The fiducial cross section measured in bins of the azimuthal angle difference between the mesons for events in the fiducial region with 2 Y(1S) with absolute rapidity less than 2.0.

The expected and observed 95% CL limits on the product of the cross section and branching fraction for a tetraquark. The branching fraction is the product of the branching fraction for the decay of the resonance to a Y(1S) meson and two muons, and the Y(1S) meson dimuon branching fraction.

The expected and observed 95% CL limits on the product of the cross section and branching fraction for a scalar state. The branching fraction is the product of the branching fraction for the decay of the resonance to a Y(1S) meson and two muons, and the Y(1S) meson dimuon branching fraction.

The expected and observed 95% CL limits on the product of the cross section and branching fraction for a pseudoscalar state. The branching fraction is the product of the branching fraction for the decay of the resonance to a Y(1S) meson and two muons, and the Y(1S) meson dimuon branching fraction.

The expected and observed 95% CL limits on the product of the cross section and branching fraction for a spin-2 state. The branching fraction is the product of the branching fraction for the decay of the resonance to a Y(1S) meson and two muons, and the Y(1S) meson dimuon branching fraction.

Kinematic properties and charges of the four muons selected in data in the signal region for the measurement of the YY production cross section. MUON1 and MUON2 form the dimuon pair associated to the dimuon object required at trigger-level. The invariant mass of both muon pairs is between 8.6 and 11 GeV. All events pass the trigger requirements and have four muons with a total charge of 0 and with vertex probability above 5%. The muons have pT above 3.5 GeV if they have an absolute pseudorapidity below 0.9 and 2.5 GeV otherwise. The muons pass the medium muon identification criterion.

Selection acceptance times efficiency for the 1 lepton signal events from MC simulations as a function of the resonance mass for VBF production.

Selection acceptance times efficiency for the 2 leptons signal events from MC simulations as a function of the resonance mass for ggF/DY production.

Selection acceptance times efficiency for the 2 leptons signal events from MC simulations as a function of the resonance mass for VBF production.

The fractions of signal events passing the VBF requirement on the RNN score as functions of the resonance mass for both VBF and ggF production. Information on the RNN model, such as the architecture, network weights and features scaling files are provided as additional resources.

Upper 95% CLs limits on the ggF production cross section of Radions in their $WW+ZZ$ decays as a function of the resonance mass.

Upper 95% CLs limits on the VBF production cross section of Radions in their $WW+ZZ$ decays as a function of the resonance mass.

Upper 95% CLs limits on the DY production cross section of HVT $W'$ in their $WZ$ decays as a function of the resonance mass.

Upper 95% CLs limits on the VBF production cross section of HVT $W'$ in their $WZ$ decays as a function of the resonance mass.

Upper 95% CLs limits on the DY production cross section of HVT $Z'$ in their $WW$ decays as a function of the resonance mass.

Upper 95% CLs limits on the VBF production cross section of HVT $Z'$ in their $WW$ decays as a function of the resonance mass.

Upper 95% CLs limits on the ggF production cross section of Gravitons in their $WW+ZZ$ decays as a function of the resonance mass.

Upper 95% CLs limits on the VBF production cross section of Gravitons in their $WW+ZZ$ decays as a function of the resonance mass.

Upper 95% CLs limits on the ggF production cross section of Radions in their $WW$ decays as a function of the resonance mass.

Upper 95% CLs limits on the VBF production cross section of Radions in their $WW$ decays as a function of the resonance mass.

Upper 95% CLs limits on the ggF production cross section of Radions in their $ZZ$ decays as a function of the resonance mass.

Upper 95% CLs limits on the VBF production cross section of Radions in their $ZZ$ decays as a function of the resonance mass.

Upper 95% CLs limits on the ggF production cross section of Gravitons in their $WW$ decays as a function of the resonance mass.

Upper 95% CLs limits on the VBF production cross section of Gravitons in their $WW$ decays as a function of the resonance mass.

Upper 95% CLs limits on the ggF production cross section of Gravitons in their $ZZ$ decays as a function of the resonance mass.

Upper 95% CLs limits on the VBF production cross section of Gravitons in their $ZZ$ decays as a function of the resonance mass.

