Detailed breakdown of systematic uncertainties for the measurement in the central rapidity electron channel. Common systematic uncertainty on the luminosity measurment of 1.8% is not included. Correlated systematic uncertainties with the suffix :A should be treated as additive and with the suffix :M should be treated as multiplicative. The source 'sys,uncor' represents bin-to-bin uncorrelated systematic uncertainty. The cross sections are given at the Born QED level. 'C Dressed' represents the multiplicative correction factor to translate the cross sections to the dressed level with the cone radius of 0.1: SigmaDressed = C Dressed * SigmaBorn.

Detailed breakdown of systematic uncertainties for the measurement in the central rapidity electron channel. Common systematic uncertainty on the luminosity measurment of 1.8% is not included. Correlated systematic uncertainties with the suffix :A should be treated as additive and with the suffix :M should be treated as multiplicative. The source 'sys,uncor' represents bin-to-bin uncorrelated systematic uncertainty. The cross sections are given at the Born QED level. 'C Dressed' represents the multiplicative correction factor to translate the cross sections to the dressed level with the cone radius of 0.1: SigmaDressed = C Dressed * SigmaBorn.

Detailed breakdown of systematic uncertainties for the measurement in the central rapidity electron channel. Common systematic uncertainty on the luminosity measurment of 1.8% is not included. Correlated systematic uncertainties with the suffix :A should be treated as additive and with the suffix :M should be treated as multiplicative. The source 'sys,uncor' represents bin-to-bin uncorrelated systematic uncertainty. The cross sections are given at the Born QED level. 'C Dressed' represents the multiplicative correction factor to translate the cross sections to the dressed level with the cone radius of 0.1: SigmaDressed = C Dressed * SigmaBorn.

Detailed breakdown of systematic uncertainties for the measurement in the forward rapidity electron channel. Common systematic uncertainty on the luminosity measurment of 1.8% is not included. Correlated systematic uncertainties with the suffix :A should be treated as additive and with the suffix :M should be treated as multiplicative. The source 'sys,uncor' represents bin-to-bin uncorrelated systematic uncertainty. The cross sections are given at the Born QED level. 'C Dressed' represents the multiplicative correction factor to translate the cross sections to the dressed level with the cone radius of 0.1: SigmaDressed = C Dressed * SigmaBorn.

Detailed breakdown of systematic uncertainties for the measurement in the forward rapidity electron channel. Common systematic uncertainty on the luminosity measurment of 1.8% is not included. Correlated systematic uncertainties with the suffix :A should be treated as additive and with the suffix :M should be treated as multiplicative. The source 'sys,uncor' represents bin-to-bin uncorrelated systematic uncertainty. The cross sections are given at the Born QED level. 'C Dressed' represents the multiplicative correction factor to translate the cross sections to the dressed level with the cone radius of 0.1: SigmaDressed = C Dressed * SigmaBorn.

Detailed breakdown of systematic uncertainties for the measurement in the forward rapidity electron channel. Common systematic uncertainty on the luminosity measurment of 1.8% is not included. Correlated systematic uncertainties with the suffix :A should be treated as additive and with the suffix :M should be treated as multiplicative. The source 'sys,uncor' represents bin-to-bin uncorrelated systematic uncertainty. The cross sections are given at the Born QED level. 'C Dressed' represents the multiplicative correction factor to translate the cross sections to the dressed level with the cone radius of 0.1: SigmaDressed = C Dressed * SigmaBorn.

Detailed breakdown of systematic uncertainties for the combined measurement of muon, electron central and electron central-forward channels. Common systematic uncertainty on the luminosity measurment of 1.8% is not included. The source 'sys,uncor' represents bin-to-bin uncorrelated systematic uncertainty. The cross sections are given at the Born QED level.

Detailed breakdown of systematic uncertainties for the combined measurement of muon, electron central and electron central-forward channels. Common systematic uncertainty on the luminosity measurment of 1.8% is not included. The source 'sys,uncor' represents bin-to-bin uncorrelated systematic uncertainty. The cross sections are given at the Born QED level.

Detailed breakdown of systematic uncertainties for the combined measurement of muon, electron central and electron central-forward channels. Common systematic uncertainty on the luminosity measurment of 1.8% is not included. The source 'sys,uncor' represents bin-to-bin uncorrelated systematic uncertainty. The cross sections are given at the Born QED level.

Detailed breakdown of systematic uncertainties for the combined measurement, integerated in cos theta_CS (differential in y, Mll) Common systematic uncertainty on the luminosity measurment of 1.8% is not included. The source 'sys,uncor' represents bin-to-bin uncorrelated systematic uncertainty. The cross sections are given at the Born QED level.

Detailed breakdown of systematic uncertainties for the combined measurement, integerated in cos theta_CS (differential in y, Mll) Common systematic uncertainty on the luminosity measurment of 1.8% is not included. The source 'sys,uncor' represents bin-to-bin uncorrelated systematic uncertainty. The cross sections are given at the Born QED level.

Detailed breakdown of systematic uncertainties for the combined measurement, integerated in cos theta_CS (differential in y, Mll) Common systematic uncertainty on the luminosity measurment of 1.8% is not included. The source 'sys,uncor' represents bin-to-bin uncorrelated systematic uncertainty. The cross sections are given at the Born QED level.

Detailed breakdown of systematic uncertainties for the combined measurement, integerated in cos theta_CS and y (differential in Mll) Common systematic uncertainty on the luminosity measurment of 1.8% is not included. The source 'sys,uncor' represents bin-to-bin uncorrelated systematic uncertainty. The cross sections are given at the Born QED level.

Detailed breakdown of systematic uncertainties for the combined measurement, integerated in cos theta_CS and y (differential in Mll) Common systematic uncertainty on the luminosity measurment of 1.8% is not included. The source 'sys,uncor' represents bin-to-bin uncorrelated systematic uncertainty. The cross sections are given at the Born QED level.

Detailed breakdown of systematic uncertainties for the combined measurement, integerated in cos theta_CS and y (differential in Mll) Common systematic uncertainty on the luminosity measurment of 1.8% is not included. The source 'sys,uncor' represents bin-to-bin uncorrelated systematic uncertainty. The cross sections are given at the Born QED level.

Powheg based prediction for AFB in the central-central fiducial phase space, as reported in Fig 16 of the paper. Powheg prediction is corrected to NNLO QCD and NLO EWK, as described in the paper. PDF uncertainties are computed using CT10 PDF set scaled to 68%.

