The total coherent $\mathrm{J}/\psi$ photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$, measured in PbPb ultra-peripheral collisions at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV. The $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$ values used correspond to the center of each rapidity range. The theoretical uncertainties is due to the uncertainties in the photon flux.

The nuclear gluon suppression factor $R_{\mathrm{g}}^{\mathrm{Pb}}$ as a function of Bjorken $x$ extracted from the CMS measurement of the coherent $\mathrm{J}/\psi$ photoproduction in PbPb ultra-peripheral collisions at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV. The $x$ values are evaluated at the centers of their corresponding rapidity ranges. The theoretical uncertainties are due to the uncertainties in the photon flux and the impulse approximation model.

The nuclear gluon suppression factor $R_{\mathrm{g}}^{\mathrm{Pb}}$ as a function of Bjorken $x$ extracted from the CMS measurement of the coherent $\mathrm{J}/\psi$ photoproduction in PbPb ultra-peripheral collisions at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV. The $x$ values are evaluated at the centers of their corresponding rapidity ranges. The theoretical uncertainties are due to the uncertainties in the photon flux and the impulse approximation model.

The total covariance matrix of the total coherent photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$. The covariance matrix includes both the experimental and theoretical (photon flux) uncertainties. The bins are ordered as increasing in $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$.

The photon flux values from STARLight as a function of rapidity, in different neutron multiplicity classes: 0n0n, 0nXn, and XnXn.

The experimental covariance matrix of the total coherent photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$. The bins are ordered as increasing in $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$.

The covariance matrix for the flux in the 0n0n neutron multiplicity class.

The theoretical (photon flux) covariance matrix of the total coherent photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$. The bins are ordered as increasing in $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$.

The covariance matrix for the flux in the 0nXn neutron multiplicity class.

The covariance matrix for the flux in the XnXn neutron multiplicity class.

The total covariance matrix of the total coherent photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$. The covariance matrix includes both the experimental and theoretical (photon flux) uncertainties. The bins are ordered as increasing in $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$.

The experimental covariance matrix of the total coherent photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$. The bins are ordered as increasing in $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$.

The theoretical (photon flux) covariance matrix of the total coherent photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$. The bins are ordered as increasing in $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$.

Covariance matrix for the extrapolation uncertainty for the measurement of the absolute differential cross section as a function of the rho observable at parton level.

Normalized differential cross section as a function of the rho observable at parton level.

Covariance matrix for the total uncertainty (i.e. fit including stat., not extrapolation) for the measurement of the normalized differential cross section as a function of the rho observable at parton level.

Covariance matrix for the statistical uncertainty for the measurement of the normalized differential cross section as a function of the rho observable at parton level.

Covariance matrix for the extrapolation uncertainty for the measurement of the normalized differential cross section as a function of the rho observable at parton level.

Correlation matrix for all nuisance parameters and parameters of interest of the Likelihood fit.

This table is a numerical representation of Fig. 8 for all nuisance parameters.

Distribution of an input to the BDT classifier in the $3\ell$ category: The linear discrimminant $p_{T}^{miss,LD}$. The discriminant is defined by the relation $p_{T}^{miss,LD} = 0.6 p_{T}^{miss} + 0.4 H_{T}^{miss}$, where $H_{T}^{miss}$ corresponds to the magnitude of the vector $p_{T}$ sum of all electrons, muons, taus and small radius jets passing the selection critertia, and $p_{T}^{miss}$ represents the missing transverse momentum vector computed as the negative vector $p_{T}$ sum of all the particles reconstructed by the PF algorithm in the event.

Distributions of the transverse mass $m_{T}$ of the lepton that is not originating from the Z boson decay and the missing transverse momentum in the $3\ell$/WZ control region. The distributions expected for the WZ and ZZ as well as for other background processes are shown for the values of nuisance parameters obtained from the ML fit used in the signal extraction.

Distributions of the four lepton invariant mass $m_{4\ell}$ in the $4\ell$/ZZ control region. The distributions expected for the ZZ as well as for other background processes are shown for the values of nuisance parameters obtained from the ML fit used in the signal extraction.

Distributions of the transverse mass $m_{T}$ of the leading lepton and the missing transverse momentum in the $2\ell$(ss) control region. The distributions expected for the misidentified $\ell$ background as well as for other background processes is shown for the values of nuisance parameters obtained from the background-only ML fit, in which the HH signal is constrained to be zero.

Distributions of the reconstructed HH mass $m_{HH}$ in the $2\ell+2 au_{h}$ control region. The distributions expected for the misidentified $\ell/ au_{h}$ background as well as for other background processes is shown for the values of nuisance parameters obtained from the background-only ML fit, in which the HH signal is constrained to be zero.

Distribution in the output of the BDT trained for nonresonant HH production and evaluated for the benchmark scenario JHEP04 BM7 for the $2\ell$(ss) category. The SM HH signal is shown for a cross section amounting to $30$ times the value predicted in the SM. The distributions expected for the background processes are shown for the values of nuisance parameters obtained from the ML fit of the signal+background hypothesis to the data. The binning is chosen to approximate signal quantiles.

Distribution in the output of the BDT trained for nonresonant HH production and evaluated for the benchmark scenario JHEP04 BM7 for the $3\ell$ category. The SM HH signal is shown for a cross section amounting to $30$ times the value predicted in the SM. The distributions expected for the background processes are shown for the values of nuisance parameters obtained from the ML fit of the signal+background hypothesis to the data. The binning is chosen to approximate signal quantiles.

Distribution in the output of the BDT trained for nonresonant HH production and evaluated for the benchmark scenario JHEP04 BM7 for the $4\ell$ category. The SM HH signal is shown for a cross section amounting to $30$ times the value predicted in the SM. The distributions expected for the background processes are shown for the values of nuisance parameters obtained from the ML fit of the signal+background hypothesis to the data. The binning is chosen to approximate signal quantiles.

Distribution in the output of the BDT trained for nonresonant HH production and evaluated for the benchmark scenario JHEP04 BM7 for the $3\ell+1 au_{h}$ category. The SM HH signal is shown for a cross section amounting to $30$ times the value predicted in the SM. The distributions expected for the background processes are shown for the values of nuisance parameters obtained from the ML fit of the signal+background hypothesis to the data. The binning is chosen to approximate background quantiles.

Distribution in the output of the BDT trained for nonresonant HH production and evaluated for the benchmark scenario JHEP04 BM7 for the $2\ell+2 au_{h}$ category. The SM HH signal is shown for a cross section amounting to $30$ times the value predicted in the SM. The distributions expected for the background processes are shown for the values of nuisance parameters obtained from the ML fit of the signal+background hypothesis to the data. The binning is chosen to approximate background quantiles.

Distribution in the output of the BDT trained for nonresonant HH production and evaluated for the benchmark scenario JHEP04 BM7 for the $1\ell+3 au_{h}$ category. The SM HH signal is shown for a cross section amounting to $30$ times the value predicted in the SM. The distributions expected for the background processes are shown for the values of nuisance parameters obtained from the ML fit of the signal+background hypothesis to the data. The binning is chosen to approximate background quantiles.

Distribution in the output of the BDT trained for nonresonant HH production and evaluated for the benchmark scenario JHEP04 BM7 for the $4 au_{h}$ category. The SM HH signal is shown for a cross section amounting to $30$ times the value predicted in the SM. The distributions expected for the background processes are shown for the values of nuisance parameters obtained from the ML fit of the signal+background hypothesis to the data. The binning is chosen to approximate background quantiles.

Observed and expected $95\%$ CL upper limits on the SM HH production cross section, obtained for both individual search categories and from a simultaneous fit of all seven categories combined.

Observed and expected $95\%$ CL upper limits on the HH production cross section as a function of the Higgs boson self-coupling strength modifier $\kappa_\lambda$ for the combination of all seven categories. All Higgs boson couplings other than $\lambda$ are assumed to have the values predicted in the SM.

Observed and expected $95\%$ CL upper limits on the HH production cross section as a function of the Higgs boson self-coupling strength modifier $\kappa_\lambda$ for the seven different categories as well as their combination. All Higgs boson couplings other than $\lambda$ are assumed to have the values predicted in the SM.

Observed and expected $95\%$ CL upper limits on the HH production cross section for the twelve benchmark scenarios from doi:10.1007/JHEP04(2016)126, the additional benchmark scenario 8a from doi:10.1007/JHEP09(2018)057, the seven benchmark scenarios from doi:10.1007/JHEP03(2020)091, and for the SM.

Observed and expected $95\%$ CL upper limits on the HH production cross section for the twelve benchmark scenarios from doi:10.1007/JHEP04(2016)126, the additional benchmark scenario 8a from doi:10.1007/JHEP09(2018)057, the seven benchmark scenarios from doi:10.1007/JHEP03(2020)091, and for the SM. The limits are shown for all seven search categories as well as for their combination.

Observed and expected $95\%$ CL upper limits on the HH production cross section as a function of the effective coupling $c_{2}$ for the combination of all seven categories. All Higgs boson couplings other than $c_{2}$ are assumed to have the values predicted in the SM.