Fig. A2: Number density $N_{ch}$ (left) and $\\Sigma p_{T}$ (right) distributions as a function of pleadingT and the comparisons to MC predictions in Toward (top), Transverse (middle), and Away (bottom) regions for $p_{T}^{track} >$ 1.0 GeV/$c$. The shaded areas in the upper panels represent the systematic uncertainties and vertical error bars indicate statistical uncertainties. In the lower panels, the shaded areas are the sum in quadrature of statistical and systematic uncertainties from the upper panels. No uncertainties are given for the MC calculations.

Fig. 9: R_T probability distribution in the Transverse region for $p_{T}^{track} >$ 0.15 GeV/$c$ and $|\\eta|<$ 0.8. The result (solid circles) is compared to the PYTHIA 8 and EPOS LHC calculations (lines). The red line represents the result of the NBD fit, where the multiplicity is scaled by its mean value, m. The parameter k is related to the standard deviation of the distribution via $\\sigma$ = $\\sqrt{ \\frac{1}{m} + \\frac{1}{k} }$. The open boxes represent the systematic uncertainties and vertical error bars indicate statistical uncertainties. No uncertainties are shown for the MC calculations. The bottom panel shows the ratio between the NBD fit, as well as those of the MC to the data.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L2b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc3LSS1b, in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The masses of the superpartners involved in the process are set to $m(\tilde{t}^{}_1)$ = 800 GeV, $m(\tilde \chi_2^0)$ = 625 GeV, $m(\tilde \chi_1^\pm)\approx m(\tilde \chi_1^0)$ = 525 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L, in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde{t}^{}_{1})$ = 800 GeV. Only statistical uncertainties are shown.

N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L0b from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}} / m_{\mathrm{eff}}$ of observed data and expected background towards Rpc2L1b from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L2b from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $m_{\mathrm{eff}}$ of observed data and expected background towards Rpv2L from publication's Figure 5 . The last bin is inclusive.

Expected 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Observed 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g \to q \bar{q}^{'} \tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm \to W^\pm \tilde{\chi}_2^0$ and $ \tilde{\chi}_2^0 \to Z \tilde{\chi}_1^0$.

Expected 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Observed 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Expected 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Observed 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal acceptance for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Signal acceptance for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal acceptance for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal acceptance for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.

Signal acceptance for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Signal efficiency for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Signal efficiency for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal efficiency for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal efficiency for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.

Signal efficiency for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Observed 95% CL upper limit on $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.

Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Observed 95% CL upper limit on $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Transverse momentum spectra of (anti-)$^3\mathrm{H}$ measured in $\mathrm{INEL}>0$ p--Pb collisions at $\sqrt{s_\mathrm{NN}} = 5.02$

$^3\overline{\mathrm{He}} /\,^3\mathrm{He}$ ratio in $\mathrm{INEL}>0$ p--Pb collisions at $\sqrt{s_\mathrm{NN}} = 5.02$

$^3\overline{\mathrm{H}} /\,^3\mathrm{H}$ ratio in $\mathrm{INEL}>0$ p--Pb collisions at $\sqrt{s_\mathrm{NN}} = 5.02$

Transverse momentum spectra obtained from the average of $^3\mathrm{He}$ and $^3\overline{\mathrm{He}}$ for $\mathrm{INEL}>0$ events in p$-$Pb collisions at $\sqrt{s_\mathrm{NN}} = 5.02$

Transverse momentum spectra obtained from the average of $^3\mathrm{He}$ and $^3\overline{\mathrm{He}}$ for events in 0$-$10% multiplicity class in p$-$Pb collisions at $\sqrt{s_\mathrm{NN}} = 5.02$

Transverse momentum spectra obtained from the average of $^3\mathrm{He}$ and $^3\overline{\mathrm{He}}$ for events in 10$-$20% multiplicity class in p$-$Pb collisions at $\sqrt{s_\mathrm{NN}} = 5.02$

Transverse momentum spectra obtained from the average of $^3\mathrm{He}$ and $^3\overline{\mathrm{He}}$ for events in 20$-$40% multiplicity class in p--Pb collisions at $\sqrt{s_\mathrm{NN}} = 5.02$

Transverse momentum spectra obtained from the average of $^3\mathrm{He}$ and $^3\overline{\mathrm{He}}$ for events in 40$-$100% multiplicity class in p--Pb collisions at $\sqrt{s_\mathrm{NN}} = 5.02$