Powheg based prediction for AFB in the central-fiducial fiducial phase space, as reported in Fig 17 of the paper. Powheg prediction is corrected to NNLO QCD and NLO EWK, as described in the paper. PDF uncertainties are computed using CT10 PDF set scaled to 68%.

The best-fit expected and observed distributions of the combined NN output in the VRSS for the $e\tau$ channel for events with 3-prong $\tau_\text{had-vis}$ candidates. The last bin in each plot includes overflow events.

The best-fit expected and observed distributions of the combined NN output in the SR for the $e\tau$ channel for events with 1-prong $\tau_\text{had-vis}$ candidates. The last bin in each plot includes overflow events.

The best-fit expected and observed distributions of the combined NN output in the SR for the $e\tau$ channel for events with 3-prong $\tau_\text{had-vis}$ candidates. The last bin in each plot includes overflow events.

The best-fit expected and observed distributions of the combined NN output in the SR for the $\mu\tau$ channel for events with 1-prong $\tau_\text{had-vis}$ candidates. The last bin in each plot includes overflow events.

The best-fit expected and observed distributions of the combined NN output in the SR for the $\mu\tau$ channel for events with 3-prong $\tau_\text{had-vis}$ candidates. The last bin in each plot includes overflow events.

Observed and expected upper limits on $\mathcal{B}(Z\rightarrow\ell\tau)$ at 95% confidence level.

The ratios (μ) of the 95% C.L. upper limits on the combined s→ W^±W^∓ and s→ ZZ cross section to simplified model expectations for the m_Z'=1 TeV scenario, for various m_s hypotheses. The observed limits (solid line) are consistent with the expectation under the SM-only hypothesis (dashed line) within uncertainties (filled band), except for a small excess for m_s=160 GeV, discussed in the text.

The ratios (μ) of the 95% C.L. upper limits on the combined s→ W^±W^∓ and s→ ZZ cross section to simplified model expectations for the m_Z'=1.7 TeV scenario, for various m_s hypotheses. The observed limits (solid line) are consistent with the expectation under the SM-only hypothesis (dashed line) within uncertainties (filled band), except for a small excess for m_s=160 GeV, discussed in the text.

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

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

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

SM background post-fit yields stacked in each SR and CR category and E_T^miss bin and data overlaid with the maximum likelihood estimators set to the conditional values of the combined signal and control region fit. The hatched uncertainty band shown includes simulation statistics uncertainties, experimental systematic uncertainties, and V+jets theory modelling systematic uncertainties. Pre-fit uncertainties cover differences between the data and pre-fit background prediction.

Cumulative efficiencies for the merged category for signal samples with m_s=160 GeV (a), m_s=235 GeV (b) and m_s=310 GeV (c), each with m_Z'=1 TeV. The dark Higgs candidate selection includes stringent jet substructure requirements and typically at most one candidate is present in signal events. Here, Δ φ_{jets_1,2,3 E_T^miss} is the smallest azimuthal angle between the E_T^miss and any of the three highest-p_T (leading) small-R jets.

Cumulative efficiencies for the intermediate category for signal samples with m_s=160 GeV (a), m_s=235 GeV (b) and m_s=310 GeV (c), each with m_Z'=1 TeV. The TAR+Comb algorithm reconstructs the dark Higgs candidate from a TAR jet with m^TAR>60 GeV that is supplemented by up to two additional small-R jets within ΔR_cone=2.5 of the TAR jet. Here, Δ φ_{jets_1,2,3 E_T^miss} is the smallest azimuthal angle between the E_T^miss and any of the three highest-p_T (leading) small-R jets. For details see text.

The product of acceptance and efficiency (A × ϵ), defined as the number of signal events satisfying the full set of selection criteria in the merged or intermediate signal regions, divided by the total number of generated signal events, for the s(W^±W^∓) dark Higgs signal points with dark Higgs boson mass m_s and Z' boson mass m_Z'.

The product of acceptance and efficiency (A × ϵ), defined as the number of signal events satisfying the full set of selection criteria in the merged or intermediate signal regions, divided by the total number of generated signal events, for the s(ZZ) dark Higgs signal points with dark Higgs boson mass m_s and Z' boson mass m_Z'.

Summary of the 95% C.L. upper limits on $\sigma_{ZH} BR(H\rightarrow aa \rightarrow (b\bar{b})(b\bar{b}))$ for the dilepton channel in the resolved analysis. The observed limits are shown, together with the expected limits (dotted black lines). In the case of the expected limits, one- and two-standard-deviation uncertainty bands are also displayed. The data was published in JHEP 10 (2018) 031.

Efficiency and acceptance for simulated $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ samples in two signal regions (SR) of the analysis, one with two $a\to b\bar{b}$ candidates in the High Purity Category (HPC), and the other with one $a\to b\bar{b}$ candidate in the High Purity Category (HPC) and one in the Low Purity Category (LPC).

Efficiency and acceptance for simulated $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ samples in two signal regions (SR) of the analysis, one with two $a\to b\bar{b}$ candidates in the High Purity Category (HPC), and the other with one $a\to b\bar{b}$ candidate in the High Purity Category (HPC) and one in the Low Purity Category (LPC).

Event yields for a simulated $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ sample with $m_a = 17.5\,\text{GeV}$. The signal sample is produced with cross section equals to the standard model $pp\to ZH$, i.e. $0.88\,\text{pb}$. Cut 0 corresponds to the initial number of events. Cut 1 requires the single lepton trigger. Cut 2 requires 2 identified leptons. Cut 3 requires the Z-boson mass window. Cut 4 requires 2 reconstructed $a\to b\bar{b}$ candidates. Cut 5a requires 2 identified $a\to b\bar{b}$ candidates in the 1HPC1LPC region. Cut 6a requires the 2 $a\to b\bar{b}$ candidates in the 1HPC1LPC region to be inside the Higgs mass window. Cut 5b requires 2 identified $a\to b\bar{b}$ candidates in the 2HPC region. Cut 6b requires the 2 $a\to b\bar{b}$ candidates in the 2HPC region to be inside the Higgs mass window.