Observed and expected $95\%$ CL upper limits on the HH production cross section as a function of the effective coupling $c_{2}$ and the top Yukawa coupling modifier $\kappa_{t}$ for the combination of all seven categories. All Higgs boson couplings other than $c_{2}$ and $\kappa_{t}$ are assumed to have the values predicted in the SM. The position of the SM in the ($c_{2}-\kappa_{t}$) plane, as well as the best fit value of $(c_{2},\kappa_{t})=(1.05, 1.74)$ together with contours for the theory cross section are shown as well.

Observed and expected $95\%$ CL upper limits on the HH production cross section as a function of the Higgs boson self-coupling modifier $\kappa_{\lambda}$ and the top Yukawa coupling modifier $\kappa_{t}$ for the combination of all seven categories. All Higgs boson couplings other than $\kappa_{\lambda}$ and $\kappa_{t}$ are assumed to have the values predicted in the SM. The position of the SM in the ($\kappa_{\lambda}-\kappa_{t}$) plane, as well as the best fit value of $(\kappa_{\lambda},\kappa_{t})=(-3.54, -1.70)$ together with contours for the theory cross section are shown as well.

Observed and expected $95\%$ CL upper limits on the HH production cross section as a function of the effective coupling $c_{2}$ and the Higgs boson self-coupling modifier $\kappa_{\lambda}$ for the combination of all seven categories. All Higgs boson couplings other than $c_{2}$ and $\kappa_{\lambda}$ are assumed to have the values predicted in the SM. The position of the SM in the ($c_{2}-\kappa_{\lambda}$) plane, as well as the best fit value of $(c_{2},\kappa_{\lambda})=(-0.66, 5.33)$ together with contours for the theory cross section are shown as well.

Observed and expected $95\%$ CL upper limits on the production of new particles X of spin $0$ and mass $m_{X}$ in the range $250$-$1000$ GeV, which decay to Higgs boson pairs.

Observed and expected $95\%$ CL upper limits on the production of new particles X of spin $0$ and mass $m_{X}$ in the range $250$-$1000$ GeV, which decay to Higgs boson pairs. The Limit is shown for the seven different search categories as well as their combination.

Observed and expected $95\%$ CL upper limits on the production of new particles X of spin $2$ and mass $m_{X}$ in the range $250$-$1000$ GeV, which decay to Higgs boson pairs.

Observed and expected $95\%$ CL upper limits on the production of new particles X of spin $2$ and mass $m_{X}$ in the range $250$-$1000$ GeV, which decay to Higgs boson pairs. The Limit is shown for the seven different search categories as well as their combination.

Distribution in the output of the BDT trained for resonances of spin 2 and mass $750\,$GeV production for the $2\ell$(ss) category. The resonant HH signal is shown for a cross section amounting to $1\,$pb. The distributions expected for the background processes are shown for the values of nuisance parameters obtained from the ML fit of the signal+background hypothesis to the data. The binning is chosen to approximate signal quantiles.

Distribution in the output of the BDT trained for resonances of spin 2 and mass $750\,$GeV production for the $3\ell$ category. The resonant HH signal is shown for a cross section amounting to $1\,$pb. The distributions expected for the background processes are shown for the values of nuisance parameters obtained from the ML fit of the signal+background hypothesis to the data. The binning is chosen to approximate signal quantiles.

Exclusion limits at 95% CL for direct gluino pair production, where the gluinos decay to light-flavor quarks and a $\tilde{\chi}_1^\pm$ that decays to $W^\pm\tilde{\chi}_1^0$. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, assuming unity branching fraction to $q_i\bar{q}_j W\pm\tilde{\chi}_1^0$.

Exclusion limits at 95% CL for direct gluino pair production, where the gluinos decay to bottom quarks ($\tilde{g}\to b\bar{b}\tilde{\chi}_1^0$). Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, assuming unity branching fraction for the given decay.

Exclusion limits at 95% CL for direct gluino pair production, where the gluinos decay to top quarks ($\tilde{g}\to t\bar{t}\tilde{\chi}_1^0$). Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, assuming unity branching fraction for the given decay.

Exclusion limits at 95% CL for light-flavor squark pair production, where the squarks decay to $q\tilde{\chi}_1^0$. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, assuming unity branching fraction for the given decay and 1-fold degeneracy in the light-flavor squarks (corresponding to the inner set of curves in the limit plot). To get the theory cross section for other N-fold degeneracy assumptions (e.g. 8-fold for the outer curves in the limit plot), just multiply by N.

Exclusion limits at 95% CL for bottom squark pair production, where the squarks decay to $b\tilde{\chi}_1^0$. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, assuming unity branching fraction for the given decay.

Exclusion limits at 95% CL for top squark pair production, where the squarks decay to $t\tilde{\chi}_1^0$. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, assuming unity branching fraction for the given decay.

Exclusion limits at 95% CL for top squark pair production, where the squarks decay to $b\tilde{\chi}_1^\pm$ and the $\tilde{\chi}_1^0$ decay to $W^\pm\tilde{\chi}_1^0$. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, assuming unity branching fraction for the given decay.

Exclusion limits at 95% CL for top squark pair production, where the squarks decay either to $b\tilde{\chi}_1^\pm\to bW^\pm\tilde{\chi}_1^0$ or to $t\tilde{\chi}_1^0$. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, assuming unity branching fraction for the given decay.

Exclusion limits at 95% CL for top squark pair production, where the squarks decay to $c\tilde{\chi}_1^0$. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, assuming unity branching fraction for the given decay.

Exclusion limits at 95% CL for the mono-$\phi$ model, in which a resonantly-produced colored scalar decays to a massive Dirac fermion and a quark. Signal cross sections are calculated at leading order in $\alpha_S$, assuming unity branching fraction for the given decay.

Cross section limits for $\mathrm{LQ}\to\mathrm{q}\nu$, where $q=u,\,d,\,s,\,\mathrm{or}\,c$. Limits are at the 95% confidence level. Theory cross sections are LO for vector LQ, and NLO for scalar LQ. Branching ratio is assumed to be 100% to $\mathrm{q}\nu$.

Cross section limits for $\mathrm{LQ}\to\mathrm{b}\nu$. Limits are at the 95% confidence level. Theory cross sections are LO for vector LQ, and NLO for scalar LQ. Branching ratio is assumed to be 100% to $\mathrm{b}\nu$.

Cross section limits for $\mathrm{LQ}\to\mathrm{t}\nu$. Limits are at the 95% confidence level. Theory cross sections are LO for vector LQ, and NLO for scalar LQ. Branching ratios are assumed to be $\mathcal{B}(\mathrm{LQ}\to\mathrm{t}\nu)=1-\beta$, and $\mathcal{B}(\mathrm{LQ}\to\mathrm{b}\tau)=\beta$.

Predictions and observations for monojet signal regions

Predictions and observations for signal regions with $250 \leq H_\mathrm{T} < 450$ GeV

Predictions and observations for signal regions with $450 \leq H_\mathrm{T} < 575$ GeV and $N_\mathrm{j}<7$

Predictions and observations for signal regions with $450 \leq H_\mathrm{T} < 575$ GeV and $N_\mathrm{j}\geq7$

Predictions and observations for signal regions with $575 \leq H_\mathrm{T} < 1200$ GeV and $N_\mathrm{j}^\mathrm{hi}<4$

Predictions and observations for signal regions with $575 \leq H_\mathrm{T} < 1200$ GeV and $4\leq N_\mathrm{j}^\mathrm{hi}<7$

Predictions and observations for signal regions with $575 \leq H_\mathrm{T} < 1200$ GeV and $N_\mathrm{j}\geq7$

Predictions and observations for signal regions with $1200 \leq H_\mathrm{T} < 1500$ GeV and $N_\mathrm{j}^\mathrm{hi}<4$

Predictions and observations for signal regions with $1200 \leq H_\mathrm{T} < 1500$ GeV and $4\leq N_\mathrm{j}^\mathrm{hi}<7$

Predictions and observations for signal regions with $1200 \leq H_\mathrm{T} < 1500$ GeV and $N_\mathrm{j}\geq7$

Predictions and observations for signal regions with $H_\mathrm{T} \geq 1500$ GeV and $N_\mathrm{j}<7$

Predictions and observations for signal regions with $H_\mathrm{T} \geq 1500$ GeV and $N_\mathrm{j}\geq7$

Covariance matrix for the 282 signal regions of the inclusive $M_\mathrm{T2}$ search

Correlation matrix for the 282 signal regions of the inclusive $M_\mathrm{T2}$ search

Bin number definitions for the $M_\mathrm{T2}$ covariance and correlation matrices

Exclusion limits at 95% CL for direct gluino pair production, where the gluinos decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino is long-lived with $c\tau_0 = 10$ cm and mass O(100) MeV greater than the neutralino's mass. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$.

Exclusion limits at 95% CL for direct gluino pair production, where the gluinos decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino is long-lived with $c\tau_0 = 50$ cm and mass O(100) MeV greater than the neutralino's mass. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$.