Mean transverse momentum obtained from the average of $^3\mathrm{He}$ and $^3\overline{\mathrm{He}}$ as a function of the mean charged-particle multiplicity density in p--Pb collisions at $\sqrt{s_\mathrm{NN}} = 5.02$ TeV

$(^3\mathrm{He} +\,^3\overline{\mathrm{He}}) / (\mathrm{p} + \overline{\mathrm{p}})$ ratio in p$-$Pb as a function of the mean charged-particle multiplicity density

$(^3\mathrm{H} +\,^3\overline{\mathrm{H}}) / (\mathrm{p} + \overline{\mathrm{p}})$ ratio in p$-$Pb as a function of the mean charged-particle multiplicity density

Coalescence parameter $B_3$ calculated using the average of $\mathrm{INEL}>0$ $^3\mathrm{He}$ and $^3\overline{\mathrm{He}}$ yields

Coalescence parameter $B_3$ calculated using the average of $\mathrm{INEL}>0$ $^3\mathrm{H}$ and $^3\overline{\mathrm{H}}$ yields

Ratio of (anti-)$^3$H and (anti-)$^3$He yields

Coalescence parameter $B_3$ calculated using the average of $^3\mathrm{He}$ and $^3\overline{\mathrm{He}}$ for $\mathrm{INEL}>0$ events in p$-$Pb collisions at $\sqrt{s_\mathrm{NN}} = 5.02$

Coalescence parameter $B_3$ calculated using the average of $^3\mathrm{He}$ and $^3\overline{\mathrm{He}}$ for events in 0$-$10% multiplicity class in p$-$Pb collisions at $\sqrt{s_\mathrm{NN}} = 5.02$

Coalescence parameter $B_3$ calculated using the average of $^3\mathrm{He}$ and $^3\overline{\mathrm{He}}$ for events in 10$-$20% multiplicity class in p$-$Pb collisions at $\sqrt{s_\mathrm{NN}} = 5.02$

Coalescence parameter $B_3$ calculated using the average of $^3\mathrm{He}$ and $^3\overline{\mathrm{He}}$ for events in 20$-$40% multiplicity class in p--Pb collisions at $\sqrt{s_\mathrm{NN}} = 5.02$

Coalescence parameter $B_3$ calculated using the average of $^3\mathrm{He}$ and $^3\overline{\mathrm{He}}$ for events in 40$-$100% multiplicity class in p--Pb collisions at $\sqrt{s_\mathrm{NN}} = 5.02$

Integrated production yield obtained from the average of $^3\mathrm{He}$ and $^3\overline{\mathrm{He}}$ for the different multiplicity classes and $\mathrm{INEL} > 0$ p--Pb collisions at $\sqrt{s_\mathrm{NN}} = 5.02$

Integrated production yield obtained from the average of $^3\mathrm{H}$ and $^3\overline{\mathrm{H}}$ for $\mathrm{INEL} > 0$ p--Pb collisions at $\sqrt{s_\mathrm{NN}} = 5.02$

$p_{\rm T}$-differential invariant cross section of electrons from heavy-flavour hadron decays in p--Pb collisions in 40--60\% centrality

$p_{\rm T}$-differential invariant cross section of electrons from heavy-flavour hadron decays in p--Pb collisions in 60--100\% centrality

HFe $R_{\rm pPb}$ in p--Pb

HFe $Q_{\rm pPb}$ in p--Pb, 0--20\% centrality

HFe $Q_{\rm pPb}$ in p--Pb, 20--40\% centrality

HFe $Q_{\rm pPb}$ in p--Pb, 40--60\% centrality

HFe $Q_{\rm pPb}$ in p--Pb, 60--100\% centrality

HFe $Q_{\rm cp}$ in p--Pb, 0--20\% centrality

HFe $Q_{\rm cp}$ in p--Pb, 20--40\% centrality

HFe $Q_{\rm cp}$ in p--Pb, 40--60\% centrality

Inclusive J/$\psi$ nuclear modification factor $R_{\rm AA}$ at midrapidity, integrated over $p_{\rm T}$, as a function of mean number of participating nucleons in Pb$-$Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV. The correlated systematic uncertainty due to the pp reference is not included and amounts to 6.9%, shown as the red box around unity in the paper figure.

