the range $p_{ll}$ > 10 GeV. The Born level combined measurement is compared with predictions by Sherpa v2.2.1, fixed-order NNLOjet and NNLOjet supplied with NLO electroweak corrections. The uncertainties in the measurement are shown as vertical bars and the uncertainties in the predictions are indicated by the coloured bands.
Comparison of the normalized $p_{ll}$ distribution in the range $p_{ll}$ > 10 GeV. The Born level combined measurement is compared with predictions by Sherpa v2.2.1, fixed-order NNLOjet and NNLOjet supplied with NLO electroweak corrections. The uncertainties in the measurement are shown as vertical bars and the uncertainties in the predictions are indicated by the coloured bands.
The measured combined normalized differential cross-sections, divided by the bin-width, in the fiducial volume at dressed level.
The measured combined normalized differential cross-sections, divided by the bin-width, in the fiducial volume at dressed level.
The inclusive top quark pair ($t\bar{t}$) production cross-section $\sigma_{t\bar{t}}$ has been measured in proton$-$proton collisions at $\sqrt{s}=13$ TeV, using $36.1$ fb$^{-1}$ of data collected in 2015$-$16 by the ATLAS experiment at the LHC. Using events with an opposite-charge $e\mu$ pair and $b$-tagged jets, the cross-section is measured to be: \begin{equation}\nonumber \sigma_{t\bar{t}} = 826.4 \pm 3.6\,\mathrm{(stat)}\ \pm 11.5\,\mathrm{(syst)}\ \pm 15.7\,\mathrm{(lumi)}\ \pm 1.9\,\mathrm{(beam)}\,\mathrm{pb}, \end{equation} where the uncertainties reflect the limited size of the data sample, experimental and theoretical systematic effects, the integrated luminosity, and the LHC beam energy, giving a total uncertainty of 2.4%. The result is consistent with theoretical QCD calculations at next-to-next-to-leading order. It is used to determine the top quark pole mass via the dependence of the predicted cross-section on $m_t^{\mathrm{pole}}$, giving $m_t^{\mathrm{pole}}=173.1^{+2.0}_{-2.1}$ GeV. It is also combined with measurements at $\sqrt{s}=7$ TeV and $\sqrt{s}=8$ TeV to derive ratios and double ratios of $t\bar{t}$ and $Z$ cross-sections at different energies. The same event sample is used to measure absolute and normalised differential cross-sections as functions of single-lepton and dilepton kinematic variables, and the results compared with predictions from various Monte Carlo event generators.
Absolute differential cross-section in the fiducial region as a function of lepton pT. The first column gives the cross-section including contributions from leptonic tau decays, the second without. Systematic uncertainties are given for ttbar modelling (ttmod), lepton calibration (lept), jet and b-tagging calibration (jet), backgrounds (bkg) and integrated luminosity and beam energy (leb). The last bin includes overflow beyond the upper bin boundary. The corresponding correlation matrices are given in Tables 23 and 24.
Normalised differential cross-section in the fiducial region as a function of lepton pT. The first column gives the cross-section including contributions from leptonic tau decays, the second without. Systematic uncertainties are given for ttbar modelling (ttmod), lepton calibration (lept), jet and b-tagging calibration (jet), backgrounds (bkg) and integrated luminosity and beam energy (leb). The last bin includes overflow beyond the upper bin boundary. The corresponding correlation matrices are given in Tables 25 and 26.
Absolute differential cross-section in the fiducial region as a function of lepton |eta|. The first column gives the cross-section including contributions from leptonic tau decays, the second without. Systematic uncertainties are given for ttbar modelling (ttmod), lepton calibration (lept), jet and b-tagging calibration (jet), backgrounds (bkg) and integrated luminosity and beam energy (leb). The corresponding correlation matrices are given in Tables 27 and 28.
Normalised differential cross-section in the fiducial region as a function of lepton |eta|. The first column gives the cross-section including contributions from leptonic tau decays, the second without. Systematic uncertainties are given for ttbar modelling (ttmod), lepton calibration (lept), jet and b-tagging calibration (jet), backgrounds (bkg) and integrated luminosity and beam energy (leb). The corresponding correlation matrices are given in Tables 29 and 30.