Exclusion limits at 95% CL for direct gluino pair production, where the gluinos decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino is long-lived with $c\tau_0 = 200$ cm and mass O(100) MeV greater than the neutralino's mass. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$.

Exclusion limits at 95% CL for direct light squark pair production, where the squarks decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino is long-lived with $c\tau_0 = 10$ cm and mass O(100) MeV greater than the neutralino's mass. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, for a single light squark.

Exclusion limits at 95% CL for direct light squark pair production, where the squarks decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino is long-lived with $c\tau_0 = 50$ cm and mass O(100) MeV greater than the neutralino's mass. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, for a single light squark.

Exclusion limits at 95% CL for direct light squark pair production, where the squarks decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino is long-lived with $c\tau_0 = 200$ cm and mass O(100) MeV greater than the neutralino's mass. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, for a single light squark.

Exclusion limits at 95% CL for direct stop pair production, where the stops decay to either a top and the lightest neutralino, or a bottom and the lightest chargino, and the chargino is long-lived with $c\tau_0 = 10$ cm and mass O(100) MeV greater than the neutralino's mass. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$.

Exclusion limits at 95% CL for direct stop pair production, where the stops decay to either a top and the lightest neutralino, or a bottom and the lightest chargino, and the chargino is long-lived with $c\tau_0 = 50$ cm and mass O(100) MeV greater than the neutralino's mass. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$.

Exclusion limits at 95% CL for direct stop pair production, where the stops decay to either a top and the lightest neutralino, or a bottom and the lightest chargino, and the chargino is long-lived with $c\tau_0 = 200$ cm and mass O(100) MeV greater than the neutralino's mass. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$.

The maximum chargino mass excluded at 95% CL for direct gluino pair production, where the gluinos decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino mass is O(100) MeV greater than the neutralino's mass. The chargino's lifetime is varied from $c\tau_{0} = 1$ to 2000 cm while the gluino mass is fixed to 1900 GeV. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$. If all kinematically allowed chargino masses are excluded, the curves, including 68 and 95% expected, tend to overlap. At short decay lengths, horizontal exclusion lines are obtained from the inclusive analysis, as this is not affected by track reconstruction inefficiencies, which may arise when the chargino decays before the CMS tracker, and therefore shows better sensitivity to scenarios with very small lifetime compared to the disappearing track search, based on median expected limits.

The maximum chargino mass excluded at 95% CL for direct squark pair production, where the squarks decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino mass is O(100) MeV greater than the neutralino's mass. The chargino's lifetime is varied from $c\tau_{0} = 1$ to 2000 cm while the squark mass is fixed to 900 GeV. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, for a single light squark. If all kinematically allowed chargino masses are excluded, the curves, including 68 and 95% expected, tend to overlap. At short decay lengths, horizontal exclusion lines are obtained from the inclusive analysis, as this is not affected by track reconstruction inefficiencies, which may arise when the chargino decays before the CMS tracker, and therefore shows better sensitivity to scenarios with very small lifetime compared to the disappearing track search, based on median expected limits.

The maximum chargino mass excluded at 95% CL for direct squark pair production, where the squarks decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino mass is O(100) MeV greater than the neutralino's mass. The chargino's lifetime is varied from $c\tau_{0} = 1$ to 2000 cm while the squark mass is fixed to 1500 GeV. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, and the eight light squarks' masses are assumed to be degenerate. If all kinematically allowed chargino masses are excluded, the curves, including 68 and 95% expected, tend to overlap. At short decay lengths, horizontal exclusion lines are obtained from the inclusive analysis, as this is not affected by track reconstruction inefficiencies, which may arise when the chargino decays before the CMS tracker, and therefore shows better sensitivity to scenarios with very small lifetime compared to the disappearing track search, based on median expected limits.

Exclusion limits at 95% CL for direct stop pair production, where the stops decay to either a top and the lightest neutralino, or a bottom and the lightest chargino, and the chargino mass is O(100) MeV greater than the neutralino's mass. The chargino's lifetime is varied from $c\tau_{0} = 1$ to 2000 cm while the stop mass is fixed to 1000 GeV. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$. If all kinematically allowed chargino masses are excluded, the curves, including 68 and 95% expected, tend to overlap. At short decay lengths, horizontal exclusion lines are obtained from the inclusive analysis, as this is not affected by track reconstruction inefficiencies, which may arise when the chargino decays before the CMS tracker, and therefore shows better sensitivity to scenarios with very small lifetime compared to the disappearing track search, based on median expected limits.

Exclusion limits at 95% CL for direct gluino pair production, where the gluinos decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino mass is O(100) MeV greater than the neutralino's mass. The chargino's lifetime is varied from $c\tau_{0} = 5$ to 1000 cm while the gluino mass is fixed to 1600 GeV and the neutralino's mass is fixed to 1575 GeV. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$.

Exclusion limits at 95% CL for direct squark pair production, where the squarks decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino mass is O(100) MeV greater than the neutralino's mass. The chargino's lifetime is varied from $c\tau_{0} = 5$ to 1000 cm while the squark mass is fixed to 2000 GeV and the neutralino's mass is fixed to 1000 GeV. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, and the eight light squarks' masses are assumed to be degenerate.

Exclusion limits at 95% CL for direct stop pair production, where the stops decay to either a top and the lightest neutralino, or a bottom and the lightest chargino, and the chargino mass is O(100) MeV greater than the neutralino's mass. The chargino's lifetime is varied from $c\tau_{0} = 5$ to 1000 cm while the stop mass is fixed to 1100 GeV and the neutralino's mass is fixed to 1000 GeV. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$.

Predictions and observations for 2016 disappearing track signal regions

Predictions and observations for 2017-2018 pixel track signal regions

Predictions and observations for 2017-2018 medium (M) and long (L) length track signal regions

Covariance matrix for the 68 signal regions of the disappearing tracks $M_\mathrm{T2}$ search

Correlation matrix for the 68 signal regions of the disappearing tracks $M_\mathrm{T2}$ search

The covariance matrix containing the experimental uncertainties of the particle-level $\mathrm{t}\overline{\mathrm{t}}$ differential cross section as a function of the XCone-jet mass.

The covariance matrix containing the model uncertainties of the particle-level $\mathrm{t}\overline{\mathrm{t}}$ differential cross section as a function of the XCone-jet mass.

The normalized particle-level $\mathrm{t}\overline{\mathrm{t}}$ differential cross section in the fiducial region as a function of the XCone-jet mass.

Correlations between bins in the normalized particle-level $\mathrm{t}\overline{\mathrm{t}}$ differential cross section as a function of the XCone-jet mass.

The covariance matrix containing the statistical uncertainties of the normalized particle-level $\mathrm{t}\overline{\mathrm{t}}$ differential cross section as a function of the XCone-jet mass.

The covariance matrix containing the experimental uncertainties of the normalized particle-level $\mathrm{t}\overline{\mathrm{t}}$ differential cross section as a function of the XCone-jet mass.

The covariance matrix containing the model uncertainties of the normalized particle-level $\mathrm{t}\overline{\mathrm{t}}$ differential cross section as a function of the XCone-jet mass.

Relative experimental uncertainties of the particle-level $\mathrm{t}\overline{\mathrm{t}}$ differential cross section in the fiducial region as a function of the XCone-jet mass.

Relative model uncertainties of the particle-level $\mathrm{t}\overline{\mathrm{t}}$ differential cross section in the fiducial region as a function of the XCone-jet mass.

Relative experimental uncertainties of the normalized particle-level $\mathrm{t}\overline{\mathrm{t}}$ differential cross section in the fiducial region as a function of the XCone-jet mass.

Relative model uncertainties of the normalized particle-level $\mathrm{t}\overline{\mathrm{t}}$ differential cross section in the fiducial region as a function of the XCone-jet mass.

$f_{0}(980)$ to pions ($(\pi^{+}+\pi^{-})/2$), $p_{\rm T}$-integrated yield ratio at midrapidity as a function of $\langle {\rm d}N_{\rm ch}/{\rm d}\eta \rangle$. The uncertainty 'stat,syst' indicates the total uncertainty (stat+syst) on the measurement. The branching ratio correction amounts to BR = (46 $\pm$ 6)% [ Phys. Rev. Lett. 111 no. 6, (2013) 062001] assuming dominance of $\pi\pi$ and KK channel has been applied to the $p_{\rm T}$-differential yields of $f_{0}(980)$. Here, the branching ratio relative uncertainty (13%) for $f_{0}(980)$ is not included.

Fig. 1 Left, data for jet radius R=0.2. Unfolded pp full jet cross-section at $\sqrt{s}$ = 5.02 TeV for R = 0.1 − 0.6. No leading track requirement is imposed.

Fig. 1 Left, data for jet radius R=0.3. Unfolded pp full jet cross-section at $\sqrt{s}$ = 5.02 TeV for R = 0.1 − 0.6. No leading track requirement is imposed.

Fig. 1 Left, data for jet radius R=0.3. Unfolded pp full jet cross-section at $\sqrt{s}$ = 5.02 TeV for R = 0.1 − 0.6. No leading track requirement is imposed.