Inclusive J/$\psi$ nuclear modification factor $R_{\rm AA}$ at midrapidity for $p_{\rm T} > 0.15$ GeV as a function of mean number of participating nucleons in Pb$-$Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV. The low-$p_{\rm T}$ interval is removed to reject J/$\psi$ from photo-production. The correlated systematic uncertainty due to the pp reference cross section is not listed and amounts to 6.9%, shown as the red box around unity in the paper figure.

Inclusive J/$\psi$ nuclear modification factor, $R_{\rm AA}$, at midrapidity in Pb$-$Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV as a function of transverse momentum, $p_{\rm T}$, for different centrality intervals. The systematic uncertianty from the pp reference, which is correlated with centrality and shown as grey band in the paper figure, is listed as sys,Reference. The systematic uncertainties on the $T_{\rm AA}$ which are correlated in $p_{\rm T}$ for each centrality bin are not listed and amount additionally to 2\%, 3\%, and 5\% for 0-20\%, 20-40\%, and 40-90\% centrality, respectively. These uncertainties are shown as boxes around unity in the paper figure.

Nuclear modification factor $R_{\rm AA}$ of inclusive J/$\psi$ at mid-rapidity. For the midrapidity point all normalization uncertainties are included.

Model-independent constraints on the coupling strength modifier as a function of the heavy scalar boson mass, for a relative width of 1.0%.

Model-independent constraints on the coupling strength modifier as a function of the heavy scalar boson mass, for a relative width of 2.5%.

Model-independent constraints on the coupling strength modifier as a function of the heavy scalar boson mass, for a relative width of 5.0%.

Model-independent constraints on the coupling strength modifier as a function of the heavy scalar boson mass, for a relative width of 10.0%.

Model-independent constraints on the coupling strength modifier as a function of the heavy scalar boson mass, for a relative width of 25.0%.

Model-independent constraints on the coupling strength modifier as a function of the heavy pseudoscalar boson mass, for a relative width of 0.5%.

Model-independent constraints on the coupling strength modifier as a function of the heavy pseudoscalar boson mass, for a relative width of 1.0%.

Model-independent constraints on the coupling strength modifier as a function of the heavy pseudoscalar boson mass, for a relative width of 2.5%.

Model-independent constraints on the coupling strength modifier as a function of the heavy pseudoscalar boson mass, for a relative width of 5.0%.

Model-independent constraints on the coupling strength modifier as a function of the heavy pseudoscalar boson mass, for a relative width of 10.0%.

Model-independent constraints on the coupling strength modifier as a function of the heavy pseudoscalar boson mass, for a relative width of 25.0%.

Model-independent constraints on the coupling strength modifier as a function of the heavy pseudoscalar boson mass, for a relative width of 0.5%.

Model-independent constraints on the coupling strength modifier as a function of the heavy pseudoscalar boson mass, for a relative width of 1.0%.

Model-independent constraints on the coupling strength modifier as a function of the heavy pseudoscalar boson mass, for a relative width of 2.5%.

Model-independent constraints on the coupling strength modifier as a function of the heavy pseudoscalar boson mass, for a relative width of 5.0%.

Model-independent constraints on the coupling strength modifier as a function of the heavy pseudoscalar boson mass, for a relative width of 10.0%.

Model-independent constraints on the coupling strength modifier as a function of the heavy pseudoscalar boson mass, for a relative width of 25.0%.

One-dimensional limits on the ATGC effective Lagrangian (LEP parametrization) parameters at 95% CL from the combination of EW Wjj and EW Zjj analyses.

Muon pT in data and SM backgrounds, and various aTGC scenarios after the event preselection, in the muon channel.

Electron pT in data and SM backgrounds, and various aTGC scenarios after the event preselection, in the electron channel.

Hadronic activity veto efficiencies in the signal-enriched BDT> 0.95 region for the muon and electron channels combined, as a function of the leading additional jet $p_T$. The data are compared with the background-only prediction as well as background+signal with PYTHIA parton showering and background+signal with HERWIG++ parton showering. In addition, the background+signal prediction from POWHEG plus HERWIG++ parton showering is included. The uncertainty bands include only the statistical uncertainty in the prediction from simulation.