Absolute differential cross-section in the fiducial region as a function of dilepton pT. The first column gives the cross-section including contributions from leptonic tau decays, the second without. Systematic uncertainties are given for ttbar modelling (ttmod), lepton calibration (lept), jet and b-tagging calibration (jet), backgrounds (bkg) and integrated luminosity and beam energy (leb). The last bin includes overflow beyond the upper bin boundary. The corresponding correlation matrices are given in Tables 31 and 32.
Normalised differential cross-section in the fiducial region as a function of dilepton pT. The first column gives the cross-section including contributions from leptonic tau decays, the second without. Systematic uncertainties are given for ttbar modelling (ttmod), lepton calibration (lept), jet and b-tagging calibration (jet), backgrounds (bkg) and integrated luminosity and beam energy (leb). The last bin includes overflow beyond the upper bin boundary. The corresponding correlation matrices are given in Tables 33 and 34.
Absolute differential cross-section in the fiducial region as a function of dilepton invariant mass. The first column gives the cross-section including contributions from leptonic tau decays, the second without. Systematic uncertainties are given for ttbar modelling (ttmod), lepton calibration (lept), jet and b-tagging calibration (jet), backgrounds (bkg) and integrated luminosity and beam energy (leb). The last bin includes overflow beyond the upper bin boundary. The corresponding correlation matrices are given in Tables 35 and 36.
Normalised differential cross-section in the fiducial region as a function of dilepton invariant mass. The first column gives the cross-section including contributions from leptonic tau decays, the second without. Systematic uncertainties are given for ttbar modelling (ttmod), lepton calibration (lept), jet and b-tagging calibration (jet), backgrounds (bkg) and integrated luminosity and beam energy (leb). The last bin includes overflow beyond the upper bin boundary. The corresponding correlation matrices are given in Tables 37 and 38.
Absolute differential cross-section in the fiducial region as a function of dilepton |rapidity|. The first column gives the cross-section including contributions from leptonic tau decays, the second without. Systematic uncertainties are given for ttbar modelling (ttmod), lepton calibration (lept), jet and b-tagging calibration (jet), backgrounds (bkg) and integrated luminosity and beam energy (leb). The corresponding correlation matrices are given in Tables 39 and 40.
Normalised differential cross-section in the fiducial region as a function of dilepton |rapidity|. The first column gives the cross-section including contributions from leptonic tau decays, the second without. Systematic uncertainties are given for ttbar modelling (ttmod), lepton calibration (lept), jet and b-tagging calibration (jet), backgrounds (bkg) and integrated luminosity and beam energy (leb). The corresponding correlation matrices are given in Tables 41 and 42.
Absolute differential cross-section in the fiducial region as a function of the azimuthal angle between the leptons. The first column gives the cross-section including contributions from leptonic tau decays, the second without. Systematic uncertainties are given for ttbar modelling (ttmod), lepton calibration (lept), jet and b-tagging calibration (jet), backgrounds (bkg) and integrated luminosity and beam energy (leb). The corresponding correlation matrices are given in Tables 43 and 44.
Normalised differential cross-section in the fiducial region as a function of the azimuthal angle between the leptons. The first column gives the cross-section including contributions from leptonic tau decays, the second without. Systematic uncertainties are given for ttbar modelling (ttmod), lepton calibration (lept), jet and b-tagging calibration (jet), backgrounds (bkg) and integrated luminosity and beam energy (leb). The corresponding correlation matrices are given in Tables 45 and 46.
Absolute differential cross-section in the fiducial region as a function of the sum of pT of the two leptons. The first column gives the cross-section including contributions from leptonic tau decays, the second without. Systematic uncertainties are given for ttbar modelling (ttmod), lepton calibration (lept), jet and b-tagging calibration (jet), backgrounds (bkg) and integrated luminosity and beam energy (leb). The last bin includes overflow beyond the upper bin boundary. The corresponding correlation matrices are given in Tables 47 and 48.
Normalised differential cross-section in the fiducial region as a function of the sum of pT of the two leptons. The first column gives the cross-section including contributions from leptonic tau decays, the second without. Systematic uncertainties are given for ttbar modelling (ttmod), lepton calibration (lept), jet and b-tagging calibration (jet), backgrounds (bkg) and integrated luminosity and beam energy (leb). The last bin includes overflow beyond the upper bin boundary. The corresponding correlation matrices are given in Tables 49 and 50.