Fig. 1 Left, data for jet radius R=0.4. Unfolded pp full jet cross-section at $\sqrt{s}$ = 5.02 TeV for R = 0.1 − 0.6. No leading track requirement is imposed.

Fig. 1 Left, data for jet radius R=0.4. Unfolded pp full jet cross-section at $\sqrt{s}$ = 5.02 TeV for R = 0.1 − 0.6. No leading track requirement is imposed.

Fig. 1 Left, data for jet radius R=0.5. Unfolded pp full jet cross-section at $\sqrt{s}$ = 5.02 TeV for R = 0.1 − 0.6. No leading track requirement is imposed.

Fig. 1 Left, data for jet radius R=0.5. Unfolded pp full jet cross-section at $\sqrt{s}$ = 5.02 TeV for R = 0.1 − 0.6. No leading track requirement is imposed.

Fig. 1 Left, data for jet radius R=0.6. Unfolded pp full jet cross-section at $\sqrt{s}$ = 5.02 TeV for R = 0.1 − 0.6. No leading track requirement is imposed.

Fig. 1 Left, data for jet radius R=0.6. Unfolded pp full jet cross-section at $\sqrt{s}$ = 5.02 TeV for R = 0.1 − 0.6. No leading track requirement is imposed.

Fig. 2, values for jet radius R=0.1. Non-perturbative correction factor applied to parton-level NLO+NLL predictions, obtained from PYTHIA 8 tune A14 as the ratio of the inclusive jet spectrum at hadron-level with MPI compared to parton-level without MPI.

Fig. 2, values for jet radius R=0.1. Non-perturbative correction factor applied to parton-level NLO+NLL predictions, obtained from PYTHIA 8 tune A14 as the ratio of the inclusive jet spectrum at hadron-level with MPI compared to parton-level without MPI.

Fig. 2, values for jet radius R=0.2. Non-perturbative correction factor applied to parton-level NLO+NLL predictions, obtained from PYTHIA 8 tune A14 as the ratio of the inclusive jet spectrum at hadron-level with MPI compared to parton-level without MPI.

Fig. 2, values for jet radius R=0.2. Non-perturbative correction factor applied to parton-level NLO+NLL predictions, obtained from PYTHIA 8 tune A14 as the ratio of the inclusive jet spectrum at hadron-level with MPI compared to parton-level without MPI.

Fig. 2, values for jet radius R=0.3. Non-perturbative correction factor applied to parton-level NLO+NLL predictions, obtained from PYTHIA 8 tune A14 as the ratio of the inclusive jet spectrum at hadron-level with MPI compared to parton-level without MPI.

Fig. 2, values for jet radius R=0.3. Non-perturbative correction factor applied to parton-level NLO+NLL predictions, obtained from PYTHIA 8 tune A14 as the ratio of the inclusive jet spectrum at hadron-level with MPI compared to parton-level without MPI.

Fig. 2, values for jet radius R=0.4. Non-perturbative correction factor applied to parton-level NLO+NLL predictions, obtained from PYTHIA 8 tune A14 as the ratio of the inclusive jet spectrum at hadron-level with MPI compared to parton-level without MPI.

Fig. 2, values for jet radius R=0.4. Non-perturbative correction factor applied to parton-level NLO+NLL predictions, obtained from PYTHIA 8 tune A14 as the ratio of the inclusive jet spectrum at hadron-level with MPI compared to parton-level without MPI.

Fig. 2, values for jet radius R=0.5. Non-perturbative correction factor applied to parton-level NLO+NLL predictions, obtained from PYTHIA 8 tune A14 as the ratio of the inclusive jet spectrum at hadron-level with MPI compared to parton-level without MPI.

Fig. 2, values for jet radius R=0.5. Non-perturbative correction factor applied to parton-level NLO+NLL predictions, obtained from PYTHIA 8 tune A14 as the ratio of the inclusive jet spectrum at hadron-level with MPI compared to parton-level without MPI.

Fig. 2, values for jet radius R=0.6. Non-perturbative correction factor applied to parton-level NLO+NLL predictions, obtained from PYTHIA 8 tune A14 as the ratio of the inclusive jet spectrum at hadron-level with MPI compared to parton-level without MPI.

Fig. 2, values for jet radius R=0.6. Non-perturbative correction factor applied to parton-level NLO+NLL predictions, obtained from PYTHIA 8 tune A14 as the ratio of the inclusive jet spectrum at hadron-level with MPI compared to parton-level without MPI.

Fig. 3 Bottom, data for jet radius ratio R=0.1/R=0.2. Unfolded pp jet cross-section ratios for various R. With R = 0.1 in the numerator.

Fig. 3 Bottom, data for jet radius ratio R=0.1/R=0.2. Unfolded pp jet cross-section ratios for various R. With R = 0.1 in the numerator.

Fig. 3 Bottom, data for jet radius ratio R=0.1/R=0.3. Unfolded pp jet cross-section ratios for various R. With R = 0.1 in the numerator.

Fig. 3 Bottom, data for jet radius ratio R=0.1/R=0.3. Unfolded pp jet cross-section ratios for various R. With R = 0.1 in the numerator.

Fig. 3 Bottom, data for jet radius ratio R=0.1/R=0.4. Unfolded pp jet cross-section ratios for various R. With R = 0.1 in the numerator.

Fig. 3 Bottom, data for jet radius ratio R=0.1/R=0.4. Unfolded pp jet cross-section ratios for various R. With R = 0.1 in the numerator.

Fig. 3 Bottom, data for jet radius ratio R=0.1/R=0.5. Unfolded pp jet cross-section ratios for various R. With R = 0.1 in the numerator.

Fig. 3 Bottom, data for jet radius ratio R=0.1/R=0.5. Unfolded pp jet cross-section ratios for various R. With R = 0.1 in the numerator.

Fig. 3 Bottom, data for jet radius ratio R=0.1/R=0.6. Unfolded pp jet cross-section ratios for various R. With R = 0.1 in the numerator.

Fig. 3 Bottom, data for jet radius ratio R=0.1/R=0.6. Unfolded pp jet cross-section ratios for various R. With R = 0.1 in the numerator.

Fig. 3 Top, data for jet radius ratio R=0.2/R=0.3. Unfolded pp jet cross-section ratios for various R. With R = 0.2 in the numerator.

Fig. 3 Top, data for jet radius ratio R=0.2/R=0.3. Unfolded pp jet cross-section ratios for various R. With R = 0.2 in the numerator.

Fig. 3 Top, data for jet radius ratio R=0.2/R=0.4. Unfolded pp jet cross-section ratios for various R. With R = 0.2 in the numerator.

Fig. 3 Top, data for jet radius ratio R=0.2/R=0.4. Unfolded pp jet cross-section ratios for various R. With R = 0.2 in the numerator.

Fig. 3 Top, data for jet radius ratio R=0.2/R=0.5. Unfolded pp jet cross-section ratios for various R. With R = 0.2 in the numerator.

Fig. 3 Top, data for jet radius ratio R=0.2/R=0.5. Unfolded pp jet cross-section ratios for various R. With R = 0.2 in the numerator.

Fig. 3 Top, data for jet radius ratio R=0.2/R=0.6. Unfolded pp jet cross-section ratios for various R. With R = 0.2 in the numerator.

Fig. 3 Top, data for jet radius ratio R=0.2/R=0.6. Unfolded pp jet cross-section ratios for various R. With R = 0.2 in the numerator.

Fig. 4 Left, data for pp. Unfolded pp and Pb-Pb full jet spectra at $\sqrt{s}=5.02$ TeV for $R=0.2$, with 5 GeV leading track requirement. The pp data points correspond to $\frac{\mathrm{d}^{2}\sigma}{\mathrm{d}p_{\mathrm{T,jet}} \mathrm{d}\eta_{\mathrm{jet}}}$.

Fig. 4 Left, data for pp. Unfolded pp and Pb-Pb full jet spectra at $\sqrt{s}=5.02$ TeV for $R=0.2$, with 5 GeV leading track requirement. The pp data points correspond to $\frac{\mathrm{d}^{2}\sigma}{\mathrm{d}p_{\mathrm{T,jet}} \mathrm{d}\eta_{\mathrm{jet}}}$.

Fig. 4 Left, data for PbPb. Unfolded pp and Pb-Pb full jet spectra at $\sqrt{s}=5.02$ TeV for $R=0.2$, with 5 GeV leading track requirement. The pp data points correspond to $\frac{\mathrm{d}^{2}\sigma}{\mathrm{d}p_{\mathrm{T,jet}} \mathrm{d}\eta_{\mathrm{jet}}}$.

Fig. 4 Left, data for PbPb. Unfolded pp and Pb-Pb full jet spectra at $\sqrt{s}=5.02$ TeV for $R=0.2$, with 5 GeV leading track requirement. The pp data points correspond to $\frac{\mathrm{d}^{2}\sigma}{\mathrm{d}p_{\mathrm{T,jet}} \mathrm{d}\eta_{\mathrm{jet}}}$.