Hadronic activity veto efficiencies in the signal-enriched BDT> 0.95 region for the muon and electron channels combined, as a function of additional jet $H_T$. The data are compared with the background-only prediction as well as background+signal with PYTHIA parton showering and background+signal with HERWIG++ parton showering. In addition, the background+signal prediction from POWHEG plus HERWIG++ parton showering is included. The uncertainty bands include only the statistical uncertainty in the prediction from simulation.

Hadronic activity veto efficiencies in the signal-enriched BDT> 0.95 region for the muon and electron channels combined, as a function of leading soft-activity jet $p_T$. The data are compared with the background-only prediction as well as background+signal with PYTHIA parton showering and background+signal with HERWIG++ parton showering. In addition, the background+signal prediction from POWHEG plus HERWIG++ parton showering is included. The uncertainty bands include only the statistical uncertainty in the prediction from simulation.

Hadronic activity veto efficiencies in the signal-enriched BDT> 0.95 region for the muon and electron channels combined, as a function of soft-activity jet $H_T$. The data are compared with the background-only prediction as well as background+signal with PYTHIA parton showering and background+signal with HERWIG++ parton showering. In addition, the background+signal prediction from POWHEG plus HERWIG++ parton showering is included. The uncertainty bands include only the statistical uncertainty in the prediction from simulation.

Transformed BDT output distribution after the event preselection, in the muon channel.

Transformed BDT output distribution after the event preselection, in the electron channel.

Measured cross section and signal strength, relative to the standard model expectation.

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 (2 sigma band) 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.

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

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.

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

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 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 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 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 $\bar\Lambda$ global polarization as function of transverse momentum ($p_{\mathrm{T}}$) for 15-50% centrality in Pb-Pb collisions at $\sqrt{s_{\mathrm{NN}}}=2.76$~TeV.

The $\bar\Lambda$ global polarization as function of transverse momentum ($p_{\mathrm{T}}$) for 5-15% centrality in Pb-Pb collisions at $\sqrt{s_{\mathrm{NN}}}=2.76$~TeV.

The $\bar\Lambda$ global polarization as function of transverse momentum ($p_{\mathrm{T}}$) for 15-50% centrality in Pb-Pb collisions at $\sqrt{s_{\mathrm{NN}}}=5.02$~TeV.

The $\bar\Lambda$ global polarization as function of transverse momentum ($p_{\mathrm{T}}$) for 5-15% centrality in Pb-Pb collisions at $\sqrt{s_{\mathrm{NN}}}=5.02$~TeV.

The $\bar\Lambda$ global polarization as function of centrality for Pb-Pb collisions at $\sqrt{s_{\mathrm{NN}}}=2.76$~TeV.

The $\bar\Lambda$ global polarization as function of centrality for Pb-Pb collisions at $\sqrt{s_{\mathrm{NN}}}=5.02$~TeV.

The $\Lambda$ global polarization as function of centrality for Pb-Pb collisions at $\sqrt{s_{\mathrm{NN}}}=2.76$~TeV.

The $\Lambda$ global polarization as function of centrality for Pb-Pb collisions at $\sqrt{s_{\mathrm{NN}}}=5.02$~TeV.

The $\Lambda$ global polarization as function of transverse momentum ($p_{\mathrm{T}}$) for 15-50% centrality in Pb-Pb collisions at $\sqrt{s_{\mathrm{NN}}}=2.76$~TeV.

The $\Lambda$ global polarization as function of transverse momentum ($p_{\mathrm{T}}$) for 5-15% centrality in Pb-Pb collisions at $\sqrt{s_{\mathrm{NN}}}=2.76$~TeV.

The $\Lambda$ global polarization as function of transverse momentum ($p_{\mathrm{T}}$) for 15-50% centrality in Pb-Pb collisions at $\sqrt{s_{\mathrm{NN}}}=5.02$~TeV.

The $\Lambda$ global polarization as function of transverse momentum ($p_{\mathrm{T}}$) for 5-15% centrality in Pb-Pb collisions at $\sqrt{s_{\mathrm{NN}}}=5.02$~TeV.

The $\Lambda$ global polarization as function of centrality for Pb-Pb collisions at $\sqrt{s_{\mathrm{NN}}}=2.76$~TeV.

