Showing 10 of 425 results
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 measurement of novel event shapes quantifying the isotropy of collider events is performed in 140 fb$^{-1}$ of proton-proton collisions with $\sqrt s=13$ TeV centre-of-mass energy recorded with the ATLAS detector at CERN's Large Hadron Collider. These event shapes are defined as the Wasserstein distance between collider events and isotropic reference geometries. This distance is evaluated by solving optimal transport problems, using the 'Energy-Mover's Distance'. Isotropic references with cylindrical and circular symmetries are studied, to probe the symmetries of interest at hadron colliders. The novel event-shape observables defined in this way are infrared- and collinear-safe, have improved dynamic range and have greater sensitivity to isotropic radiation patterns than other event shapes. The measured event-shape variables are corrected for detector effects, and presented in inclusive bins of jet multiplicity and the scalar sum of the two leading jets' transverse momenta. The measured distributions are provided as inputs to future Monte Carlo tuning campaigns and other studies probing fundamental properties of QCD and the production of hadronic final states up to the TeV-scale.
IRing2 for HT2>=500 GeV, NJets>=2
IRing2 for HT2>=500 GeV, NJets>=3
IRing2 for HT2>=500 GeV, NJets>=4
IRing2 for HT2>=500 GeV, NJets>=5
IRing2 for HT2>=1000 GeV, NJets>=2
IRing2 for HT2>=1000 GeV, NJets>=3
IRing2 for HT2>=1000 GeV, NJets>=4
IRing2 for HT2>=1000 GeV, NJets>=5
IRing2 for HT2>=1500 GeV, NJets>=2
IRing2 for HT2>=1500 GeV, NJets>=3
IRing2 for HT2>=1500 GeV, NJets>=4
IRing2 for HT2>=1500 GeV, NJets>=5
IRing128 for HT2>=500 GeV, NJets>=2
IRing128 for HT2>=500 GeV, NJets>=3
IRing128 for HT2>=500 GeV, NJets>=4
IRing128 for HT2>=500 GeV, NJets>=5
IRing128 for HT2>=1000 GeV, NJets>=2
IRing128 for HT2>=1000 GeV, NJets>=3
IRing128 for HT2>=1000 GeV, NJets>=4
IRing128 for HT2>=1000 GeV, NJets>=5
IRing128 for HT2>=1500 GeV, NJets>=2
IRing128 for HT2>=1500 GeV, NJets>=3
IRing128 for HT2>=1500 GeV, NJets>=4
IRing128 for HT2>=1500 GeV, NJets>=5
ICyl16 for HT2>=500 GeV, NJets>=2
ICyl16 for HT2>=500 GeV, NJets>=3
ICyl16 for HT2>=500 GeV, NJets>=4
ICyl16 for HT2>=500 GeV, NJets>=5
ICyl16 for HT2>=1000 GeV, NJets>=2
ICyl16 for HT2>=1000 GeV, NJets>=3
ICyl16 for HT2>=1000 GeV, NJets>=4
ICyl16 for HT2>=1000 GeV, NJets>=5
ICyl16 for HT2>=1500 GeV, NJets>=2
ICyl16 for HT2>=1500 GeV, NJets>=3
ICyl16 for HT2>=1500 GeV, NJets>=4
ICyl16 for HT2>=1500 GeV, NJets>=5
IRing2 covariance for HT2>=500 GeV, NJets>=2 (Table 1)
IRing2 covariance for HT2>=500 GeV, NJets>=3 (Table 2)
IRing2 covariance for HT2>=500 GeV, NJets>=4 (Table 3)
IRing2 covariance for HT2>=500 GeV, NJets>=5 (Table 4)
IRing2 covariance for HT2>=1000 GeV, NJets>=2 (Table 5)
IRing2 covariance for HT2>=1000 GeV, NJets>=3 (Table 6)
IRing2 covariance for HT2>=1000 GeV, NJets>=4 (Table 7)
IRing2 covariance for HT2>=1000 GeV, NJets>=5 (Table 8)
IRing2 covariance for HT2>=1500 GeV, NJets>=2 (Table 9)
IRing2 covariance for HT2>=1500 GeV, NJets>=3 (Table 10)
IRing2 covariance for HT2>=1500 GeV, NJets>=4 (Table 11)
IRing2 covariance for HT2>=1500 GeV, NJets>=5 (Table 12)
IRing128 covariance for HT2>=500 GeV, NJets>=2 (Table 13)
IRing128 covariance for HT2>=500 GeV, NJets>=3 (Table 14)
IRing128 covariance for HT2>=500 GeV, NJets>=4 (Table 15)
IRing128 covariance for HT2>=500 GeV, NJets>=5 (Table 16)
IRing128 covariance for HT2>=1000 GeV, NJets>=2 (Table 17)
IRing128 covariance for HT2>=1000 GeV, NJets>=3 (Table 18)
IRing128 covariance for HT2>=1000 GeV, NJets>=4 (Table 19)