Fig. 4 Right, data for pp. Unfolded pp and Pb-Pb full jet spectra at $\sqrt{s}=5.02$ TeV for $R=0.4$, with 7 GeV leading track requirement.

Fig. 4 Right, data for pp. Unfolded pp and Pb-Pb full jet spectra at $\sqrt{s}=5.02$ TeV for $R=0.4$, with 7 GeV leading track requirement.

Fig. 4 Right, data for PbPb. Unfolded pp and Pb-Pb full jet spectra at $\sqrt{s}=5.02$ TeV for $R=0.4$, with 7 GeV leading track requirement.

Fig. 4 Right, data for PbPb. Unfolded pp and Pb-Pb full jet spectra at $\sqrt{s}=5.02$ TeV for $R=0.4$, with 7 GeV leading track requirement.

Fig. 5 Left, data for pp jet cross section with leading track bias ratio 5/0. Ratio of the pp jet cross-section with various leading charged particle requirements

Fig. 5 Left, data for pp jet cross section with leading track bias ratio 5/0. Ratio of the pp jet cross-section with various leading charged particle requirements

Fig. 5 Left, data for pp jet cross section with leading track bias ratio 7/0. Ratio of the pp jet cross-section with various leading charged particle requirements

Fig. 5 Left, data for pp jet cross section with leading track bias ratio 7/0. Ratio of the pp jet cross-section with various leading charged particle requirements

Fig. 5 Left, data for pp jet cross section with leading track bias ratio 7/5. Ratio of the pp jet cross-section with various leading charged particle requirements

Fig. 5 Left, data for pp jet cross section with leading track bias ratio 7/5. Ratio of the pp jet cross-section with various leading charged particle requirements

Fig. 5 Right. Ratio of the R = 0.2 Pb–Pb jet cross-section with a 7 GeV/c leading charged particle requirement compared to a 5 GeV/c leading charged particle requirement.

Fig. 5 Right. Ratio of the R = 0.2 Pb–Pb jet cross-section with a 7 GeV/c leading charged particle requirement compared to a 5 GeV/c leading charged particle requirement.

Fig. 6 Top Left. Jet $R_{\mathrm{AA}}$ at $\sqrt{s}=5.02$ TeV for $R=0.2$. Same leading track requirement of 5 GeV is imposed on the numerator as well as denominator.

Fig. 6 Top Left. Jet $R_{\mathrm{AA}}$ at $\sqrt{s}=5.02$ TeV for $R=0.2$. Same leading track requirement of 5 GeV is imposed on the numerator as well as denominator.

Fig. 6 Top Right. Jet $R_{\mathrm{AA}}$ at $\sqrt{s}=5.02$ TeV for $R=0.4$. Same leading track requirement of 7 GeV is imposed on the numerator as well as denominator.

Fig. 6 Top Right. Jet $R_{\mathrm{AA}}$ at $\sqrt{s}=5.02$ TeV for $R=0.4$. Same leading track requirement of 7 GeV is imposed on the numerator as well as denominator.

Fig. 6 Bottom Left. Jet $R_{\mathrm{AA}}$ at $\sqrt{s}=5.02$ TeV for $R=0.2$. PbPb with leading track requirement of 5 GeV. pp reference without a leading track requirement.

Fig. 6 Bottom Left. Jet $R_{\mathrm{AA}}$ at $\sqrt{s}=5.02$ TeV for $R=0.2$. PbPb with leading track requirement of 5 GeV. pp reference without a leading track requirement.

Fig. 6 Bottom Right. Jet $R_{\mathrm{AA}}$ at $\sqrt{s}=5.02$ TeV for $R=0.4$. PbPb with leading track requirement of 7 GeV. pp reference without a leading track requirement.

Fig. 6 Bottom Right. Jet $R_{\mathrm{AA}}$ at $\sqrt{s}=5.02$ TeV for $R=0.4$. PbPb with leading track requirement of 7 GeV. pp reference without a leading track requirement.

Reconstruction level differential cross section spectla, obtained for the central acceptance, $|\eta| < 3$, for events with Pomeron-Proton ($\mathrm{I\!P}\mathrm{p} + \gamma \mathrm{p}$) topology compared to the to the EPOS-LHC predictions, broken down into the non-diffractive (ND), central diffractive (CD), single diffractive (SD) and double diffractive (DD) components. Forward Rapidity Gap definition: $|\eta| < 2.5$: $p_{T}^{track} < 200$ MeV and $\sum \limits_{bin} E^{PF} < 6$ GeV $|\eta| \in [2.5,3.0]$: $\sum \limits_{bin} E_{neutral}^{PF} < 13.4$ GeV

The number of high purity tracksin the first $\eta$ bin after a gap of $4.5 \leq \Delta\eta^F < 5.0$ for events with the Pomeron-Proton ($\mathrm{I\!P}\mathrm{p} + \gamma \mathrm{p}$) topology Forward Rapidity Gap definition: $|\eta| < 2.5$: $p_{T}^{track} < 200$ MeV and $\sum \limits_{bin} E^{PF} < 6$ GeV $|\eta| \in [2.5,3.0]$: $\sum \limits_{bin} E_{neutral}^{PF} < 13.4$ GeV

The transeverse momentum of high purity tracksin the first $\eta$ bin after a gap of $4.5 \leq \Delta\eta^F < 5.0$ for events with the Pomeron-Proton ($\mathrm{I\!P}\mathrm{p} + \gamma \mathrm{p}$) topology Forward Rapidity Gap definition: $|\eta| < 2.5$: $p_{T}^{track} < 200$ MeV and $\sum \limits_{bin} E^{PF} < 6$ GeV $|\eta| \in [2.5,3.0]$: $\sum \limits_{bin} E_{neutral}^{PF} < 13.4$ GeV

The total energy of all Particle Flow candidatesin the first $\eta$ bin after a gap of $4.5 \leq \Delta\eta^F < 5.0$ for events with the Pomeron-Proton ($\mathrm{I\!P}\mathrm{p} + \gamma \mathrm{p}$) topology Forward Rapidity Gap definition: $|\eta| < 2.5$: $p_{T}^{track} < 200$ MeV and $\sum \limits_{bin} E^{PF} < 6$ GeV $|\eta| \in [2.5,3.0]$: $\sum \limits_{bin} E_{neutral}^{PF} < 13.4$ GeV

Unfolded diffraction enhanced differential cross section for events with Pomeron-Lead ($\mathrm{I\!P}\mathrm{Pb}$) topology, defined on the region $|\eta| < 5.2$, compared to hadron level predictions of the MC generators. The data are corrected for the contribution from events with undetectable energy in the HF calorimeter adjacent to the rapidity gap. The corrections are obtained using the EPOS-LHC MC sample. Forward Rapidity Gap definition: $|\eta| < 2.5$: $p_{T}^{track} < 200$ MeV and $\sum \limits_{bin} E^{PF} < 6$ GeV $|\eta| \in [2.5,3.0]$: $\sum \limits_{bin} E_{neutral}^{PF} < 13.4$ GeV $|\eta| > 3.0$: No particles

Unfolded diffraction enhanced differential cross section for events with Pomeron-Proton ($\mathrm{I\!P}\mathrm{p} + \gamma \mathrm{p}$) topology, defined on the region $|\eta| < 5.2$, compared to hadron level predictions of the MC generators. The data are corrected for the contribution from events with undetectable energy in the HF calorimeter adjacent to the rapidity gap. The corrections are obtained using the EPOS-LHC MC sample. Forward Rapidity Gap definition: $|\eta| < 2.5$: $p_{T}^{track} < 200$ MeV and $\sum \limits_{bin} E^{PF} < 6$ GeV $|\eta| \in [2.5,3.0]$: $\sum \limits_{bin} E_{neutral}^{PF} < 13.4$ GeV $|\eta| > 3.0$: No particles

Unfolded diffractive enhanced differential cross section spectla for events with Pomeron-Lead ($\mathrm{I\!P}\mathrm{Pb}$) topology, compared to the to the hadron-level EPOS-LHC predictions, broken down into the non-diffractive (ND), central diffractive (CD), single diffractive (SD) and double diffractive (DD) components. Forward Rapidity Gap definition: $|\eta| < 2.5$: $p_{T}^{track} < 200$ MeV and $\sum \limits_{bin} E^{PF} < 6$ GeV $|\eta| \in [2.5,3.0]$: $\sum \limits_{bin} E_{neutral}^{PF} < 13.4$ GeV $|\eta| > 3.0$: No particles

Unfolded diffractive enhanced differential cross section spectla for events with Pomeron-Proton ($\mathrm{I\!P}\mathrm{p} + \gamma \mathrm{p}$) topology, compared to the to the hadron-level EPOS-LHC predictions, broken down into the non-diffractive (ND), central diffractive (CD), single diffractive (SD) and double diffractive (DD) components. Forward Rapidity Gap definition: $|\eta| < 2.5$: $p_{T}^{track} < 200$ MeV and $\sum \limits_{bin} E^{PF} < 6$ GeV $|\eta| \in [2.5,3.0]$: $\sum \limits_{bin} E_{neutral}^{PF} < 13.4$ GeV $|\eta| > 3.0$: No particles