Absolute differential cross-section in the fiducial region as a function of the sum of the energies of the two leptons. The first column gives the cross-section including contributions from leptonic tau decays, the second without. Systematic uncertainties are given for ttbar modelling (ttmod), lepton calibration (lept), jet and b-tagging calibration (jet), backgrounds (bkg) and integrated luminosity and beam energy (leb). The last bin includes overflow beyond the upper bin boundary. The corresponding correlation matrices are given in Tables 51 and 52.
Normalised differential cross-section in the fiducial region as a function of the sum of the energies of the two leptons. The first column gives the cross-section including contributions from leptonic tau decays, the second without. Systematic uncertainties are given for ttbar modelling (ttmod), lepton calibration (lept), jet and b-tagging calibration (jet), backgrounds (bkg) and integrated luminosity and beam energy (leb). The last bin includes overflow beyond the upper bin boundary. The corresponding correlation matrices are given in Tables 53 and 54.
Absolute differential cross-section in the fiducial region as a function of lepton |eta| and dilepton invariant mass. The first four columns give the cross-section including contributions from leptonic tau decays in the four mass bins, and the last four columns do not include the leptonic tau contributions. Systematic uncertainties are given for ttbar modelling (ttmod), lepton calibration (lept), jet and b-tagging calibration (jet), backgrounds (bkg) and integrated luminosity and beam energy (leb).
Normalised differential cross-section in the fiducial region as a function of lepton |eta| and dilepton invariant mass. The first four columns give the cross-section including contributions from leptonic tau decays in the four mass bins, and the last four columns do not include the leptonic tau contributions. Systematic uncertainties are given for ttbar modelling (ttmod), lepton calibration (lept), jet and b-tagging calibration (jet), backgrounds (bkg) and integrated luminosity and beam energy (leb).
Absolute differential cross-section in the fiducial region as a function of dilepton |rapidity| and dilepton invariant mass. The first four columns give the cross-section including contributions from leptonic tau decays in the four mass bins, and the last four columns do not include the leptonic tau contributions. Systematic uncertainties are given for ttbar modelling (ttmod), lepton calibration (lept), jet and b-tagging calibration (jet), backgrounds (bkg) and integrated luminosity and beam energy (leb).
Normalised differential cross-section in the fiducial region as a function of dilepton |rapidity| and dilepton invariant mass. The first four columns give the cross-section including contributions from leptonic tau decays in the four mass bins, and the last four columns do not include the leptonic tau contributions. Systematic uncertainties are given for ttbar modelling (ttmod), lepton calibration (lept), jet and b-tagging calibration (jet), backgrounds (bkg) and integrated luminosity and beam energy (leb).
Absolute differential cross-section in the fiducial region as a function of the azimuthal angle between the leptons and dilepton invariant mass. The first four columns give the cross-section including contributions from leptonic tau decays in the four mass bins, and the last four columns do not include the leptonic tau contributions. Systematic uncertainties are given for ttbar modelling (ttmod), lepton calibration (lept), jet and b-tagging calibration (jet), backgrounds (bkg) and integrated luminosity and beam energy (leb).
Normalised differential cross-section in the fiducial region as a function of the azimuthal angle between the leptons and dilepton invariant mass. The first four columns give the cross-section including contributions from leptonic tau decays in the four mass bins, and the last four columns do not include the leptonic tau contributions. Systematic uncertainties are given for ttbar modelling (ttmod), lepton calibration (lept), jet and b-tagging calibration (jet), backgrounds (bkg) and integrated luminosity and beam energy (leb).
Correlation matrix for the absolute differential cross-section in the fiducial region as a function of lepton pT as measured in Table 1, including tau decay contributions.
Correlation matrix for the absolute differential cross-section in the fiducial region as a function of lepton pT as measured in Table 1, not including tau decay contributions.
Correlation matrix for the normalised differential cross-section in the fiducial region as a function of lepton pT as measured in Table 2, including tau decay contributions.
Correlation matrix for the normalised differential cross-section in the fiducial region as a function of lepton pT as measured in Table 2, not including tau decay contributions.
Correlation matrix for the absolute differential cross-section in the fiducial region as a function of lepton |eta| as measured in Table 3, including tau decay contributions.
Correlation matrix for the absolute differential cross-section in the fiducial region as a function of lepton |eta| as measured in Table 3, not including tau decay contributions.
Correlation matrix for the normalised differential cross-section in the fiducial region as a function of lepton |eta| as measured in Table 4, including tau decay contributions.
Correlation matrix for the normalised differential cross-section in the fiducial region as a function of lepton |eta| as measured in Table 4, not including tau decay contributions.