IRing128 covariance for HT2>=1000 GeV, NJets>=5 (Table 20)
IRing128 covariance for HT2>=1500 GeV, NJets>=2 (Table 21)
IRing128 covariance for HT2>=1500 GeV, NJets>=3 (Table 22)
IRing128 covariance for HT2>=1500 GeV, NJets>=4 (Table 23)
IRing128 covariance for HT2>=1500 GeV, NJets>=5 (Table 24)
ICyl16 covariance for HT2>=500 GeV, NJets>=2 (Table 25)
ICyl16 covariance for HT2>=500 GeV, NJets>=3 (Table 26)
ICyl16 covariance for HT2>=500 GeV, NJets>=4 (Table 27)
ICyl16 covariance for HT2>=500 GeV, NJets>=5 (Table 28)
ICyl16 covariance for HT2>=1000 GeV, NJets>=2 (Table 29)
ICyl16 covariance for HT2>=1000 GeV, NJets>=3 (Table 30)
ICyl16 covariance for HT2>=1000 GeV, NJets>=4 (Table 31)
ICyl16 covariance for HT2>=1000 GeV, NJets>=5 (Table 32)
ICyl16 covariance for HT2>=1500 GeV, NJets>=2 (Table 33)
ICyl16 covariance for HT2>=1500 GeV, NJets>=3 (Table 34)
ICyl16 covariance for HT2>=1500 GeV, NJets>=4 (Table 35)
ICyl16 covariance for HT2>=1500 GeV, NJets>=5 (Table 36)
IRing2 covariance, complete
1-IRing128 covariance, complete
1-ICyl16 covariance, complete
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.
Differential cross-section measurements are presented for the electroweak production of two jets in association with a $Z$ boson. These measurements are sensitive to the vector-boson fusion production mechanism and provide a fundamental test of the gauge structure of the Standard Model. The analysis is performed using proton-proton collision data collected by ATLAS at $\sqrt{s}$=13 TeV and with an integrated luminosity of 139 fb$^{-1}$. The differential cross-sections are measured in the $Z\rightarrow \ell^+\ell^-$ decay channel ($\ell=e,\mu$) as a function of four observables: the dijet invariant mass, the rapidity interval spanned by the two jets, the signed azimuthal angle between the two jets, and the transverse momentum of the dilepton pair. The data are corrected for the effects of detector inefficiency and resolution and are sufficiently precise to distinguish between different state-of-the-art theoretical predictions calculated using Powheg+Pythia8, Herwig7+Vbfnlo and Sherpa 2.2. The differential cross-sections are used to search for anomalous weak-boson self-interactions using a dimension-six effective field theory. The differential cross-section as a function of the signed azimuthal angle between the two jets is found to be particularly sensitive to the interference between the Standard Model and dimension-six scattering amplitudes and provides a direct test of charge-conjugation and parity invariance in the weak-boson self-interactions.
A measurement of observables sensitive to effects of colour reconnection in top-quark pair-production events is presented using 139 fb$^{-1}$ of 13$\,$TeV proton-proton collision data collected by the ATLAS detector at the LHC. Events are selected by requiring exactly one isolated electron and one isolated muon with opposite charge and two or three jets, where exactly two jets are required to be $b$-tagged. For the selected events, measurements are presented for the charged-particle multiplicity, the scalar sum of the transverse momenta of the charged particles, and the same scalar sum in bins of charged-particle multiplicity. These observables are unfolded to the stable-particle level, thereby correcting for migration effects due to finite detector resolution, acceptance and efficiency effects. The particle-level measurements are compared with different colour reconnection models in Monte Carlo generators. These measurements disfavour some of the colour reconnection models and provide inputs to future optimisation of the parameters in Monte Carlo generators.
