Dependence of the parameter $A$ on $(t_1, t_2)$.

Dependence of the parameter $R$ on $(t_1, t_2)$.

Dependence of the parameter $c$ on $(t_1, t_2)$.

Dependence of the parameter $R$ on the two scattered proton transverse momenta.

Correlation coefficients among values of best parameters for the two-channel model, in the case of the exponential parametrisation of the proton-pomeron form factor.

Correlation coefficients among values of best parameters for the two-channel model, in the case of the Orear-type parametrisation of the proton-pomeron form factor.

Correlation coefficients among values of best parameters for the two-channel model, in the case of the power-law parametrisation of the proton-pomeron form factor.

Post-fit distribution of the $M(ll)$ variable for the ultrahigh-$p_{\mathrm{T}}^{\mathrm{miss}}$ bins in the '2l soft' signal region of the '2/3l soft' analysis.

Post-fit distribution of the $M(ll)$ variable for the low-$p_{\mathrm{T}}^{\mathrm{miss}}$ bins in the '3l soft' signal region of the the '2/3l soft' analysis.

Post-fit distribution of the $M(ll)$ variable for the medium-$p_{\mathrm{T}}^{\mathrm{miss}}$ bins in the '3l soft' signal region of the the '2/3l soft' analysis.

Post-fit distribution of the $m_{\mathrm{T2}}(ll)$ variable for low-$p_{\mathrm{T}}^{\mathrm{miss}}$ bins in the '2l soft' signal region of the '2/3l soft' analysis.

Post-fit distribution of the $m_{\mathrm{T2}}(ll)$ variable for medium-$p_{\mathrm{T}}^{\mathrm{miss}}$ bins in the '2l soft' signal region of the '2/3l soft' analysis.

Post-fit distribution of the $m_{\mathrm{T2}}(ll)$ variable for high-$p_{\mathrm{T}}^{\mathrm{miss}}$ bins in the '2l soft' signal region of the '2/3l soft' analysis.

Post-fit distribution of the $m_{\mathrm{T2}}(ll)$ variable for ultrahigh-$p_{\mathrm{T}}^{\mathrm{miss}}$ bins in the '2l soft' signal region of the '2/3l soft' analysis.

2SS $\ell/{\geq}\,3\ell$ search: observed and expected yields across the SRs in category A, events with three light leptons of which at least two form an OSSF pair, after the requirement that the leading-lepton $p_{\mathrm{T}}$ be greater than 30 GeV is applied.

2SS $\ell/{\geq}\,3\ell$ search: observed and expected yields across the SRs of the '${\geq}\ 3\ell$' search in category B, events with three light leptons and no OSSF pair, after the requirement that the leading-lepton $p_{\mathrm{T}}$ be greater than 30 GeV is applied.

Wino-bino model: cross section limits in the model parameter space, for wino-like chargino-neutralino production in the WZ topology for the full parameter space.

Wino-bino model: cross section limits in the model parameter space, for wino-like chargino-neutralino production in the WZ topology for the compressed space.

Wino-bino model: cross section limits in the model parameter space, for wino-like chargino-neutralino production in the WH topology for the full parameter space.

Wino-bino model: cross section limits in the model parameter space, for wino-like chargino-neutralino production with mixed topology with equal branching fraction to WZ and WH.

Wino-bino model: exclusion contours from the individual and combined analyses targeting WZ topology for the full parameter space. For visualization of the exclusion contours, linear interpolation is employed to account for the limited granularity of the available signal samples.

Wino-bino model: exclusion contours from the individual and combined analyses targeting the corresponding compressed region. For visualization of the exclusion contours, linear interpolation is employed to account for the limited granularity of the available signal samples.

Wino-bino model: exclusion contours from the individual and combined analyses targeting the WH topology for the full parameter space. For visualization of the exclusion contours, linear interpolation is employed to account for the limited granularity of the available signal samples.

Wino-bino model: exclusion contours from the individual and combined analyses targeting combined contours for these two topologies. For visualization of the exclusion contours, linear interpolation is employed to account for the limited granularity of the available signal samples.

GMSB model: expected and observed cross section limits for the neutralino-neutralino production for the ZZ topology.

GMSB model: expected and observed cross section limits for the neutralino-neutralino production for the HH topology.

GMSB model: expected and observed cross section limits for the neutralino-neutralino production for the mixed topology with equal branching fraction to H and Z.