Event yields for a simulated $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ sample with $m_a = 17.5\,\text{GeV}$. The signal sample is produced with cross section equals to the standard model $pp\to ZH$, i.e. $0.88\,\text{pb}$. Cut 0 corresponds to the initial number of events. Cut 1 requires the single lepton trigger. Cut 2 requires 2 identified leptons. Cut 3 requires the Z-boson mass window. Cut 4 requires 2 reconstructed $a\to b\bar{b}$ candidates. Cut 5a requires 2 identified $a\to b\bar{b}$ candidates in the 1HPC1LPC region. Cut 6a requires the 2 $a\to b\bar{b}$ candidates in the 1HPC1LPC region to be inside the Higgs mass window. Cut 5b requires 2 identified $a\to b\bar{b}$ candidates in the 2HPC region. Cut 6b requires the 2 $a\to b\bar{b}$ candidates in the 2HPC region to be inside the Higgs mass window.

Background yield table for Z+jets, $t\bar{t}$, and rare sources. Observed data yield. Signal $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ yield with $m_a = 20\,\text{GeV}$. The signal sample is produced with cross section equals to the standard model $pp\to ZH$, i.e. $0.88\,\text{pb}$, with a branching ratio set to 1 for the $H \rightarrow aa$ decay, whereas the ATLAS figure attached to this entry instead uses the upper-limit branching ratio (smaller than 1). The table includes the yields in two signal regions with leptons consistent with an on-shell Z-boson decay, one with 2 $a\to b\bar{b}$ candidates in the 2HPC region and one with 2 $a\to b\bar{b}$ candidates in the 1HPC1LPC region. The table also includes the yields in four control regions, one with leptons consistent with an on-shell Z-boson decay and 2 $a\to b\bar{b}$ candidates in the Low Purity Category (LPC), and three others where the leptons are not consistent an on-shell Z-boson decay.

Background yield table for Z+jets, $t\bar{t}$, and rare sources. Observed data yield. Signal $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ yield with $m_a = 20\,\text{GeV}$. The signal sample is produced with cross section equals to the standard model $pp\to ZH$, i.e. $0.88\,\text{pb}$. The table includes the yields in two signal regions with leptons consistent with an on-shell Z-boson decay, one with 2 $a\to b\bar{b}$ candidates in the 2HPC region and one with 2 $a\to b\bar{b}$ candidates in the 1HPC1LPC region. The table also includes the yields in four control regions, one with leptons consistent with an on-shell Z-boson decay and 2 $a\to b\bar{b}$ candidates in the Low Purity Category (LPC), and three others where the leptons are not consistent an on-shell Z-boson decay.

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

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

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

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

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

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

Data from FigAux 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).

Post-fit $m_\text{T}(\gamma, E_\text{T}^\text{miss})$ distribution in the inclusive signal region for the dark-photon search with the 125 GeV mass $\mathcal{B}(H \to \gamma \gamma_\text{d})$ signal normalization set to zero. A $H \to \gamma \gamma_\text{d}$ decay signal is shown for two different mass hypotheses, 125 GeV and 500 GeV, and scaled to a $\mathcal{B}(H \to \gamma \gamma_\text{d})$ of 2% and 1%, respectively. Events with $m_\text{T}(\gamma, E_\text{T}^\text{miss})$ larger than the rightmost bin boundary are added to that bin.

The 95% CL upper limit on the Higgs boson production cross-section times branching ratio to $\gamma \gamma_\text{d}$ is shown for different VBF-produced scalar-mediator-mass hypotheses in the NWA. The theoretically predicted cross-section of a Higgs boson produced via VBF and with the $\mathcal{B}(H \to \gamma \gamma_\text{d}) =$ 5% is superimposed on the $\pm 1\sigma$ and $\pm 2\sigma$ NNLO QCD + NLO EW uncertainty band of the expected production cross-section limit.

Post-fit $m_\text{jj}$ distribution in the inclusive signal region. The Higgs boson invisible decay signal is scaled to a $\mathcal{B}_\text{inv}$ of 37%. Events with $m_\text{jj}$ larger than the rightmost bin boundary are added to that bin.

Post-fit $m_\text{jj}$ distribution in the one-lepton control region $W_{\ell \nu}^\gamma$ CR. Events with $m_\text{jj}$ larger than the rightmost bin boundary are added to that bin.

Post-fit $m_\text{T}$ distribution in the one lepton control region. Events with $m_\text{T}$ larger than the rightmost bin boundary are added to that bin.

Post-fit photon centrality distribution in the zero lepton signal plus control region with the $\mathcal{B}_\text{inv}$ signal normalization set to zero in the fit.

Post-fit photon $E_\text{T}$ distribution in the zero lepton signal region with the $\mathcal{B}_\text{inv}$ signal normalization set to zero in the fit.

Post-fit photon centrality distribution in the zero lepton signal plus control region resulting from the fit to the $m_\text{jj}$ distribution for EW $Z \gamma + \text{jets}$. The post-fit uncertainties include statistical, experimental, and theory contributions.

Post-fit photon $E_\text{T}$ distribution in the zero lepton signal region resulting from the fit to the $m_\text{jj}$ distribution for EW $Z \gamma + \text{jets}$. The post-fit uncertainties include statistical, experimental, and theory contributions.

Post-fit DNN output score distribution in the one lepton control region.

Yields for the EW $Z \gamma + \text{jets}$ process are shown after each selection along with relative and absolute signal acceptance efficiencies.

Yields for the 125 GeV Higgs boson with $\mathcal{B}_\text{inv.} =$ 1 signal produced by the vector boson fusion process in association with a final state photon are shown after each selection along with relative and absolute signal acceptance efficiencies.

Yields for the 125 GeV Higgs boson with $\mathcal{B}(H \to \gamma \gamma_\text{d}) =$ 1 signal produced by the vector boson fusion process are shown after each selection along with relative and absolute signal acceptance efficiencies.

Upper limits on $\mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ at 95% CL including the BDT cut as a function of the signal mass.

Upper limits on $\mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ at 95% CL without the BDT cut as a function of the signal mass.

The number of events when applying each cut in the analysis for $m_a$ = 16 GeV. The first row shows the approximate total number of events scaled to the theoretical signal cross-section and luminosity of the full Run 2 dataset, assuming $ \mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ = 0.16%.

The number of events when applying each cut in the analysis for $m_a$ = 20 GeV. The first row shows the approximate total number of events scaled to the theoretical signal cross-section and luminosity of the full Run 2 dataset, assuming $ \mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ = 0.16%.

The number of events when applying each cut in the analysis for $m_a$ = 30 GeV. The first row shows the approximate total number of events scaled to the theoretical signal cross-section and luminosity of the full Run 2 dataset, assuming $ \mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ = 0.16%.