Naming convention for the observables at different levels of the analysis. At the background-subtracted level the contributions of tracks from pile-up collisions and tracks from secondary vertices are subtracted. At the corrected level the tracking-efficiency correction (TEC) is applied. The observables at particle level are the analysis results.
The $\chi^2$ and NDF for measured normalised differential cross-sections obtained by comparing the different predictions with the unfolded data. Global($n_\text{ch},\Sigma_{n_{\text{ch}}} p_{\text{T}}$) denotes the scenario in which the covariance matrix is built including the correlations of systematic uncertainties between the two observables $n_{\text{ch}}$ and $\Sigma_{n_{\text{ch}}} p_{\text{T}}$
Normalised differential cross-section as a function of $n_\text{ch}$.
Normalised differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$.
Normalised double-differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$.
Normalised double-differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$.
Normalised double-differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 40 \leq n_\text{ch} < 60$.
Normalised double-differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 60 \leq n_\text{ch} < 80$.
Normalised double-differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n\text{ch}$ in $ n_\text{ch} \geq 80$.
The $\chi^2$ and NDF for measured absolute differential cross-sections obtained by comparing the different predictions with the unfolded data. Global($n_\text{ch},\Sigma_{n_{\text{ch}}} p_{\text{T}}$) denotes the scenario in which the covariance matrix is built including the correlations of systematic uncertainties between the two observables $n_{\text{ch}}$ and $\Sigma_{n_{\text{ch}}} p_{\text{T}}$
Absolute differential cross-section as a function of $n_\text{ch}$.
Absolute differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$.
Absolute double-differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$.
Absolute double-differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$.
Absolute double-differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 40 \leq n_\text{ch} < 60$.
Absolute double-differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 60 \leq n_\text{ch} < 80$.
Absolute double-differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n\text{ch}$ in $ n_\text{ch} \geq 80$.
Measurements of charged particle distributions, sensitive to the underlying event, have been performed with the ATLAS detector at the LHC. The measurements are based on data collected using a minimum-bias trigger to select proton-proton collisions at center-of-mass energies of 900 GeV and 7 TeV. The 'underlying event' is defined as those aspects of a hadronic interaction attributed not to the hard scattering process, but rather to the accompanying interactions of the rest of the proton. Three regions are defined in azimuthal angle with respect to the highest-pt charged particle in the event, such that the region transverse to the dominant momentum-flow is most sensitive to the underlying event. In each of these regions, distributions of the charged particle multiplicity, pt density, and average pt are measured. The data show a higher underlying event activity than that predicted by Monte Carlo models tuned to pre-LHC data.
Particle Number Density versus Lead Particle PT at centre-of-mass energy 900 GeV.
Particle Number Density versus Lead Particle PT at centre-of-mass energy 7000 GeV.
Particle PT Density versus Lead Particle PT at centre-of-mass energy 900 GeV.
Particle PT Density versus Lead Particle PT at centre-of-mass energy 7000 GeV.
Standard deviation of the Particle Number Density versus Lead Particle PT at centre-of-mass energy 900 GeV.
Standard deviation of the Particle Number Density versus Lead Particle PT at centre-of-mass energy 7000 GeV.
Standard deviation of the Particle PT Density versus Lead Particle PT at centre-of-mass energy 900 GeV.
Standard deviation of the Particle PT Density versus Lead Particle PT at centre-of-mass energy 7000 GeV.
Mean Particle PT versus Lead Particle PT at centre-of-mass energy 900 GeV.
Mean Particle PT versus Lead Particle PT at centre-of-mass energy 7000 GeV.
Mean Particle PT versus Region Particle Number at centre-of-mass energy 900 GeV.
Mean Particle PT versus Region Particle Number at centre-of-mass energy 7000 GeV.
Event Number Density versus \phi_{1} - \phi_{n} at centre-of-mass energy 900 GeV.
Event Number Density versus \phi_{1} - \phi_{n} at centre-of-mass energy 7000 GeV.
Event p_{T} Density versus \phi_{1} - \phi_{n} at centre-of-mass energy 900 GeV for a lower PT cut of 0.1 GeV.
Event p_{T} Density versus \phi_{1} - \phi_{n} at centre-of-mass energy 7000 GeV for a lower PT cut of 0.1 GeV.
Particle Number Density versus Lead Particle PT at centre-of-mass energy 900 GeV for a lower PT cut of 0.1 GeV.