GMSB model: cross section limits for neutralino-neutralino production as a function of the NSLP mass and the branching fraction to the H boson for the combination of the searches.

GMSB model: exclusion limit for neutralino-neutralino production as a function of the NSLP mass and the branching fraction to the H boson for the combination of the searches along with the input searches. For visualization of the exclusion contours, linear interpolation is employed to account for the limited granularity of the available signal samples.

Cross section upper limit(s) in the mass plane of NLSP and LSP masses for the higgsino-bino model.

Mass plane cross section upper limit for direct slepton pair production, with observed and expected exclusion limits in the full mass plane from the combination.

Mass plane cross section upper limit for direct slepton pair production, with observed and expected exclusion limits in the compressed region from '2/3l' soft search.

Statistical correlation coefficients for double-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.4 as a function of the dijet invariant mass ($m_{1,2}$) and the absolute rapidity of the outermost jet ($\left| y \right|_\text{max}$)

Double-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.8 as a function of the dijet invariant mass ($m_{1,2}$) and the absolute rapidity of the outermost jet ($\left| y \right|_\text{max}$)

Electroweak corrections to double-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.8 as a function of the dijet invariant mass ($m_{1,2}$) and the absolute rapidity of the outermost jet ($\left| y \right|_\text{max}$)

Nonperturbative corrections to double-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.8 as a function of the dijet invariant mass ($m_{1,2}$) and the absolute rapidity of the outermost jet ($\left| y \right|_\text{max}$)

Statistical correlation coefficients for double-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.8 as a function of the dijet invariant mass ($m_{1,2}$) and the absolute rapidity of the outermost jet ($\left| y \right|_\text{max}$)

Triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.4 as a function of the dijet invariant mass ($m_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

Electroweak corrections to triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.4 as a function of the dijet invariant mass ($m_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

Nonperturbative corrections to triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.4 as a function of the dijet invariant mass ($m_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

Statistical correlation coefficients for triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.4 as a function of the dijet invariant mass ($m_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

Triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.8 as a function of the dijet invariant mass ($m_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

Electroweak corrections to triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.8 as a function of the dijet invariant mass ($m_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

Nonperturbative corrections to triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.8 as a function of the dijet invariant mass ($m_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

Statistical correlation coefficients for triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.8 as a function of the dijet invariant mass ($m_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

Triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.4 as a function of the dijet average transverse momentum ($\langle p_\text{T} \rangle_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

Electroweak corrections to triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.4 as a function of the dijet average transverse momentum ($\langle p_\text{T} \rangle_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

Nonperturbative corrections to triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.4 as a function of the dijet average transverse momentum ($\langle p_\text{T} \rangle_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

Statistical correlation coefficients for triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.4 as a function of the dijet average transverse momentum ($\langle p_\text{T} \rangle_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

Triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.8 as a function of the dijet average transverse momentum ($\langle p_\text{T} \rangle_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

Electroweak corrections to triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.8 as a function of the dijet average transverse momentum ($\langle p_\text{T} \rangle_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

Nonperturbative corrections to triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.8 as a function of the dijet average transverse momentum ($\langle p_\text{T} \rangle_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

Statistical correlation coefficients for triple-differential dijet cross section for anti-$k_\text{T}$ jets with R = 0.8 as a function of the dijet average transverse momentum ($\langle p_\text{T} \rangle_{1,2}$), the total boost of dijet system ($y_\text{b}$), and the absolute rapidity separation of the two jets ($y^*$)

The JEC, JER, and total systematic uncertainties in unfolded cross sections as functions of transverse momentum, for 1.5<|y|<2. The total systematic uncertainty includes also the luminosity, jet identification and trigger efficiency uncertainties.

The unfolded measured particle-level inclusive jet cross section as functions of jet pT (markers), for |y|<0.5, compared to the NLO perturbative QCD prediction (histogram), using the CT14NLO PDF set, with muR = muF = HT, and corrected for the NP effects. The experimental and theoretical systematic uncertainties are shown.

The unfolded measured particle-level inclusive jet cross section as functions of jet pT (markers), for 0.5<|y|<1, compared to the NLO perturbative QCD prediction (histogram), using the CT14NLO PDF set, with muR = muF = HT, and corrected for the NP effects. The experimental and theoretical systematic uncertainties are shown.