The number of events when applying each cut in the analysis for $m_a$ = 40 GeV. The first row shows the approximate total number of events scaled to the theoretical signal cross-section and luminosity of the full Run 2 dataset, assuming $ \mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ = 0.16%.

The number of events when applying each cut in the analysis for $m_a$ = 50 GeV. The first row shows the approximate total number of events scaled to the theoretical signal cross-section and luminosity of the full Run 2 dataset, assuming $ \mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ = 0.16%.

The number of events when applying each cut in the analysis for $m_a$ = 60 GeV. The first row shows the approximate total number of events scaled to the theoretical signal cross-section and luminosity of the full Run 2 dataset, assuming $ \mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ = 0.16%.

Vertex selection efficiency for the $\tilde{t}$ $R$-hadron benchmark model as a function of the transverse decay distance $r_{DV}$.

Track multiplicity $n_{Tracks}$ for preselected DVs in MET-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.

Track multiplicity $n_{Tracks}$ for preselected DVs in MET-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.

Track multiplicity $n_{Tracks}$ for preselected DVs in muon-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.

Track multiplicity $n_{Tracks}$ for preselected DVs in muon-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.

Invariant mass $m_{DV}$ for the highest-mass preselected DV with at least three associated tracks in MET-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.

Invariant mass $m_{DV}$ for the highest-mass preselected DV with at least three associated tracks in MET-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.

Invariant mass $m_{DV}$ for the highest-mass preselected DV with at least three associated tracks in muon-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.

Invariant mass $m_{DV}$ for the highest-mass preselected DV with at least three associated tracks in muon-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.

The observed event yields in the control, validation and signal regions are shown for the MET Trigger selections, along with the predicted background yields. The bottom panel shows the ratio of observed events to the total background yields. The errors represent the total uncertainty of the backgrounds prediction, including the statistical and systematic uncertainties added in quadrature.

The observed event yields in the control, validation and signal regions are shown for the MET Trigger selections, along with the predicted background yields. The bottom panel shows the ratio of observed events to the total background yields. The errors represent the total uncertainty of the backgrounds prediction, including the statistical and systematic uncertainties added in quadrature.

The observed event yields in the control, validation and signal regions are shown for the Muon Trigger selections, along with the predicted background yields. The bottom panel shows the ratio of observed events to the total background yields. The errors represent the total uncertainty of the backgrounds prediction, including the statistical and systematic uncertainties added in quadrature.

The observed event yields in the control, validation and signal regions are shown for the Muon Trigger selections, along with the predicted background yields. The bottom panel shows the ratio of observed events to the total background yields. The errors represent the total uncertainty of the backgrounds prediction, including the statistical and systematic uncertainties added in quadrature.

Expected exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.

Expected exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.

Expected (1 sigma band) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.

Expected (1 sigma band) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.

Expected (2 sigma band) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.

Expected (2 sigma band) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.

Observed exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.

Observed exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.

Observed (+1 sigma) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.

Observed (+1 sigma) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.

Observed (-1 sigma) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.

Observed (-1 sigma) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.

Exclusion limits on the production cross section as a function of m($\tilde{t}$) are shown for several values of $\tau(\tilde{t})$ along with the nominal signal production cross section and its theoretical uncertainty.

Exclusion limits on the production cross section as a function of m($\tilde{t}$) are shown for several values of $\tau(\tilde{t})$ along with the nominal signal production cross section and its theoretical uncertainty.

Parameterized event selection efficiencies for the $E_{T}^{miss}$ Trigger SR. The event-level efficiencies for each SR are extracted for all events passing the acceptance of the corresponding SR.

Parameterized event selection efficiencies for the $E_{T}^{miss}$ Trigger SR. The event-level efficiencies for each SR are extracted for all events passing the acceptance of the corresponding SR.

Parameterized event selection efficiencies for the Muon Trigger SR. The event-level efficiencies for each SR are extracted for all events passing the acceptance of the corresponding SR.

Parameterized event selection efficiencies for the Muon Trigger SR. The event-level efficiencies for each SR are extracted for all events passing the acceptance of the corresponding SR.

Parameterized muon-level reconstruction efficiencies as a function of the muon $p_{T}$ and $d_{0}$. The muon-level efficiencies are extracted using muons passing the muon acceptance criteria.

Parameterized muon-level reconstruction efficiencies as a function of the muon $p_{T}$ and $d_{0}$. The muon-level efficiencies are extracted using muons passing the muon acceptance criteria.

Parameterized vertex-level reconstruction efficiencies as a function of the radial position of the truth vertex. The efficiency is calculated independent of the muons originating from this truth vertex.

Parameterized vertex-level reconstruction efficiencies as a function of the radial position of the truth vertex. The efficiency is calculated independent of the muons originating from this truth vertex.

Parameterized vertex-level reconstruction efficiencies as a function of the radial position of the truth vertex. The efficiency is calculated only for truth vertices which have a muon originating from them which is matched to a reconstructed muon.

Parameterized vertex-level reconstruction efficiencies as a function of the radial position of the truth vertex. The efficiency is calculated only for truth vertices which have a muon originating from them which is matched to a reconstructed muon.

The $p_{T}$ distribution of all muons originating from LLP decays in the samples used to calculate and validate the efficiencies.

The $p_{T}$ distribution of all muons originating from LLP decays in the samples used to calculate and validate the efficiencies.

The invariant mass and multiplicity of selected decay products of all truth vertices used in the calculation and validation of the reconstructed efficiencies.

The invariant mass and multiplicity of selected decay products of all truth vertices used in the calculation and validation of the reconstructed efficiencies.

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

Differential cross section as a function of $m_{\gamma\gamma}$. The table contains the values measured in data and theory predictions from SHERPA, DIPHOX and NNLOJET.

Differential cross section as a function of $p_{T,\gamma\gamma}$. The table contains the values measured in data and theory predictions from SHERPA, DIPHOX and NNLOJET.

Differential cross section as a function of $a_{T,\gamma\gamma}$. The table contains the values measured in data and theory predictions from SHERPA, DIPHOX and NNLOJET.

Differential cross section as a function of $\phi_{\eta}*$. The table contains the values measured in data and theory predictions from SHERPA, DIPHOX and NNLOJET.

Differential cross section as a function of $\pi-\Delta\phi_{\gamma\gamma}$. The table contains the values measured in data and theory predictions from SHERPA, DIPHOX and NNLOJET.