Correlation matrix for the absolute differential cross-section in the fiducial region as a function of dilepton pT as measured in Table 5, including tau decay contributions.
Correlation matrix for the absolute differential cross-section in the fiducial region as a function of dilepton pT as measured in Table 5, not including tau decay contributions.
Correlation matrix for the normalised differential cross-section in the fiducial region as a function of dilepton pT as measured in Table 6, including tau decay contributions.
Correlation matrix for the normalised differential cross-section in the fiducial region as a function of dilepton pT as measured in Table 6, not including tau decay contributions.
Correlation matrix for the absolute differential cross-section in the fiducial region as a function of dilepton invariant mass as measured in Table 7, including tau decay contributions.
Correlation matrix for the absolute differential cross-section in the fiducial region as a function of dilepton invariant mass as measured in Table 7, not including tau decay contributions.
Correlation matrix for the normalised differential cross-section in the fiducial region as a function of dilepton invariant mass as measured in Table 8, including tau decay contributions.
Correlation matrix for the normalised differential cross-section in the fiducial region as a function of dilepton invariant mass as measured in Table 8, not including tau decay contributions.
Correlation matrix for the absolute differential cross-section in the fiducial region as a function of dilepton |rapidity| as measured in Table 9, including tau decay contributions.
Correlation matrix for the absolute differential cross-section in the fiducial region as a function of dilepton |rapidity| as measured in Table 9, not including tau decay contributions.
Correlation matrix for the normalised differential cross-section in the fiducial region as a function of dilepton |rapidity| as measured in Table 10, including tau decay contributions.
Correlation matrix for the normalised differential cross-section in the fiducial region as a function of dilepton |rapidity| as measured in Table 10, not including tau decay contributions.
Correlation matrix for the absolute differential cross-section in the fiducial region as a function of the azimuthal angle between the leptons as measured in Table 11, including tau decay contributions.
Correlation matrix for the absolute differential cross-section in the fiducial region as a function of the azimuthal angle between the leptons as measured in Table 11, not including tau decay contributions.
Correlation matrix for the normalised differential cross-section in the fiducial region as a function of the azimuthal angle between the leptons as measured in Table 12, including tau decay contributions.
Correlation matrix for the normalised differential cross-section in the fiducial region as a function of the azimuthal angle between the leptons as measured in Table 12, not including tau decay contributions.
Correlation matrix for the absolute differential cross-section in the fiducial region as a function of the sum of pT of the two leptons as measured in Table 13, including tau decay contributions.
Correlation matrix for the absolute differential cross-section in the fiducial region as a function of the sum of pT of the two leptons as measured in Table 13, not including tau decay contributions.
Correlation matrix for the normalised differential cross-section in the fiducial region as a function of the sum of pT of the two leptons as measured in Table 14, including tau decay contributions.
Correlation matrix for the normalised differential cross-section in the fiducial region as a function of the sum of pT of the two leptons as measured in Table 14, not including tau decay contributions.
Correlation matrix for the absolute differential cross-section in the fiducial region as a function of the sum of the energies of the two leptons as measured in Table 15, including tau decay contributions.
Correlation matrix for the absolute differential cross-section in the fiducial region as a function of the sum of the energies of the two leptons as measured in Table 15, not including tau decay contributions.
Correlation matrix for the normalised differential cross-section in the fiducial region as a function of the sum of the energies of the two leptons as measured in Table 16, including tau decay contributions.
Correlation matrix for the normalised differential cross-section in the fiducial region as a function of the sum of the energies of the two leptons as measured in Table 16, not including tau decay contributions.
Correlation matrix for the combination of all eight one-dimensional absolute fiducial cross-section measurements, including tau decay contributions. The observables are arranged as follows: lepton pT (bins 1-11),lepton |eta| (bins 12-20),dilepton pT (bins 21-29),dilepton invariant mass (bins 30-41),dilepton |rapidity| (bins 42-50),the azimuthal angle between the leptons (bins 51-60),the sum of pT of the two leptons (bins 61-68),the sum of the energies of the two leptons (bins 69-78).
Correlation matrix for the combination of all eight one-dimensional absolute fiducial cross-section measurements, not including tau decay contributions. The observables are arranged as follows: lepton pT (bins 1-11),lepton |eta| (bins 12-20),dilepton pT (bins 21-29),dilepton invariant mass (bins 30-41),dilepton |rapidity| (bins 42-50),the azimuthal angle between the leptons (bins 51-60),the sum of pT of the two leptons (bins 61-68),the sum of the energies of the two leptons (bins 69-78).