Particle Number Density versus Lead Particle PT at centre-of-mass energy 7000 GeV for a lower PT cut of 0.1 GeV.
Particle PT Density versus Lead Particle PT at centre-of-mass energy 900 GeV for a lower PT cut of 0.1 GeV.
Particle PT Density versus Lead Particle PT at centre-of-mass energy 7000 GeV for a lower PT cut of 0.1 GeV.
Particle Number Density versus Leading Particle Pseudorapidity at centre-of-mass energy 7000 GeV for a lower PT cut of 0.1 GeV.
Particle PT Density versus Leading Particle Pseudorapidity at centre-of-mass energy 7000 GeV for a lower PT cut of 0.1 GeV.
This paper presents a measurement of the $W$ boson production cross section and the $W^{+}/W^{-}$ cross-section ratio, both in association with jets, in proton--proton collisions at $\sqrt{s}=8$ TeV with the ATLAS experiment at the Large Hadron Collider. The measurement is performed in final states containing one electron and missing transverse momentum using data corresponding to an integrated luminosity of 20.2 fb$^{-1}$. Differential cross sections for events with one or two jets are presented for a range of observables, including jet transverse momenta and rapidities, the scalar sum of transverse momenta of the visible particles and the missing transverse momentum in the event, and the transverse momentum of the $W$ boson. For a subset of the observables, the differential cross sections of positively and negatively charged $W$ bosons are measured separately. In the cross-section ratio of $W^{+}/W^{-}$ the dominant systematic uncertainties cancel out, improving the measurement precision by up to a factor of nine. The observables and ratios selected for this paper provide valuable input for the up quark, down quark, and gluon parton distribution functions of the proton.
Statistical correlation between bins in data for the differential cross section for the production of W bosons as a function of the leading jet p<sub>T</sub> for events with N<sub> jets</sub> ≥ 2.
Differential cross sections for the production of W<sup>+</sup> bosons, W<sup>-</sup> bosons and the W<sup>+</sup>/W<sup>-</sup> cross section ratio as a function of the leading jet p<sub>T</sub> for events with N<sub> jets</sub> ≥ 2.
Statistical correlation between bins in data for the differential cross sections for the production of W<sup>+</sup> bosons as a function of the leading jet p<sub>T</sub> for events with N<sub> jets</sub> ≥ 2.
Statistical correlation between bins in data for the differential cross sections for the production of W<sup>-</sup> bosons as a function of the leading jet p<sub>T</sub> for events with N<sub> jets</sub> ≥ 2.
Differential cross section for the production of W bosons as a function of the electron η for events with N<sub> jets</sub> ≥ 0.
Statistical correlation between bins in data for the differential cross section for the production of W bosons as a function of the electron η for events with N<sub> jets</sub> ≥ 0.
Differential cross sections for the production of W<sup>+</sup> bosons, W<sup>-</sup> bosons and the W<sup>+</sup>/W<sup>-</sup> cross section ratio as a function of the electron η for events with N<sub> jets</sub> ≥ 0.
Statistical correlation between bins in data for the differential cross sections for the production of W<sup>+</sup> bosons as a function of the electron η for events with N<sub> jets</sub> ≥ 0.
Statistical correlation between bins in data for the differential cross sections for the production of W<sup>-</sup> bosons as a function of the electron η for events with N<sub> jets</sub> ≥ 0.
Differential cross section for the production of W bosons as a function of the electron η for events with N<sub> jets</sub> ≥ 1.
Statistical correlation between bins in data for the differential cross section for the production of W bosons as a function of the electron η for events with N<sub> jets</sub> ≥ 1.
Differential cross sections for the production of W<sup>+</sup> bosons, W<sup>-</sup> bosons and the W<sup>+</sup>/W<sup>-</sup> cross section ratio as a function of the electron η for events with N<sub> jets</sub> ≥ 1.
Statistical correlation between bins in data for the differential cross sections for the production of W<sup>+</sup> bosons as a function of the electron η for events with N<sub> jets</sub> ≥ 1.
Statistical correlation between bins in data for the differential cross sections for the production of W<sup>-</sup> bosons as a function of the electron η for events with N<sub> jets</sub> ≥ 1.
List of experimentally considered systematic uncertainties for the W+jets cross section measurement
Non-perturbative corrections for the cross section for the production of W bosons for different inclusive jet multiplicities.