Differential cross section as a function of $|cos\theta*|^{(CS)}$. The table contains the values measured in data and theory predictions from SHERPA, DIPHOX and NNLOJET.

The contribution from different systematic uncertainties to the measured $t\bar{t}t\bar{t}$ production cross section, grouped in categories.

The results of the fitted signal strength $\mu$ in the 1L/2LOS and 2LSS/3L combined channel.

The results of fitted inclusive ${t\bar{t}t\bar{t}}$ cross-section in the 1L/2LOS and 2LSS/3L combined channel.

Comparison between data and prediction for the distribution of the sum of the pseudo-continuous b-tagging score over the six jets with the highest score in the 1L,$\geq$9j,$\geq$3b region before the fit.

Comparison between data and prediction for the distribution of the sum of the pseudo-continuous b-tagging score over the six jets with the highest score in the 1L,$\geq$9j,$\geq$3b region after the fit.

Comparison between data and prediction for the distribution of the sum of the pseudo-continuous b-tagging score over the six jets with the highest score in the 2LOS,$\geq$7j,$\geq$3b region before the fit.

Comparison between data and prediction for the distribution of the sum of the pseudo-continuous b-tagging score over the six jets with the highest score in the 2LOS,$\geq$7j,$\geq$3b region after the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,$\geq$8j,$\geq$3b region before the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,$\geq$8j,$\geq$3b region after the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 2LOS,$\geq$6j,$\geq$3b region before the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 2LOS,$\geq$6j,$\geq$3b region after the fit.

Comparison between data and prediction for the distribution of number of jets in the 1L,$\geq$8j,$\geq$3b region before the fit.

Comparison between data and prediction for the distribution of number of jets in the 1L,$\geq$8j,$\geq$3b region after the fit.

Comparison between data and prediction for the distribution of number of jets in the 2LOS,$\geq$6j,$\geq$3b region before the fit.

Comparison between data and prediction for the distribution of number of jets in the 2LOS,$\geq$6j,$\geq$3b region after the fit.

Comparison between data and prediction for the distribution of b-jets multiplicity in the 1L,$\geq$8j,$\geq$3b region before the fit.

Comparison between data and prediction for the distribution of b-jets multiplicity in the 1L,$\geq$8j,$\geq$3b region after the fit.

Comparison between data and prediction for the distribution of b-jets multiplicity in the 2LOS,$\geq$6j,$\geq$3b region before the fit.

Comparison between data and prediction for the distribution of b-jets multiplicity in the 2LOS,$\geq$6j,$\geq$3b region after the fit.

Comparison between data and prediction for the distribution of the BDT score in the 1L,9j,4b signal region before the fit.

Comparison between data and prediction for the distribution of the BDT score in the 1L,9j,4b signal region after the fit.

Comparison between data and prediction for the distribution of the BDT score in the 1L,9j,$\geq$5b signal region before the fit.

Comparison between data and prediction for the distribution of the BDT score in the 1L,9j,$\geq$5b signal region after the fit.

Comparison between data and prediction for the distribution of the BDT score in the 1L,$\geq$10j,3bL signal region before the fit.

Comparison between data and prediction for the distribution of the BDT score in the 1L,$\geq$10j,3bL signal region after the fit.

Comparison between data and prediction for the distribution of the BDT score in the 1L,$\geq$10j,3bH signal region before the fit.

Comparison between data and prediction for the distribution of the BDT score in the 1L,$\geq$10j,3bH signal region after the fit.

Comparison between data and prediction for the distribution of the BDT score in the 1L,$\geq$10j,4b signal region before the fit.

Comparison between data and prediction for the distribution of the BDT score in the 1L,$\geq$10j,4b signal region after the fit.

Comparison between data and prediction for the distribution of the BDT score in the 1L,$\geq$10j,$\geq$5b signal region before the fit.

Comparison between data and prediction for the distribution of the BDT score in the 1L,$\geq$10j,$\geq$5b signal region after the fit.

Comparison between data and prediction for the distribution of the BDT score in the 2LOS,7j,$\geq$4b signal region before the fit.

Comparison between data and prediction for the distribution of the BDT score in the 2LOS,7j,$\geq$4b signal region after the fit.

Comparison between data and prediction for the distribution of the BDT score in the 2LOS,$\geq$8j,3bL signal region before the fit.

Comparison between data and prediction for the distribution of the BDT score in the 2LOS,$\geq$8j,3bL signal region after the fit.

Comparison between data and prediction for the distribution of the BDT score in the 2LOS,$\geq$8j,3bH signal region before the fit.

Comparison between data and prediction for the distribution of the BDT score in the 2LOS,$\geq$8j,3bH signal region after the fit.

Comparison between data and prediction for the distribution of the BDT score in the 2LOS,$\geq$8j,$\geq$4b signal region before the fit.

Comparison between data and prediction for the distribution of the BDT score in the 2LOS,$\geq$8j,$\geq$4b signal region after the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,8j,3bV validation region before the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,8j,3bV validation region after the fit.

Comparison between data and prediction for the distribution of the BDT score in the 1L,9j,3bV validation region before the fit.

Comparison between data and prediction for the distribution of the BDT score in the 1L,9j,3bV validation region after the fit.

Comparison between data and prediction for the distribution of the BDT score in the 1L,$\geq$10j,3bV validation region before the fit.

Comparison between data and prediction for the distribution of the BDT score in the 1L,$\geq$10j,3bV validation region after the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 2LOS,6j,3bV validation region before the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 2LOS,6j,3bV validation region after the fit.

Comparison between data and prediction for the distribution of the BDT score in the 2LOS,7j,3bV validation region before the fit.

Comparison between data and prediction for the distribution of the BDT score in the 2LOS,7j,3bV validation region after the fit.

Comparison between data and prediction for the distribution of the BDT score in the 2LOS,$\geq$8j,3bV validation region before the fit.

Comparison between data and prediction for the distribution of the BDT score in the 2LOS,$\geq$8j,3bV validation region after the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,8j,3bL control region before the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,8j,3bL control region after the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,8j,3bH control region before the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,8j,3bH control region after the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,9j,3bL control region before the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,9j,3bL control region after the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,9j,3bH control region before the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,9j,3bH control region after the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,8j,4b control region before the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,8j,4b control region after the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,8j,$\geq$5b control region before the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 1L,8j,$\geq$5b control region after the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 2LOS,6j,3bL control region before the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 2LOS,6j,3bL control region after the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 2LOS,6j,3bH control region before the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 2LOS,6j,3bH control region after the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 2LOS,7j,3bL control region before the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 2LOS,7j,3bL control region after the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 2LOS,7j,3bH control region before the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 2LOS,7j,3bH control region after the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 2LOS,6j,$\geq$4b control region before the fit.