Correlation matrix for the combination of all eight one-dimensional normalised fiducial cross-section measurements, including tau decay contributions. The observables are arranged as follows: lepton pT (bins 1-10),lepton |eta| (bins 11-18),dilepton pT (bins 19-26),dilepton invariant mass (bins 27-37),dilepton |rapidity| (bins 38-45),the azimuthal angle between the leptons (bins 46-54),the sum of pT of the two leptons (bins 55-61),the sum of the energies of the two leptons (bins 62-70).
Correlation matrix for the combination of all eight one-dimensional normalised fiducial cross-section measurements, not including tau decay contributions. The observables are arranged as follows: lepton pT (bins 1-10),lepton |eta| (bins 11-18),dilepton pT (bins 19-26),dilepton invariant mass (bins 27-37),dilepton |rapidity| (bins 38-45),the azimuthal angle between the leptons (bins 46-54),the sum of pT of the two leptons (bins 55-61),the sum of the energies of the two leptons (bins 62-70).
Fiducial region definition
A search is presented for pair-production of long-lived neutral particles using 33 fb$^{-1}$ of $\sqrt{s} = 13$ TeV proton-proton collision data, collected during 2016 by the ATLAS detector at the LHC. This search focuses on a topology in which one long-lived particle decays in the ATLAS inner detector and the other decays in the muon spectrometer. Special techniques are employed to reconstruct the displaced tracks and vertices in the inner detector and in the muon spectrometer. One event is observed that passes the full event selection, which is consistent with the estimated background. Limits are placed on scalar boson propagators with masses from 125 GeV to 1000 GeV decaying into pairs of long-lived hidden-sector scalars with masses from 8 GeV to 400 GeV. The limits placed on several low-mass scalars extend previous exclusion limits in the range of proper lifetimes $c \tau$ from 5 cm to 1 m.
IDVx selection efficiency as a function of the radial decay position for $m_H = 125$ GeV.
IDVx selection efficiency as a function of the radial decay position for $m_s = 50$ GeV.
Observed $CL_S$ limits on $BR$ for $m_H = 125$ GeV.
Observed $CL_S$ limits on $\sigma \times BR$ for $m_{\Phi} = 200-400$ GeV.
Observed $CL_S$ limits on $\sigma \times BR$ for $m_{\Phi} = 600-1000$ GeV.
Combined limits from this analysis (ID) and the CR and MS analyses for $m_{H} = 125$ GeV, $m_s = 15$ GeV.
Combined limits from this analysis (ID) and the CR and MS analyses for $m_{H} = 125$ GeV, $m_s = 25$ GeV.
Combined limits from this analysis (ID) and the CR and MS analyses for $m_{H} = 125$ GeV, $m_s = 40$ GeV.
Combined limits from this analysis (ID) and the CR and MS analyses for $m_{H} = 125$ GeV, $m_s = 55$ GeV.
Combined limits from this analysis (ID) and the CR and MS analyses for $m_{\Phi} = 200$ GeV, $m_s = 25$ GeV.
Combined limits from this analysis (ID) and the CR and MS analyses for $m_{\Phi} = 200$ GeV, $m_s = 50$ GeV.
Comparison of the IDVx reconstruction and selection efficiency for a Higgs with a mass of 125 GeV decaying to an LLP with a mass of 8 GeV, using only standard tracking versus using standard and large radius tracking for all ID vertices in the signal MC sample.
Comparison of the IDVx reconstruction and selection efficiency for a Higgs with a mass of 125 GeV decaying to an LLP with a mass of 8 GeV, using only standard tracking versus using standard and large radius tracking for ID vertices passing the full IDVx selection criteria.
Comparison of the IDVx reconstruction and selection efficiency for a $\Phi$ with a mass of 1000 GeV decaying to an LLP with a mass of 150 GeV, using only standard tracking versus using standard and large radius tracking for all ID vertices in the signal MC sample.
Comparison of the IDVx reconstruction and selection efficiency for a $\Phi$ with a mass of 1000 GeV decaying to an LLP with a mass of 150 GeV, using only standard tracking versus using standard and large radius tracking for ID vertices passing the full IDVx selection criteria.