The unfolded measured particle-level inclusive jet cross section as functions of jet pT (markers), for 1<|y|<1.5, compared to the NLO perturbative QCD prediction (histogram), using the CT14NLO PDF set, with muR = muF = HT, and corrected for the NP effects. The experimental and theoretical systematic uncertainties are shown.

The unfolded measured particle-level inclusive jet cross section as functions of jet pT (markers), for 1.5<|y|<2, compared to the NLO perturbative QCD prediction (histogram), using the CT14NLO PDF set, with muR = muF = HT, and corrected for the NP effects. The experimental and theoretical systematic uncertainties are shown.

Ratios (points) of the unfolded measured cross sections to the NLO theoretical predictions, using the CT14NLO PDF set, with mu = pT, for |y|<0.5. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

Ratios (points) of the unfolded measured cross sections to the NLO theoretical predictions, using the CT14NLO PDF set, with mu = pT, for 0.5<|y|<1. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

Ratios (points) of the unfolded measured cross sections to the NLO theoretical predictions, using the CT14NLO PDF set, with mu = pT, for 1<|y|<1.5. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

Ratios (points) of the unfolded measured cross sections to the NLO theoretical predictions, using the CT14NLO PDF set, with mu = pT, for 1.5<|y|<2. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

Ratios (points) of the unfolded measured cross sections to the NLO theoretical predictions, using the CT14NLO PDF set, with mu = HT, for |y|<0.5. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

Ratios (points) of the unfolded measured cross sections to the NLO theoretical predictions, using the CT14NLO PDF set, with mu = HT, for 0.5<|y|<1. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

Ratios (points) of the unfolded measured cross sections to the NLO theoretical predictions, using the CT14NLO PDF set, with mu = HT, for 1<|y|<1.5. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

Ratios (points) of the unfolded measured cross sections to the NLO theoretical predictions, using the CT14NLO PDF set, with mu = HT, for 1.5<|y|<2. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

Ratios (points) of the unfolded measured cross sections to the NNLO theoretical predictions, using the CT14NNLO PDF set, with mu = HT, for |y|<0.5. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

Ratios (points) of the unfolded measured cross sections to the NNLO theoretical predictions, using the CT14NNLO PDF set, with mu = HT, for 0.5<|y|<1. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

Ratios (points) of the unfolded measured cross sections to the NNLO theoretical predictions, using the CT14NNLO PDF set, with mu = HT, for 1<|y|<1.5. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

Ratios (points) of the unfolded measured cross sections to the NNLO theoretical predictions, using the CT14NNLO PDF set, with mu = HT, for 1.5<|y|<2. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

Ratios (points) of the unfolded measured cross sections to the NNLO theoretical predictions, using the NNPDF31NNLO PDF set, with mu = HT, for |y|<0.5. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

Ratios (points) of the unfolded measured cross sections to the NNLO theoretical predictions, using the NNPDF31NNLO PDF set, with mu = HT, for 0.5<|y|<1. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

Ratios (points) of the unfolded measured cross sections to the NNLO theoretical predictions, using the NNPDF31NNLO PDF set, with mu = HT, for 1<|y|<1.5. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

Ratios (points) of the unfolded measured cross sections to the NNLO theoretical predictions, using the NNPDF31NNLO PDF set, with mu = HT, for 1.5<|y|<2. The vertical error bars show the statistical experimental uncertainty. The systematic experimental uncertainty, the total theoretical uncertainty, and the individual sources of theoretical uncertainty are shown.

The effect of aS(MZ) variation, for |y|<0.5. The NNLO theoretical cross section predictions using the NNPDF31NNLO PDF with m = HT, calculated for different choices of aS (0.108, 0.110, 0.112, 0.114, 0.116, 0.117, 0.118, 0.119, 0.120, 0.122, and 0.124), are divided by the benchmark NNLO prediction for aS = 0.118 and the same choice of PDF set, muR, and muF. Also shown is the experimental unfolded measurement divided by the same benchmark prediction. The width of the unity line corresponds to the statistical uncertainty from the MC integration for the determination of the NNLO prediction. The error bars on the unfolded data correspond to the total experimental statistical and systematic uncertainty added in quadrature.