Comparison between data and prediction for the distribution of the scalar sum of all jet and lepton pT in the event in the 2LOS,6j,$\geq$4b control region after the fit.

Non-prompt fraction of jpsi production in 5.02 TeV PbPb collision data as a function of pT for integrated centrality in the rapidity range |y| < 2.

The nuclear modification factor as a function of pT for the prompt jpsi for |y|<2, in 0--80% centrality bin.

The nuclear modification factor as a function of pT for the prompt jpsi for |y|<2, in 0--10%, 20--40%, and 40--80% centrality bin.

The nuclear modification factor as a function of pT for the non-prompt jpsi for |y|<2, in 0--80% centrality bin.

The nuclear modification factor as a function of pT for the non-prompt jpsi for |y|<2, in 0--10%, 20--40%, and 40--80% centrality bin.

The nuclear modification factor as a function of pT for the prompt and non-prompt jpsi for |y|<2, in 0--20% centrality bin.

The nuclear modification factor as a function of eta for the prompt jpsi for 9 < pT < 40 GeV, in 0--80% centrality bin.

The nuclear modification factor as a function of eta for the prompt jpsi for 9 < pT < 40 GeV, in 0--10%, 20--40%, and 40--80% centrality bin.

The nuclear modification factor as a function of eta for the non-prompt jpsi for 9 < pT < 40 GeV, in 0--80% centrality bin.

The nuclear modification factor as a function of eta for the non-prompt jpsi for 9 < pT < 40 GeV, in 0--10%, 20--40%, and 40--80% centrality bin.

The nuclear modification factor as a function of Npart for the prompt jpsi for |y|<2, and 9 < pT < 40 GeV

The nuclear modification factor as a function of Npart for the non-prompt jpsi for |y|<2, and 9 < pT < 40 GeV

The double ratio of nuclear modification factor as a function of Npart for the prompt jpsi and psi(2S) for |y|<2, and 9 < pT < 40 GeV

The double ratio nuclear modification factor as a function of Npart for the non-prompt jpsi and psi(2S) for |y|<2, and 9 < pT < 40 GeV

Limit Plot

Limit Plot

Limit Plot

Limit Plot

Limit Plot

Limit Plot

Limit Plot

Limit Plot

Limit Plot

HVT WW Acceptance times Efficiency

HVT WW Acceptance times Efficiency

HVT WZ Acceptance times Efficiency

HVT WZ Acceptance times Efficiency

RS Graviton WW Acceptance times Efficiency

RS Graviton WW Acceptance times Efficiency

RS Graviton ZZ Acceptance times Efficiency

RS Graviton ZZ Acceptance times Efficiency

The observed exclusion contour at 95% CL as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$. Masses that are within the contours are excluded.

The expected exclusion contour at 95% CL as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$. Masses that are within the contour are excluded.

The expected exclusion contour at 95% CL as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$. Masses that are within the contour are excluded.

The minus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.

The minus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.

The plus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.

The plus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.

The minus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.

The minus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.

The plus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.

The plus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.

The observed exclusion contour at 95% CL as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$. Points that are within the contours are excluded.

The observed exclusion contour at 95% CL as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$. Points that are within the contours are excluded.

The expected exclusion contour at 95% CL as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$. Points that are within the contours are excluded.

The expected exclusion contour at 95% CL as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$. Points that are within the contours are excluded.

The minus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$

The minus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$

The plus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$

The plus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$

The plus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$

The plus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$

The minus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$

The minus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$

Model dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{0}_{1})$ signal grid. The column titled 'Leading Region' stores information on which of the fit regions (SRA-B, SRC or SRD) is the dominant based on the expected CLs values.

Model dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{0}_{1})$ signal grid. The column titled 'Leading Region' stores information on which of the fit regions (SRA-B, SRC or SRD) is the dominant based on the expected CLs values.

Expected model dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{0}_{1})$ signal grid. The column titled 'Leading Region' stores information on which of the fit regions (SRA-B, SRC or SRD) is the dominant based on the expected CLs values.

Expected model dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{0}_{1})$ signal grid. The column titled 'Leading Region' stores information on which of the fit regions (SRA-B, SRC or SRD) is the dominant based on the expected CLs values.

Model dependent upper limit on the cross section for the $LQ_{3}^{u}$ signal grid with $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau))=0$ %. Only the SRA-B fit region is considered in this interpretation.

Model dependent upper limit on the cross section for the $LQ_{3}^{u}$ signal grid with $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau))=0$ %. Only the SRA-B fit region is considered in this interpretation.

Expected model dependent upper limit on the cross section for the $LQ_{3}^{u}$ signal grid with $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau))=0$ %. Only the SRA-B fit region is considered in this interpretation.

Expected model dependent upper limit on the cross section for the $LQ_{3}^{u}$ signal grid with $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau))=0$ %. Only the SRA-B fit region is considered in this interpretation.

The distributions of $S$ in SRA-TW. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.

The distributions of $S$ in SRA-TW. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.

The distributions of $\it{m}^{\mathrm{R=1.2}}_{1}$ in SRB-TT. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.

The distributions of $\it{m}^{\mathrm{R=1.2}}_{1}$ in SRB-TT. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.

The distributions of R$_{ISR}$ in SRC signal regions before R$_{ISR}$ cuts are applied. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.

The distributions of R$_{ISR}$ in SRC signal regions before R$_{ISR}$ cuts are applied. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.

The distributions of $E^{miss}_{T}/\sqrt{H_{T}}$ in SRD0. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.

The distributions of $E^{miss}_{T}/\sqrt{H_{T}}$ in SRD0. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.

The distributions of $E^{miss}_{T}/\sqrt{H_{T}}$ in SRD1. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.

The distributions of $E^{miss}_{T}/\sqrt{H_{T}}$ in SRD1. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.

The distributions of $E^{miss}_{T}/\sqrt{H_{T}}$ in SRD2. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.