The IDVx selection efficiency as a function of long-lived particle decay $z$ position for MC signal samples with a 125 GeV Higgs boson decaying to LLPs with masses of 8, 25, and 55 GeV. The efficiency for the 55 GeV LLP sample is shown both with and without the material veto applied.
The IDVx selection efficiency as a function of long-lived particle decay $z$ position for MC signal samples with mediators of masses 200, 400, and 600 GeV decaying to LLPs with a mass of 50 GeV. The efficiency for the 200 GeV mediator sample is shown both with and without the material veto applied.
The impact of the IDVx selections on the selection efficiency for the MC signal sample with a Higgs with a mass of 125 GeV decaying to an LLP with a mass of 8 GeV.
The impact of the IDVx selections on the selection efficiency for the MC signal sample with a Higgs with a mass of 125 GeV decaying to an LLP with a mass of 8 GeV.
The impact of the IDVx selections on the selection efficiency for the MC signal sample with a Higgs with a mass of 125 GeV decaying to an LLP with a mass of 8 GeV.
The impact of the IDVx selections on the selection efficiency for the MC signal sample with a $\Phi$ with a mass of 400 GeV decaying to an LLP with a mass of 50 GeV.
The impact of the IDVx selections on the selection efficiency for the MC signal sample with a $\Phi$ with a mass of 400 GeV decaying to an LLP with a mass of 50 GeV.
The impact of the IDVx selections on the selection efficiency for the MC signal sample with a $\Phi$ with a mass of 400 GeV decaying to an LLP with a mass of 50 GeV.
The impact of the IDVx selections on the selection efficiency for the MC signal sample with a $\Phi$ with a mass of 1000 GeV decaying to an LLP with a mass of 150 GeV.
The impact of the IDVx selections on the selection efficiency for the MC signal sample with a $\Phi$ with a mass of 1000 GeV decaying to an LLP with a mass of 150 GeV.
The impact of the IDVx selections on the selection efficiency for the MC signal sample with a $\Phi$ with a mass of 1000 GeV decaying to an LLP with a mass of 150 GeV.
$CL_S$ limits on $B_{H\rightarrow ss}$ for $m_{H} = 125$ GeV, $m_s = 8$ GeV.
$CL_S$ limits on $B_{H\rightarrow ss}$ for $m_{H} = 125$ GeV, $m_s = 15$ GeV.
$CL_S$ limits on $B_{H\rightarrow ss}$ for $m_{H} = 125$ GeV, $m_s = 25$ GeV.
$CL_S$ limits on $B_{H\rightarrow ss}$ for $m_{H} = 125$ GeV, $m_s = 40$ GeV.
$CL_S$ limits on $B_{H\rightarrow ss}$ for $m_{H} = 125$ GeV, $m_s = 55$ GeV.
$CL_S$ limits on $\sigma \times B_{\Phi\rightarrow ss}$ for $m_{\Phi} = 200$ GeV, $m_s = 8$ GeV.
$CL_S$ limits on $\sigma \times B_{\Phi\rightarrow ss}$ for $m_{\Phi} = 200$ GeV, $m_s = 25$ GeV.
$CL_S$ limits on $\sigma \times B_{\Phi\rightarrow ss}$ for $m_{\Phi} = 200$ GeV, $m_s = 50$ GeV.
$CL_S$ limits on $\sigma \times B_{\Phi\rightarrow ss}$ for $m_{\Phi} = 400$ GeV, $m_s = 50$ GeV.
$CL_S$ limits on $\sigma \times B_{\Phi\rightarrow ss}$ for $m_{\Phi} = 400$ GeV, $m_s = 100$ GeV.
$CL_S$ limits on $\sigma \times B_{\Phi\rightarrow ss}$ for $m_{\Phi} = 600$ GeV, $m_s = 50$ GeV.
$CL_S$ limits on $\sigma \times B_{\Phi\rightarrow ss}$ for $m_{\Phi} = 600$ GeV, $m_s = 150$ GeV.
$CL_S$ limits on $\sigma \times B_{\Phi\rightarrow ss}$ for $m_{\Phi} = 1000$ GeV, $m_s = 50$ GeV.
$CL_S$ limits on $\sigma \times B_{\Phi\rightarrow ss}$ for $m_{\Phi} = 1000$ GeV, $m_s = 150$ GeV.
$CL_S$ limits on $\sigma \times B_{\Phi\rightarrow ss}$ for $m_{\Phi} = 1000$ GeV, $m_s = 400$ GeV.
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