The effect of aS(MZ) variation, for 0.5<|y|<1. The NNLO theoretical cross section predictions using the NNPDF31NNLO PDF with m = HT, calculated for different choices of aS (0.108, 0.110, 0.112, 0.114, 0.116, 0.117, 0.118, 0.119, 0.120, 0.122, and 0.124), are divided by the benchmark NNLO prediction for aS = 0.118 and the same choice of PDF set, muR, and muF. Also shown is the experimental unfolded measurement divided by the same benchmark prediction. The width of the unity line corresponds to the statistical uncertainty from the MC integration for the determination of the NNLO prediction. The error bars on the unfolded data correspond to the total experimental statistical and systematic uncertainty added in quadrature.

The effect of aS(MZ) variation, for 1<|y|<1.5. The NNLO theoretical cross section predictions using the NNPDF31NNLO PDF with m = HT, calculated for different choices of aS (0.108, 0.110, 0.112, 0.114, 0.116, 0.117, 0.118, 0.119, 0.120, 0.122, and 0.124), are divided by the benchmark NNLO prediction for aS = 0.118 and the same choice of PDF set, muR, and muF. Also shown is the experimental unfolded measurement divided by the same benchmark prediction. The width of the unity line corresponds to the statistical uncertainty from the MC integration for the determination of the NNLO prediction. The error bars on the unfolded data correspond to the total experimental statistical and systematic uncertainty added in quadrature.

The effect of aS(MZ) variation, for 1.5<|y|<2. The NNLO theoretical cross section predictions using the NNPDF31NNLO PDF with m = HT, calculated for different choices of aS (0.108, 0.110, 0.112, 0.114, 0.116, 0.117, 0.118, 0.119, 0.120, 0.122, and 0.124), are divided by the benchmark NNLO prediction for aS = 0.118 and the same choice of PDF set, muR, and muF. Also shown is the experimental unfolded measurement divided by the same benchmark prediction. The width of the unity line corresponds to the statistical uncertainty from the MC integration for the determination of the NNLO prediction. The error bars on the unfolded data correspond to the total experimental statistical and systematic uncertainty added in quadrature.

Unfolded correlation matrix for |y|<0.5.

Unfolded correlation matrix for 0.5<|y|<1.

Unfolded correlation matrix for 1<|y|<1.5.

Unfolded correlation matrix for 1.5<|y|<2.

Two-dimensional exclusion limits for Dirac HNL pure electron coupling scenario

Two-dimensional exclusion limits for Majorana HNL pure muon coupling scenario

Two-dimensional exclusion limits for Dirac HNL pure muon coupling scenario

Two-dimensional exclusion limits for Majorana HNL pure tau lepton coupling scenario

Two-dimensional exclusion limits for Dirac HNL pure tau lepton coupling scenario

Two-dimensional exclusion limits for Majorana HNL mixed electron-muon coupling scenario

DTwo-dimensional exclusion limits for Dirac HNL mixed electron-muon coupling scenario

Two-dimensional exclusion limits for Majorana HNL mixed electron-tau lepton coupling scenario

Two-dimensional exclusion limits for Dirac HNL mixed electron-tau lepton coupling scenario

Two-dimensional exclusion limits for Majorana HNL mixed muon-tau lepton coupling scenario

Two-dimensional exclusion limits for Dirac HNL mixed muon-tau lepton coupling scenario

Two-dimensional exclusion limits for Majorana HNL democratic lepton coupling scenario

Two-dimensional exclusion limits for Dirac HNL democratic lepton coupling scenario

Lower limits on Majorana HNL mass for fixed proper decay length of $c\tau=0.1\,\text{mm}$

Lower limits on Dirac HNL mass for fixed proper decay length of $c\tau=0.1\,\text{mm}$

Lower limits on Majorana HNL mass for fixed proper decay length of $c\tau=1\,\text{mm}$

Lower limits on Dirac HNL mass for fixed proper decay length of $c\tau=1\,\text{mm}$

Lower limits on Majorana HNL proper decay length for fixed mass of 4.5 GeV

Lower limits on Dirac HNL proper decay length for fixed mass of 4.5 GeV

Lower limits on Majorana HNL proper decay length for fixed mass of 8 GeV

Lower limits on Dirac HNL proper decay length for fixed mass of 8 GeV

Correlation matrix associated to the statistical covariance matrix of the data and MC for the primary Lund jet plane density for AK8 jets in a one-dimensional representation with bin indices. The mapping between the bin indices and the physical binning can be imported from the XML file attached to this HepData record using the TUnfoldBinningXML class of ROOT (qualitatively, it corresponds to slicing the Lund plane horizontally from low kT to high kT).