The distributions of $E^{miss}_{T}/\sqrt{H_{T}}$ in SRD2. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (1300,1)\ \mathrm{GeV} $ in SRA-TT. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 30000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (1300,1)\ \mathrm{GeV} $ in SRA-TT. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 30000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (1300,1)\ \mathrm{GeV} $ in SRA-TW. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 30000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (1300,1)\ \mathrm{GeV} $ in SRA-TW. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 30000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (1300,1)\ \mathrm{GeV} $ in SRA-T0. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 30000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (1300,1)\ \mathrm{GeV} $ in SRA-T0. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 30000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (700,400)\ \mathrm{GeV} $ in signal regions SRB-TT, SRB-TW and SRB-T0. The regions differ by the last cut applied. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 60000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (700,400)\ \mathrm{GeV} $ in signal regions SRB-TT, SRB-TW and SRB-T0. The regions differ by the last cut applied. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 60000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (500,327)\ \mathrm{GeV} $ in regions SRC-1, SRC-2, SRC-3, SRC-4 and SRC-5. The regions differ by the last cut applied. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 150000 raw MC events with filter efficiency of 0.384 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (500,327)\ \mathrm{GeV} $ in regions SRC-1, SRC-2, SRC-3, SRC-4 and SRC-5. The regions differ by the last cut applied. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 150000 raw MC events with filter efficiency of 0.384 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (550,500)\ \mathrm{GeV} $ in SRD0. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 90000 raw MC events with filter efficiency of 0.428 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (550,500)\ \mathrm{GeV} $ in SRD0. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 90000 raw MC events with filter efficiency of 0.428 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (550,500)\ \mathrm{GeV} $ in SRD1. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 90000 raw MC events with filter efficiency of 0.428 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (550,500)\ \mathrm{GeV} $ in SRD1. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 90000 raw MC events with filter efficiency of 0.428 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (550,500)\ \mathrm{GeV} $ in SRD2. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 90000 raw MC events with filter efficiency of 0.428 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (550,500)\ \mathrm{GeV} $ in SRD2. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 90000 raw MC events with filter efficiency of 0.428 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Signal acceptance in SRA-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$

Signal acceptance in SRA-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$

Signal efficiency in SRA-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.

Signal efficiency in SRA-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.

Signal acceptance in SRA-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$

Signal acceptance in SRA-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$

Signal efficiency in SRA-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.

Signal efficiency in SRA-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.

Signal acceptance in SRA-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$

Signal acceptance in SRA-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$

Signal efficiency in SRA-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.

Signal efficiency in SRA-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.

Signal acceptance in SRB-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$

Signal acceptance in SRB-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$

Signal efficiency in SRB-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.

Signal efficiency in SRB-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.

Signal acceptance in SRB-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$

Signal acceptance in SRB-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$

Signal efficiency in SRB-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.

Signal efficiency in SRB-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.

Signal acceptance in SRB-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$

Signal acceptance in SRB-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$

Signal efficiency in SRB-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.

Signal efficiency in SRB-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.

Signal acceptance in SRC1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRC1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRC1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRC1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRC2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRC2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRC2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRC2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRC3 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRC3 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRC3 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRC3 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRC4 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRC4 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRC4 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ plane showed in the paper plot.

Signal efficiency in SRC4 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ plane showed in the paper plot.

Signal acceptance in SRC5 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ plane showed in the paper plot.

Signal acceptance in SRC5 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ plane showed in the paper plot.

Signal efficiency in SRC5 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRC5 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRD0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRD0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRD0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRD0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRD1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRD1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRD1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRD1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRD2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRD2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRD2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRD2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Distribution of $m^{vis}_{HH}$ after applying all the event selection that define the $HH$ SR, except the requirement on $m^{vis}_{HH}$. The background labelled as "Others" contains $W$+jets, diboson, $t\bar{t}$ and single-top-quark processes. The $X\rightarrow HH \rightarrow b\bar{b}\tau^{+}\tau^{-}$ signal is overlaid for two resonance mass hypotheses with a cross-section set to the expected limit, while all backgrounds are pre-fit. The first and the last bins contains the under-flow and over-flow bin entries, respectively. The hatched bands represent combined statistical and systematic uncertainties.

Event yields of the various estimated backgrounds and data, computed in the signal region of the search for $X\rightarrow HH \rightarrow b\bar{b}\tau^{+}\tau^{-}$. The background labelled as "Others" contains $W$+jets, diboson, $t\bar{t}$ and single-top-quark processes. Statistical and systematic uncertainties are quoted. The background yields and uncertainties are pre-fit and are found to be similar to those post-fit.

Event yields of the various estimated backgrounds and data, computed in the signal region of the search for $X\rightarrow HH \rightarrow b\bar{b}\tau^{+}\tau^{-}$. The background labelled as "Others" contains $W$+jets, diboson, $t\bar{t}$ and single-top-quark processes. Statistical and systematic uncertainties are quoted. The background yields and uncertainties are pre-fit and are found to be similar to those post-fit.

Expected and observed 95% CL upper limits on the production of a heavy, narrow-width, scalar resonance decaying to a pair of Higgs bosons ($X\rightarrow HH$). The final state used in the search consists of a boosted $b\bar{b}$ pair and a boosted hadronically decaying $\tau^{+}\tau^{-}$ pair, and the SM braching ratio of the Higgs boson are assumed. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit are indicated by the error bands. Two different requirements are applied on the visible mass of the two boosted Higgs boson candidates for the resonance mass hypotheses of 1.6 TeV and 2.5 TeV, leading to discontinuities in the limits (at 1.6 TeV, the difference between imposing no requirement and $m^{vis}_{HH}>900$ GeV is less than 1% though).

Expected and observed 95% CL upper limits on the production of a heavy, narrow-width, scalar resonance decaying to a pair of Higgs bosons ($X\rightarrow HH$). The final state used in the search consists of a boosted $b\bar{b}$ pair and a boosted hadronically decaying $\tau^{+}\tau^{-}$ pair, and the SM braching ratio of the Higgs boson are assumed. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit are indicated by the error bands. Two different requirements are applied on the visible mass of the two boosted Higgs boson candidates for the resonance mass hypotheses of 1.6 TeV and 2.5 TeV, leading to discontinuities in the limits (at 1.6 TeV, the difference between imposing no requirement and $m^{vis}_{HH}>900$ GeV is less than 1% though).