The $\Lambda$ global polarization as function of centrality for Pb-Pb collisions at $\sqrt{s_{\mathrm{NN}}}=5.02$~TeV.

The correction $R_{\mathrm{SP}}^{(1)}$ for finite resolution of the spectator plane angle $\Psi_{\mathrm{SP}}$ as a function of collision centrality for LHC10h data set.

The correction $R_{\mathrm{SP}}^{(1)}$ for finite resolution of the spectator plane angle $\Psi_{\mathrm{SP}}$ as a function of collision centrality for LHC11h data set.

The correction $R_{\mathrm{SP}}^{(1)}$ for finite resolution of the spectator plane angle $\Psi_{\mathrm{SP}}$ as a function of collision centrality for LHC15h data set.

Observed and predicted mTtot distribution in the b-tag category of the 2tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.

Observed and expected 95% CL upper limits on the gluon-gluon fusion Higgs boson production cross section times ditau branching fraction as a function of the Higgs boson mass.

Observed and expected 95% CL upper limits on the b-associated Higgs boson production cross section times ditau branching fraction as a function of the boson mass.

The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.

The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.

The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.

The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.

The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.

The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.

The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.

The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.

The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.

The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.

The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.

The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.

Acceptance times efficiency for a scalar boson produced by gluon-gluon fusion as a function of the scalar boson mass.

Acceptance times efficiency for a scalar boson produced by b-associated production as a function of the scalar boson mass.

Observed 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.

Expected 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.

Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.

Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.

Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.

Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.

Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.

Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.

Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.

Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.

Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.

Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.

Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.

Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.

Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.

Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.

Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.

HFe cross section in Pb-Pb, 60-80 centrality

HFe RAA in Pb-Pb, 0-10 centrality

HFe RAA in Pb-Pb, 30-50 centrality

HFe RAA in Pb-Pb, 60-80 centrality

The summed covariance matrix of all systematic and statistical uncertainties associated with the measurement in bins of $\ln{(1/z)} \times \ln{(R/\Delta R)}$.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 0.69 < ln(1/z) < 0.97.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 0.97 < ln(1/z) < 1.25.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 1.25 < ln(1/z) < 1.52.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 1.52 < ln(1/z) < 1.80.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 1.80 < ln(1/z) < 2.08.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 2.08 < ln(1/z) < 2.36.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 2.36 < ln(1/z) < 2.63.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 2.63 < ln(1/z) < 2.91.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 2.91 < ln(1/z) < 3.19.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 3.19 < ln(1/z) < 3.47.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 3.47 < ln(1/z) < 3.74.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 3.74 < ln(1/z) < 4.02.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 4.02 < ln(1/z) < 4.30.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 4.30 < ln(1/z) < 4.57.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 4.57 < ln(1/z) < 4.85.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 4.85 < ln(1/z) < 5.13.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 5.13 < ln(1/z) < 5.41.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 5.41 < ln(1/z) < 5.68.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 5.68 < ln(1/z) < 5.96.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 0.00 < ln(R/#DeltaR) < 0.33.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 0.33 < ln(R/#DeltaR) < 0.67.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 0.67 < ln(R/#DeltaR) < 1.00.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 1.00 < ln(R/#DeltaR) < 1.33.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 1.33 < ln(R/#DeltaR) < 1.67.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 1.67 < ln(R/#DeltaR) < 2.00.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 2.00 < ln(R/#DeltaR) < 2.33.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 2.33 < ln(R/#DeltaR) < 2.67.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 2.67 < ln(R/#DeltaR) < 3.00.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 3.00 < ln(R/#DeltaR) < 3.33.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 3.33 < ln(R/#DeltaR) < 3.67.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 3.67 < ln(R/#DeltaR) < 4.00.

Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 4.00 < ln(R/#DeltaR) < 4.33.