Unfolded diffractive enhanced differential cross section spectla for events with Pomeron-Lead ($\mathrm{I\!P}\mathrm{Pb}$) topology, compared to the to the hadron-level QGSJET II predictions, broken down into the non-diffractive (ND), central diffractive (CD), single diffractive (SD) and double diffractive (DD) components. Forward Rapidity Gap definition: $|\eta| < 2.5$: $p_{T}^{track} < 200$ MeV and $\sum \limits_{bin} E^{PF} < 6$ GeV $|\eta| \in [2.5,3.0]$: $\sum \limits_{bin} E_{neutral}^{PF} < 13.4$ GeV $|\eta| > 3.0$: No particles

Unfolded diffractive enhanced differential cross section spectla for events with Pomeron-Proton ($\mathrm{I\!P}\mathrm{p} + \gamma \mathrm{p}$) topology, compared to the to the hadron-level QGSJET II predictions, broken down into the non-diffractive (ND), central diffractive (CD), single diffractive (SD) and double diffractive (DD) components. Forward Rapidity Gap definition: $|\eta| < 2.5$: $p_{T}^{track} < 200$ MeV and $\sum \limits_{bin} E^{PF} < 6$ GeV $|\eta| \in [2.5,3.0]$: $\sum \limits_{bin} E_{neutral}^{PF} < 13.4$ GeV $|\eta| > 3.0$: No particles

Reconstruction level diffraction enhanced differential cross section spectrum for Pomeron-Proton ($\mathrm{I\!P}\mathrm{p} + \gamma \mathrm{p}$) topology corrected for the contribution from events with undetectable energy in the HF calorimeter adjacent to the rapidity gap, compared with the spectrum obtained with events satisfying the ZDC veto requirement $E_{ZDC−} < 1 \mathrm{~TeV}$ which selects only the events without lead nuclear break up (without correction for HF undetectable energy). Forward Rapidity Gap definition: $|\eta| < 2.5$: $p_{T}^{track} < 200$ MeV and $\sum \limits_{bin} E^{PF} < 6$ GeV $|\eta| \in [2.5,3.0]$: $\sum \limits_{bin} E_{neutral}^{PF} < 13.4$ GeV $|\eta| > 3.0$: No particles

Ratio of measured PSI(2S) over J/PSI(1S) cross section in charged-particle multiplicity intervals and integrated in multiplicity.

Ratio of measured PSI(2S) over J/PSI(1S) cross section in charged-particle multiplicity intervals and integrated in multiplicity.

Ratio of measured PSI(2S) over J/PSI(1S) cross section in charged-particle multiplicity intervals and integrated in multiplicity.

The measured cross section as a function of exclusive jet multiplicity, $N_{\text{jets}}$, when $50<p_T<100$ GeV

The measured cross section as a function of exclusive jet multiplicity, $N_{\text{jets}}$, when $p_T>100$ GeV

The measured cross section as a function of $\Delta\phi_{Z,jet1}$, when $p_T<10$ GeV

The measured cross section as a function of $\Delta\phi_{Z,jet1}$, when $10<p_T<30$ GeV

The measured cross section as a function of $\Delta\phi_{Z,jet1}$, when $30<p_T<50$ GeV

The measured cross section as a function of $\Delta\phi_{Z,jet1}$, when $50<p_T<100$ GeV

The measured cross section as a function of $\Delta\phi_{Z,jet1}$, when $p_T>100$ GeV

The measured cross section as a function of $\Delta\phi_{jet1,jet2}$, when $p_T<10$ GeV

The measured cross section as a function of $\Delta\phi_{jet1,jet2}$, when $10<p_T<30$ GeV

The measured cross section as a function of $\Delta\phi_{jet1,jet2}$, when $30<p_T<50$ GeV

The measured cross section as a function of $\Delta\phi_{jet1,jet2}$, when $50<p_T<100$ GeV

The measured cross section as a function of $\Delta\phi_{jet1,jet2}$, when $p_T>100$ GeV

Limits on anomalous magnetic moment of the tau lepton

Mean $p_T$ values of the $\Upsilon(1$S$)$, $\Upsilon(2$S$)$, and $\Upsilon(3$S$)$ states with $p_T\,>\,0\,GeV$ and $|y|\,<\,1.2$ as a function of track multiplicity $N_{track}$

Ratio $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ with $|y|\,<\,1.2$ as a function of track multiplicity $N_{track}$ in $0<p_T<5\,$GeV range

Ratio $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ with $|y|\,<\,1.2$ as a function of track multiplicity $N_{track}$ in $5<p_T<7\,$GeV range

Ratio $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ with $|y|\,<\,1.2$ as a function of track multiplicity $N_{track}$ in $7<p_T<9\,$GeV range

Ratio $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ with $|y|\,<\,1.2$ as a function of track multiplicity $N_{track}$ in $9<p_T<11\,$GeV range

Ratio $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ with $|y|\,<\,1.2$ as a function of track multiplicity $N_{track}$ in $11<p_T<15\,$GeV range

Ratio $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ with $|y|\,<\,1.2$ as a function of track multiplicity $N_{track}$ in $15<p_T<20\,$GeV range

Ratio $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ with $|y|\,<\,1.2$ as a function of track multiplicity $N_{track}$ in $20<p_T<50\,$GeV range

Ratio $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ with $|y|\,<\,1.2$ as a function of track multiplicity $N_{track}$ in $0<p_T<5\,$GeV range

Ratio $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ with $|y|\,<\,1.2$ as a function of track multiplicity $N_{track}$ in $5<p_T<7\,$GeV range

Ratio $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ with $|y|\,<\,1.2$ as a function of track multiplicity $N_{track}$ in $7<p_T<9\,$GeV range

Ratio $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ with $|y|\,<\,1.2$ as a function of track multiplicity $N_{track}$ in $9<p_T<11\,$GeV range

Ratio $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ with $|y|\,<\,1.2$ as a function of track multiplicity $N_{track}$ in $11<p_T<15\,$GeV range

Ratio $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ with $|y|\,<\,1.2$ as a function of track multiplicity $N_{track}$ in $15<p_T<20\,$GeV range

Ratio $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ with $|y|\,<\,1.2$ as a function of track multiplicity $N_{track}$ in $20<p_T<50\,$GeV range

Ratios $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ and $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ as functions of "forward" track multiplicity $N_{track}^{\Delta\phi}$ for $\Upsilon(n$S$)$ states with $p_T\,>\,7\,GeV$ and $|y|\,<\,1.2$. Forward tracks are those with momentum direction in $\Delta\phi\,<\,\pi/3$ w.r.t. the $\Upsilon(n$S$)$ momentum direction.

Ratios $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ and $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ as functions of "transverse" track multiplicity $N_{track}^{\Delta\phi}$ for $\Upsilon(n$S$)$ states with $p_T\,>\,7\,GeV$ and $|y|\,<\,1.2$. Transverse tracks are those with momentum direction in $\pi/3\,<\,\Delta\phi\,<\,2\pi/3$ w.r.t. the $\Upsilon(n$S$)$ momentum direction.

Ratios $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ and $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ as functions of "backward" track multiplicity $N_{track}^{\Delta\phi}$ for $\Upsilon(n$S$)$ states with $p_T\,>\,7\,GeV$ and $|y|\,<\,1.2$. Backward tracks are those with momentum direction in $\Delta\phi\,>\,2\pi/3$ w.r.t. the $\Upsilon(n$S$)$ momentum direction.

Ratios $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ and $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ as functions of track multiplicity $N_{track}$ for $\Upsilon(n$S$)$ states with $p_T\,>\,7\,GeV$ and $|y|\,<\,1.2$ and $N^{\Delta R}_{track}\,=\,0$ charged particles produced in $\Delta R\,<\,0.5$ cone around $\Upsilon(n$S$)$ momentum direction.

Ratios $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ and $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ as functions of track multiplicity $N_{track}$ for $\Upsilon(n$S$)$ states with $p_T\,>\,7\,GeV$ and $|y|\,<\,1.2$ and $N^{\Delta R}_{track}\,=\,1$ charged particles produced in $\Delta R\,<\,0.5$ cone around $\Upsilon(n$S$)$ momentum direction.

Ratios $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ and $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ as functions of track multiplicity $N_{track}$ for $\Upsilon(n$S$)$ states with $p_T\,>\,7\,GeV$ and $|y|\,<\,1.2$ and $N^{\Delta R}_{track}\,=\,2$ charged particles produced in $\Delta R\,<\,0.5$ cone around $\Upsilon(n$S$)$ momentum direction.

Ratios $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ and $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ as functions of track multiplicity $N_{track}$ for $\Upsilon(n$S$)$ states with $p_T\,>\,7\,GeV$ and $|y|\,<\,1.2$ and $N^{\Delta R}_{track}\,>\,2$ charged particles produced in $\Delta R\,<\,0.5$ cone around $\Upsilon(n$S$)$ momentum direction.