Differential cross sections normalized to the fiducial cross section as a function of the $p_T$ of the second-highest-$p_T$ jet

Differential cross sections normalized to the fiducial cross section as a function of the $|\eta|$ of the highest-$p_T$ jet

Differential cross sections normalized to the fiducial cross section as a function of the $|\eta|$ of the second-highest-$p_T$ jet

Differential cross sections normalized to the fiducial cross section as a function of the pseudorapidity difference between the two highest-$p_T$ jets in the event

Differential cross sections normalized to the fiducial cross section as a function of the invariant mass of the two highest-$p_T$ jets in the event

Differential cross sections normalized to the fiducial cross section as a function of the invariant mass of the four-lepton system, in the full $m_{4l}$ range

Differential cross sections normalized to the fiducial cross section as a function of the invariant mass of the four-lepton system in events with 0 jet, in the on-shell ZZ region

Differential cross sections normalized to the fiducial cross section as a function of the invariant mass of the four-lepton system in events with 1 jet, in the on-shell ZZ region

Differential cross sections normalized to the fiducial cross section as a function of the invariant mass of the four-lepton system in events with 2 jets, in the on-shell ZZ region

Differential cross sections normalized to the fiducial cross section as a function of the invariant mass of the four-lepton system in events with at least 3 jets, in the on-shell ZZ region

Differential cross sections normalized to the fiducial cross section as a function of the invariant mass of the four-lepton system in events with 0 jet, in the full $m_{4l}$ range

Differential cross sections normalized to the fiducial cross section as a function of the invariant mass of the four-lepton system in events with 1 jet, in the full $m_{4l}$ range

Differential cross sections normalized to the fiducial cross section as a function of the invariant mass of the four-lepton system in events with 2 jets, in the full $m_{4l}$ range

Differential cross sections normalized to the fiducial cross section as a function of the invariant mass of the four-lepton system in events with at least 3 jets, in the full $m_{4l}$ range

Product of detector efficiency and analysis acceptance for signal samples with various $m_a$ values for the muon channel.

Unfolded E2C distributions in data compared to MC predictions.

Unfolded E2C distributions in data compared to MC predictions.

Unfolded E2C distributions in data compared to MC predictions.

Unfolded E2C distributions in data compared to MC predictions.

Unfolded E2C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.

Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.

Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.

Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.

Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.

Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.

Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.

Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.

The fitted slopes of the E3C/E2C data distributions as a function of jet pt are used to illustrate the dependency of alphas on jet pt.

Unfolded E3C/E2C distributions in data compared to MC predictions.

Unfolded E3C/E2C distributions in data compared to MC predictions.

Unfolded E3C/E2C distributions in data compared to MC predictions.

Unfolded E3C/E2C distributions in data compared to MC predictions.

Unfolded E3C/E2C distributions in data compared to MC predictions.

Unfolded E3C/E2C distributions in data compared to MC predictions.

Unfolded E3C/E2C distributions in data compared to MC predictions.

Unfolded E3C/E2C distributions in data compared to MC predictions.

The chi2 scan result using eq.3 for different alphas.

The correlation matrix is composed by 10 jet pt region, each region is represented by a block in the plot. Inside each block, there are 22 xL bins same as the E2C, E3C and E3C/E2C distributions. Therefore, the x and y bins of the correlation matrix is given by, binNumber = pT_index * 22 + xL_index.

The correlation matrix is composed by 10 jet pt region, each region is represented by a block in the plot. Inside each block, there are 22 xL bins same as the E2C, E3C and E3C/E2C distributions. Therefore, the x and y bins of the correlation matrix is given by, binNumber = pT_index * 22 + xL_index.

The correlation matrix is composed by 10 jet pt region, each region is represented by a block in the plot. Inside each block, there are 22 xL bins same as the E2C, E3C and E3C/E2C distributions. Therefore, the x and y bins of the correlation matrix is given by, binNumber = pT_index * 22 + xL_index.

The energy weight of E2C as defined in eq.1 in the paper is used in the unfolding, the binning is listed in this table.

The energy weight of E3C as defined in eq.1 in the paper is used in the unfolding, the binning is listed in this table.