The measured fiducial cross section vs $m(\ell\ell\gamma)$. The central values are provided along with the statistical and systematic uncertainties together with the sign information. The statistical and "Uncor" uncertainty should be treated as uncorrelated bin-to-bin, while the rest are correlated between bins, and they are written as signed NP variations. The parton-to-particle correction factor $C_{theory}$ is the ratio of the cross-section predicted by Sherpa LO samples at particle level within the fiducial phase-space region defined in Table 4 to the predicted cross-section at parton level within the same fiducial region but with the smooth-cone isolation prescription defined above replacing the particle-level photon isolation criterion, and with Born-level leptons in place of dressed leptons. This correction should be applied on fixed order parton-level calculations. The systematic uncertainty is evaluated from a comparison with the correction factor obtained using events generated with SHERPA 2.2.2 at NLO. In the case that the calculations are valid for dressed leptons, a modified correction factor excluding the Born-to-dressed lepton correction should be applied instead. This correction only takes into account the particle-level isolation criteria, and is provided separately here. The Sherpa 2.2.8 NLO cross-sections given below include a small contribution from EW $Z\gamma jj$ production.

The measured fiducial cross section vs $p_{\mathrm{T}}^{\ell\ell\gamma}$. The central values are provided along with the statistical and systematic uncertainties together with the sign information. The statistical and "Uncor" uncertainty should be treated as uncorrelated bin-to-bin, while the rest are correlated between bins, and they are written as signed NP variations. The parton-to-particle correction factor $C_{theory}$ is the ratio of the cross-section predicted by Sherpa LO samples at particle level within the fiducial phase-space region defined in Table 4 to the predicted cross-section at parton level within the same fiducial region but with the smooth-cone isolation prescription defined above replacing the particle-level photon isolation criterion, and with Born-level leptons in place of dressed leptons. This correction should be applied on fixed order parton-level calculations. The systematic uncertainty is evaluated from a comparison with the correction factor obtained using events generated with SHERPA 2.2.2 at NLO. In the case that the calculations are valid for dressed leptons, a modified correction factor excluding the Born-to-dressed lepton correction should be applied instead. This correction only takes into account the particle-level isolation criteria, and is provided separately here. The Sherpa 2.2.8 NLO cross-sections given below include a small contribution from EW $Z\gamma jj$ production.

The measured fiducial cross section vs $\Delta\phi(ll,\gamma)$. The central values are provided along with the statistical and systematic uncertainties together with the sign information. The statistical and "Uncor" uncertainty should be treated as uncorrelated bin-to-bin, while the rest are correlated between bins, and they are written as signed NP variations. The parton-to-particle correction factor $C_{theory}$ is the ratio of the cross-section predicted by Sherpa LO samples at particle level within the fiducial phase-space region defined in Table 4 to the predicted cross-section at parton level within the same fiducial region but with the smooth-cone isolation prescription defined above replacing the particle-level photon isolation criterion, and with Born-level leptons in place of dressed leptons. This correction should be applied on fixed order parton-level calculations. The systematic uncertainty is evaluated from a comparison with the correction factor obtained using events generated with SHERPA 2.2.2 at NLO. In the case that the calculations are valid for dressed leptons, a modified correction factor excluding the Born-to-dressed lepton correction should be applied instead. This correction only takes into account the particle-level isolation criteria, and is provided separately here. The Sherpa 2.2.8 NLO cross-sections given below include a small contribution from EW $Z\gamma jj$ production.

The measured fiducial cross section vs $p_{\mathrm{T}}^{\ell\ell\gamma}/m(\ell\ell\gamma)$. The central values are provided along with the statistical and systematic uncertainties together with the sign information. The statistical and "Uncor" uncertainty should be treated as uncorrelated bin-to-bin, while the rest are correlated between bins, and they are written as signed NP variations. The parton-to-particle correction factor $C_{theory}$ is the ratio of the cross-section predicted by Sherpa LO samples at particle level within the fiducial phase-space region defined in Table 4 to the predicted cross-section at parton level within the same fiducial region but with the smooth-cone isolation prescription defined above replacing the particle-level photon isolation criterion, and with Born-level leptons in place of dressed leptons. This correction should be applied on fixed order parton-level calculations. The systematic uncertainty is evaluated from a comparison with the correction factor obtained using events generated with SHERPA 2.2.2 at NLO. In the case that the calculations are valid for dressed leptons, a modified correction factor excluding the Born-to-dressed lepton correction should be applied instead. This correction only takes into account the particle-level isolation criteria, and is provided separately here. The Sherpa 2.2.8 NLO cross-sections given below include a small contribution from EW $Z\gamma jj$ production.

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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 r