Ratios $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ and $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ as functions of track multiplicity $N_{track}$ in transverse sphericity bin $0.00\,<\,S_T\,<\,0.55$ for $\Upsilon(n$S$)$ states with $p_T\,>\,7\,GeV$ and $|y|\,<\,1.2$.

Ratios $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ and $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ as functions of track multiplicity $N_{track}$ in transverse sphericity bin $0.55\,<\,S_T\,<\,0.70$ for $\Upsilon(n$S$)$ states with $p_T\,>\,7\,GeV$ and $|y|\,<\,1.2$.

Ratios $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ and $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ as functions of track multiplicity $N_{track}$ in transverse sphericity bin $0.70\,<\,S_T\,<\,0.85$ for $\Upsilon(n$S$)$ states with $p_T\,>\,7\,GeV$ and $|y|\,<\,1.2$.

Ratios $\Upsilon(2$S$)\,/\,\Upsilon(1$S$)$ and $\Upsilon(3$S$)\,/\,\Upsilon(1$S$)$ as functions of track multiplicity $N_{track}$ in transverse sphericity bin $0.85\,<\,S_T\,<\,1.00$ for $\Upsilon(n$S$)$ states with $p_T\,>\,7\,GeV$ and $|y|\,<\,1.2$.

Efficiency-corrected multiplicity bins used in the $\Upsilon(n$S$)$ ratio analysis and the corresponding mean number of charged particle tracks.

Measured DPS effective cross section

pp -> J/psi J/psi J/psi X cross section

$pp \rightarrow J/\psi J/\psi J/\psi X~$ fiducial cross section

Ratio of $p_{\mathrm{T,ch\ jet}}$-differential cross section of charm jets tagged with $\mathrm{D^{0}}$ mesons for different $R$: $\sigma(R=0.2)/\sigma(R=0.4)$ and $\sigma(R=0.2)/\sigma(R=0.6)$ in pp collisions at $\sqrt{s}=13$ TeV.

Ratio of $p_{\mathrm{T,ch\ jet}}$-differential cross section of charm jets tagged with $\mathrm{D^{0}}$ mesons for different $R$: $\sigma(R=0.2)/\sigma(R=0.4)$ and $\sigma(R=0.2)/\sigma(R=0.6)$ in pp collisions at $\sqrt{s}=5.02$ TeV.

The fraction of $\mathrm{D^{0}}$ jets over inclusive charged-particle jets in pp collisions at $\sqrt{s}=5.02$ TeV for $R=0.2$, $0.4$, and $0.6$.

Distributions of $z^{\mathrm{ch}}_{||}$-differential yield of charm jets tagged with $\mathrm{D^{0}}$ mesons normalised by the number of $\mathrm{D^{0}}$ jets within each distribution in pp collisions at $\sqrt{s}=13$ TeV in four jet-$p_{\mathrm{T}}$ intervals $5<p_{\mathrm{T,ch\ jet}}<7$ GeV/$c$, $7<p_{\mathrm{T,ch\ jet}}<10$ GeV/$c$, $10<p_{\mathrm{T,ch\ jet}}<15$ GeV/$c$, and $15<p_{\mathrm{T,ch\ jet}}<50$ GeV/$c$ for jet radii $R=0.2$, $0.4$, and $0.6$.

Distributions of $z^{\mathrm{ch}}_{||}$-differential yield of charm jets tagged with $\mathrm{D^{0}}$ mesons normalised by the number of $\mathrm{D^{0}}$ jets within each distribution in pp collisions at $\sqrt{s}=5.02$ TeV in four jet-$p_{\mathrm{T}}$ intervals $5<p_{\mathrm{T,ch\ jet}}<7$ GeV/$c$, $7<p_{\mathrm{T,ch\ jet}}<10$ GeV/$c$, $10<p_{\mathrm{T,ch\ jet}}<15$ GeV/$c$, and $15<p_{\mathrm{T,ch\ jet}}<50$ GeV/$c$ for jet radii $R=0.2$, $0.4$, and $0.6$.

$p_{\mathrm{T,ch\ jet}}$-differential cross section of charm jets tagged with $\mathrm{D^{0}}$ mesons for $R=0.3$ in pp collisions at $\sqrt{s}=5.02$ TeV.

The fraction of $\mathrm{D^{0}}$ jets over inclusive charged-particle jets in pp collisions at $\sqrt{s}=5.02$ TeV for $R=0.3$.

Distributions of $z^{\mathrm{ch}}_{||}$-differential yield of charm jets tagged with $\mathrm{D^{0}}$ mesons normalised by the number of $\mathrm{D^{0}}$ jets within each distribution in pp collisions at $\sqrt{s}=5.02$ TeV in four jet-$p_{\mathrm{T}}$ intervals $5<p_{\mathrm{T,ch\ jet}}<7$ GeV/$c$, $7<p_{\mathrm{T,ch\ jet}}<10$ GeV/$c$, $10<p_{\mathrm{T,ch\ jet}}<15$ GeV/$c$, and $15<p_{\mathrm{T,ch\ jet}}<50$ GeV/$c$ for jet radius $R=0.3$.

Expected and observed $95\%\text{ CL}$ upper limits on the product of the cross sections and branching fraction for the decay into $\tau$ leptons for $bb\phi$ production in a mass range of $60\leq m_\phi\leq 3500\text{ GeV}$, in addition to $\text{H}(125)$. The central $68$ and $95\%$ intervals are given in addition to the expected median value. In this case, $gg\phi$ production rate has been fixed to zero. Numerical values provided in this table correspond to Figure 38 of the auxilliary material of the publication.

Expected and observed $95\%\text{ CL}$ upper limits on the product of the cross sections and branching fraction for the decay into $\tau$ leptons for $gg\phi$ production in a mass range of $60\leq m_\phi\leq 3500\text{ GeV}$, in addition to $\text{H}(125)$. The central $68$ and $95\%$ intervals are given in addition to the expected median value. In this case, $bb\phi$ production rate has been profiled and only top quarks have been considered in the $gg\phi$ loop. Numerical values provided in this table correspond to Figure 39 of the auxilliary material of the publication.

Expected and observed $95\%\text{ CL}$ upper limits on the product of the cross sections and branching fraction for the decay into $\tau$ leptons for $gg\phi$ production in a mass range of $60\leq m_\phi\leq 3500\text{ GeV}$, in addition to $\text{H}(125)$. The central $68$ and $95\%$ intervals are given in addition to the expected median value. In this case, $bb\phi$ production rate has been profiled and only bottom quarks have been considered in the $gg\phi$ loop. Numerical values provided in this table correspond to Figure 40 of the auxilliary material of the publication.

Local significance for a $gg\phi$ signal in a mass range of $60\leq m_\phi\leq 3500\text{ GeV}$. In this case, $bb\phi$ production rate has been profiled. Numerical values provided in this table correspond to Figure 31 of the auxilliary material of the publication.

Local significance for a $bb\phi$ signal in a mass range of $60\leq m_\phi\leq 3500\text{ GeV}$. In this case, $gg\phi$ production rate has been profiled. Numerical values provided in this table correspond to Figure 32 of the auxilliary material of the publication.

Local significance for a $gg\phi$ signal in a mass range of $60\leq m_\phi\leq 3500\text{ GeV}$. In this case, $bb\phi$ production rate has been fixed to zero. Numerical values provided in this table correspond to Figure 33 of the auxilliary material of the publication.

Local significance for a $bb\phi$ signal in a mass range of $60\leq m_\phi\leq 3500\text{ GeV}$. In this case, $gg\phi$ production rate has been fixed to zero. Numerical values provided in this table correspond to Figure 34 of the auxilliary material of the publication.

Local significance for a $gg\phi$ signal in a mass range of $60\leq m_\phi\leq 3500\text{ GeV}$. In this case, $bb\phi$ production rate has been profiled and only top quarks have been considered in the $gg\phi$ loop. Numerical values provided in this table correspond to Figure 35 of the auxilliary material of the publication.