Non-perturbative corrections for the differential cross sections for the production of W<sup>+</sup> bosons and W<sup>-</sup> bosons as a function of the inclusive jet multiplicity.
Non-perturbative corrections for the differential cross section for the production of W bosons as a function of H<sub> T</sub> for events with N<sub> jets</sub> ≥ 1.
Non-perturbative corrections for the differential cross sections for the production of W<sup>+</sup> bosons and W<sup>-</sup> bosons as a function of the H<sub> T</sub> for events with N<sub> jets</sub> ≥ 1.
Non-perturbative corrections for the differential cross section for the production of W bosons as a function of the W p<sub>T</sub> for events with N<sub> jets</sub> ≥ 1.
Non-perturbative corrections for the differential cross sections for the production of W<sup>+</sup> bosons and W<sup>-</sup> bosons as a function of the W p<sub>T</sub> for events with N<sub> jets</sub> ≥ 1.
Non-perturbative corrections for the differential cross section for the production of W bosons as a function of the leading jet p<sub>T</sub> for events with N<sub> jets</sub> ≥ 1.
Non-perturbative corrections for the differential cross sections for the production of W<sup>+</sup> bosons and W<sup>-</sup> bosons as a function of the leading jet p<sub>T</sub> for events with N<sub> jets</sub> ≥ 1.
Non-perturbative corrections for the differential cross section for the production of W bosons as a function of the leading jet rapidity for events with N<sub> jets</sub> ≥ 1.
Non-perturbative corrections for the differential cross sections for the production of W<sup>+</sup> bosons and W<sup>-</sup> bosons as a function of the leading jet rapidity for events with N<sub> jets</sub> ≥ 1.
Non-perturbative corrections for the differential cross section for the production of W bosons as a function of second leading jet p<sub>T</sub> for events with N<sub> jets</sub> ≥ 2.
Non-perturbative corrections for the differential cross section for the production of W bosons as a function of second leading jet rapidity for events with N<sub> jets</sub> ≥ 2.
Non-perturbative corrections for the differential cross section for the production of W bosons as a function of Δ R<sub>jet1,jet2</sub> for events with N<sub> jets</sub> ≥ 2.
Non-perturbative corrections for the differential cross section for the production of W bosons as a function of dijet invariant mass for events with N<sub> jets</sub> ≥ 2.
Non-perturbative corrections for the cross section for the production of W bosons as a function of exclusive jet multiplicity.
Non-perturbative corrections for the differential cross section for the production of W bosons as a function of the H<sub> T</sub> for events with N<sub> jets</sub> ≥ 2.
Non-perturbative corrections for the differential cross sections for the production of W<sup>+</sup> bosons and W<sup>-</sup> bosons as a function of the H<sub> T</sub> for events with N<sub> jets</sub> ≥ 2.
Non-perturbative corrections for the differential cross section for the production of W bosons as a function of the W p<sub>T</sub> for events with N<sub> jets</sub> ≥ 2.
Non-perturbative corrections for the differential cross sections for the production of W<sup>+</sup> bosons and W<sup>-</sup> bosons as a function of the W p<sub>T</sub> for events with N<sub> jets</sub> ≥ 2.
Non-perturbative corrections for the differential cross section for the production of W bosons as a function of the leading jet p<sub>T</sub> for events with N<sub> jets</sub> ≥ 2.
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 $\ln{(1/z)} \times \ln{(R/\Delta R)}$.
Inclusive and differential cross-sections for the production of top quarks in association with a photon are measured with proton$-$proton collision data corresponding to an integrated luminosity of 139 fb$^{-1}$. The data were collected by the ATLAS detector at the LHC during Run 2 between 2015 and 2018 at a centre-of-mass energy of 13 TeV. The measurements are performed in a fiducial volume defined at parton level. Events with exactly one photon, one electron and one muon of opposite sign, and at least two jets, of which at least one is $b$-tagged, are selected. The fiducial cross-section is measured to be $39.6\,^{+2.7}_{-2.3}\,\textrm{fb}$. Differential cross-sections as functions of several observables are compared with state-of-the-art Monte Carlo simulations and next-to-leading-order theoretical calculations. These include cross-sections as functions of photon kinematic variables, angular variables related to the photon and the leptons, and angular separations between the two leptons in the event. All measurements are in agreement with the predictions from the Standard Model.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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