The signal selection acceptance times efficiency (A$\times \epsilon$), defined as the ratio of the number of MC signal events in the category to the number of generated signal events, is presented as a function of the HVT resonance mass in the VBF category. The A$\times \epsilon$ is shown for the combination of all decay channels. For the HVT VBF samples, generator cuts are: m$_{jj} >$ 150 GeV. The decay of $W$ and $Z$ are to all flavors of leptons. The uncertainty shown represents the total statistical and systematic uncertainties.

Signal selection acceptance times efficiency (A$\times \epsilon$), defined as the ratio of the number of MC signal events in the category to the number of generated signal events, as a function of the HVT resonance mass for the quark-antiquark production. The $A\times\epsilon$ is shown for each decay channel and the inclusive one. The decay of $W$ and $Z$ are to all flavors of leptons. The uncertainty shown represents the total statistical and systematic uncertainties.

Signal selection acceptance times efficiency (A$\times \epsilon$), defined as the ratio of the number of MC signal events in the category to the number of generated signal events, as a function of the HVT resonance mass for the quark-antiquark production. The $A\times\epsilon$ is shown for each decay channel and the inclusive one. The decay of $W$ and $Z$ are to all flavors of leptons. The uncertainty shown represents the total statistical and systematic uncertainties.

Observed and expected distributions of the $WZ$ invariant mass in the q$\bar{\mathrm q}$ category after applying all selection cuts. Background contributions are obtained from background-only likelihood fit to the data.

Observed and expected distributions of the $WZ$ invariant mass in the q$\bar{\mathrm q}$ category after applying all selection cuts. Background contributions are obtained from background-only likelihood fit to the data.

Observed and expected distributions of the $WZ$ invariant mass in the $VBF$ category after applying all selection cuts. Background contributions are obtained from background-only likelihood fit to the data.

Observed and expected distributions of the $WZ$ invariant mass in the $VBF$ category after applying all selection cuts. Background contributions are obtained from background-only likelihood fit to the data.

Observed and expected 95% C.L. upper limits on $\sigma\times$BR($W'\to W^\pm Z$) for the q$\bar{\mathrm q}$ production of a $W'$ boson in the HVT model as a function of its mass. The $\pm1\sigma$ and $\pm2\sigma$ uncertainty in the expected limits are given. Limits are calculated in the asymptotic approximation below 900 GeV and are obtained from pseudo-experiments above that.

Observed and expected 95% C.L. upper limits on $\sigma\times$BR($W'\to W^\pm Z$) for the q$\bar{\mathrm q}$ production of a $W'$ boson in the HVT model as a function of its mass. The $\pm1\sigma$ and $\pm2\sigma$ uncertainty in the expected limits are given. Limits are calculated in the asymptotic approximation below 900 GeV and are obtained from pseudo-experiments above that.

Observed and expected 95% C.L. upper limits on $\sigma\times$BR($W'\to W^\pm Z$) for the $VBF$ production of a $W'$ boson in the HVT model as a function of its mass. The $\pm1\sigma$ and $\pm2\sigma$ uncertainty are given in the expected limits. Limits are calculated in the asymptotic approximation below 700 GeV and are obtained from pseudo-experiments above that.

Observed and expected 95% C.L. upper limits on $\sigma\times$BR($W'\to W^\pm Z$) for the $VBF$ production of a $W'$ boson in the HVT model as a function of its mass. The $\pm1\sigma$ and $\pm2\sigma$ uncertainty are given in the expected limits. Limits are calculated in the asymptotic approximation below 700 GeV and are obtained from pseudo-experiments above that.

Observed and expected 95% C.L. upper limits on $\sigma\times$BR($H_5^\pm\to W^\pm Z$) of the Georgi-Machacek Model as a function of $m_{H_5^\pm}$. The $\pm1\sigma$ and $\pm2\sigma$ uncertainty in the expected limits are given. Limits are calculated in the asymptotic approximation below 700 GeV and are obtained from pseudo-experiments above that.

Observed and expected 95% C.L. upper limits on $\sigma\times$BR($H_5^\pm\to W^\pm Z$) of the Georgi-Machacek Model as a function of $m_{H_5^\pm}$. The $\pm1\sigma$ and $\pm2\sigma$ uncertainty in the expected limits are given. Limits are calculated in the asymptotic approximation below 700 GeV and are obtained from pseudo-experiments above that.

Observed and expected 95% C.L. upper limits on the parameter $\sin(\theta_H)$ of the Georgi-Machacek Model as a function of $m_{H_5^\pm}$. The $\pm1\sigma$ and $\pm2\sigma$ uncertainty are given in the expected limits. Limits are calculated in the asymptotic approximation below 700 GeV and are obtained from pseudo-experiments above that.

Observed and expected 95% C.L. upper limits on the parameter $\sin(\theta_H)$ of the Georgi-Machacek Model as a function of $m_{H_5^\pm}$. The $\pm1\sigma$ and $\pm2\sigma$ uncertainty are given in the expected limits. Limits are calculated in the asymptotic approximation below 700 GeV and are obtained from pseudo-experiments above that.

Absolute differential cross-section as a function of $\Delta R^{extra1}_{jet1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $\Delta R^{extra1}_{jet1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $|y^{t,1}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $|y^{t,1}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $|y^{t,1}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $|y^{t,1}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $|y^{t,2}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $|y^{t,2}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $|y^{t,2}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $|y^{t,2}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $|y^{t\bar{t}}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $|y^{t\bar{t}}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $|y^{t\bar{t}}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $|y^{t\bar{t}}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $p_{T}^{t,1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{t,1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $p_{T}^{t,1}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $p_{T}^{t,1}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $p_{T}^{t,2}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{t,2}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $p_{T}^{t,2}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $p_{T}^{t,2}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $p_{T}^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{t\bar{t}}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $p_{T}^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $p_{T}^{t\bar{t}}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $N_{jets}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $N_{jets}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $N_{jets}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $N_{jets}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $\Delta\phi^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $\Delta\phi^{t\bar{t}}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $\Delta\phi^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $\Delta\phi^{t\bar{t}}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $|P_{out}^{t,1}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $|P_{out}^{t,1}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $|P_{out}^{t,1}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $|P_{out}^{t,1}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $|P_{cross}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $|P_{cross}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $|P_{cross}|$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $|P_{cross}|$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Relative differential cross-section as a function of $Z^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $Z^{t\bar{t}}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.

Absolute differential cross-section as a function of $Z^{t\bar{t}}$ at particle level in the all hadronic resolved topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $Z^{t\bar{t}}$ at particle level in the all hadronic resolved topology, accounting for the statistical and systematic uncertainties.