Local significance for a $gg\phi$ signal in a mass range of $60\leq m_\phi\leq 3500\text{ GeV}$. In this case, $bb\phi$ production rate has been profiled and only bottom quarks have been considered in the $gg\phi$ loop. Numerical values provided in this table correspond to Figure 36 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $95\text{ GeV}$, produced via gluon-fusion ($gg\phi$), via vector boson fusion ($qq\phi$) or in association with b quarks ($bb\phi$). In this case, $bb\phi$ production rate is profiled, whereas the scan is performed in the $gg\phi$ and $qq\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 64 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a scalar resonance ($H$) with a mass of $60\text{ GeV}$, produced via gluon-fusion or in association with b quarks. For this scan, we assume the $ggH$ and $bbH$ processes are only influenced by the Yukawa couplings to the top and bottom quarks and we scale the cross sections predicted for a SM-like Higgs boson of the same mass depending on these couplings. The scans are displayed for the product of the reduced Yukawa couplings $g_{b,\,t}^{H}$ and the square root of the branching fraction for the $H\rightarrow\tau\tau$ decay process, where the former is defined as the ratio of the Yukawa coupling of $H$ to the Yukawa coupling expected for a SM-like Higgs boson. Numerical values provided in this table correspond to Figure 65 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a pseudoscalar resonance ($A$) with a mass of $60\text{ GeV}$, produced via gluon-fusion or in association with b quarks. For this scan, we assume the $ggA$ and $bbA$ processes are only influenced by the Yukawa couplings to the top and bottom quarks and we scale the cross sections predicted for a SM-like Higgs boson of the same mass depending on these couplings. For the $ggA$ process, there is also an enhancement to the cross section for a pseudoscalar resonance compared to the equivalent process for the production of a scalar. This enhancement is taken into account when scaling the cross sections for the SM-like Higgs boson. The scans are displayed for the product of the reduced Yukawa couplings $g_{b,\,t}^{A}$ and the square root of the branching fraction for the $A\rightarrow\tau\tau$ decay process, where the former is defined as the ratio of the Yukawa coupling of $A$ to the Yukawa coupling expected for a SM-like Higgs boson. Numerical values provided in this table correspond to Figure 66 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a scalar resonance ($H$) with a mass of $80\text{ GeV}$, produced via gluon-fusion or in association with b quarks. For this scan, we assume the $ggH$ and $bbH$ processes are only influenced by the Yukawa couplings to the top and bottom quarks and we scale the cross sections predicted for a SM-like Higgs boson of the same mass depending on these couplings. The scans are displayed for the product of the reduced Yukawa couplings $g_{b,\,t}^{H}$ and the square root of the branching fraction for the $H\rightarrow\tau\tau$ decay process, where the former is defined as the ratio of the Yukawa coupling of $H$ to the Yukawa coupling expected for a SM-like Higgs boson. Numerical values provided in this table correspond to Figure 67 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a pseudoscalar resonance ($A$) with a mass of $80\text{ GeV}$, produced via gluon-fusion or in association with b quarks. For this scan, we assume the $ggA$ and $bbA$ processes are only influenced by the Yukawa couplings to the top and bottom quarks and we scale the cross sections predicted for a SM-like Higgs boson of the same mass depending on these couplings. For the $ggA$ process, there is also an enhancement to the cross section for a pseudoscalar resonance compared to the equivalent process for the production of a scalar. This enhancement is taken into account when scaling the cross sections for the SM-like Higgs boson. The scans are displayed for the product of the reduced Yukawa couplings $g_{b,\,t}^{A}$ and the square root of the branching fraction for the $A\rightarrow\tau\tau$ decay process, where the former is defined as the ratio of the Yukawa coupling of $A$ to the Yukawa coupling expected for a SM-like Higgs boson. Numerical values provided in this table correspond to Figure 68 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a scalar resonance ($H$) with a mass of $95\text{ GeV}$, produced via gluon-fusion or in association with b quarks. For this scan, we assume the $ggH$ and $bbH$ processes are only influenced by the Yukawa couplings to the top and bottom quarks and we scale the cross sections predicted for a SM-like Higgs boson of the same mass depending on these couplings. The scans are displayed for the product of the reduced Yukawa couplings $g_{b,\,t}^{H}$ and the square root of the branching fraction for the $H\rightarrow\tau\tau$ decay process, where the former is defined as the ratio of the Yukawa coupling of $H$ to the Yukawa coupling expected for a SM-like Higgs boson. Numerical values provided in this table correspond to Figure 69 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a pseudoscalar resonance ($A$) with a mass of $95\text{ GeV}$, produced via gluon-fusion or in association with b quarks. For this scan, we assume the $ggA$ and $bbA$ processes are only influenced by the Yukawa couplings to the top and bottom quarks and we scale the cross sections predicted for a SM-like Higgs boson of the same mass depending on these couplings. For the $ggA$ process, there is also an enhancement to the cross section for a pseudoscalar resonance compared to the equivalent process for the production of a scalar. This enhancement is taken into account when scaling the cross sections for the SM-like Higgs boson. The scans are displayed for the product of the reduced Yukawa couplings $g_{b,\,t}^{A}$ and the square root of the branching fraction for the $A\rightarrow\tau\tau$ decay process, where the former is defined as the ratio of the Yukawa coupling of $A$ to the Yukawa coupling expected for a SM-like Higgs boson. Numerical values provided in this table correspond to Figure 70 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a scalar resonance ($H$) with a mass of $100\text{ GeV}$, produced via gluon-fusion or in association with b quarks. For this scan, we assume the $ggH$ and $bbH$ processes are only influenced by the Yukawa couplings to the top and bottom quarks and we scale the cross sections predicted for a SM-like Higgs boson of the same mass depending on these couplings. The scans are displayed for the product of the reduced Yukawa couplings $g_{b,\,t}^{H}$ and the square root of the branching fraction for the $H\rightarrow\tau\tau$ decay process, where the former is defined as the ratio of the Yukawa coupling of $H$ to the Yukawa coupling expected for a SM-like Higgs boson. Numerical values provided in this table correspond to Figure 71 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a pseudoscalar resonance ($A$) with a mass of $100\text{ GeV}$, produced via gluon-fusion or in association with b quarks. For this scan, we assume the $ggA$ and $bbA$ processes are only influenced by the Yukawa couplings to the top and bottom quarks and we scale the cross sections predicted for a SM-like Higgs boson of the same mass depending on these couplings. For the $ggA$ process, there is also an enhancement to the cross section for a pseudoscalar resonance compared to the equivalent process for the production of a scalar. This enhancement is taken into account when scaling the cross sections for the SM-like Higgs boson. The scans are displayed for the product of the reduced Yukawa couplings $g_{b,\,t}^{A}$ and the square root of the branching fraction for the $A\rightarrow\tau\tau$ decay process, where the former is defined as the ratio of the Yukawa coupling of $A$ to the Yukawa coupling expected for a SM-like Higgs boson. Numerical values provided in this table correspond to Figure 72 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a scalar resonance ($H$) with a mass of $120\text{ GeV}$, produced via gluon-fusion or in association with b quarks. For this scan, we assume the $ggH$ and $bbH$ processes are only influenced by the Yukawa couplings to the top and bottom quarks and we scale the cross sections predicted for a SM-like Higgs boson of the same mass depending on these couplings. The scans are displayed for the product of the reduced Yukawa couplings $g_{b,\,t}^{H}$ and the square root of the branching fraction for the $H\rightarrow\tau\tau$ decay process, where the former is defined as the ratio of the Yukawa coupling of $H$ to the Yukawa coupling expected for a SM-like Higgs boson. Numerical values provided in this table correspond to Figure 73 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a pseudoscalar resonance ($A$) with a mass of $120\text{ GeV}$, produced via gluon-fusion or in association with b quarks. For this scan, we assume the $ggA$ and $bbA$ processes are only influenced by the Yukawa couplings to the top and bottom quarks and we scale the cross sections predicted for a SM-like Higgs boson of the same mass depending on these couplings. For the $ggA$ process, there is also an enhancement to the cross section for a pseudoscalar resonance compared to the equivalent process for the production of a scalar. This enhancement is taken into account when scaling the cross sections for the SM-like Higgs boson. The scans are displayed for the product of the reduced Yukawa couplings $g_{b,\,t}^{A}$ and the square root of the branching fraction for the $A\rightarrow\tau\tau$ decay process, where the former is defined as the ratio of the Yukawa coupling of $A$ to the Yukawa coupling expected for a SM-like Higgs boson. Numerical values provided in this table correspond to Figure 74 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a scalar resonance ($H$) with a mass of $125\text{ GeV}$, produced via gluon-fusion or in association with b quarks. For this scan, we assume the $ggH$ and $bbH$ processes are only influenced by the Yukawa couplings to the top and bottom quarks and we scale the cross sections predicted for a SM-like Higgs boson of the same mass depending on these couplings. The scans are displayed for the product of the reduced Yukawa couplings $g_{b,\,t}^{H}$ and the square root of the branching fraction for the $H\rightarrow\tau\tau$ decay process, where the former is defined as the ratio of the Yukawa coupling of $H$ to the Yukawa coupling expected for a SM-like Higgs boson. Numerical values provided in this table correspond to Figure 75 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a pseudoscalar resonance ($A$) with a mass of $125\text{ GeV}$, produced via gluon-fusion or in association with b quarks. For this scan, we assume the $ggA$ and $bbA$ processes are only influenced by the Yukawa couplings to the top and bottom quarks and we scale the cross sections predicted for a SM-like Higgs boson of the same mass depending on these couplings. For the $ggA$ process, there is also an enhancement to the cross section for a pseudoscalar resonance compared to the equivalent process for the production of a scalar. This enhancement is taken into account when scaling the cross sections for the SM-like Higgs boson. The scans are displayed for the product of the reduced Yukawa couplings $g_{b,\,t}^{A}$ and the square root of the branching fraction for the $A\rightarrow\tau\tau$ decay process, where the former is defined as the ratio of the Yukawa coupling of $A$ to the Yukawa coupling expected for a SM-like Higgs boson. Numerical values provided in this table correspond to Figure 76 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a scalar resonance ($H$) with a mass of $130\text{ GeV}$, produced via gluon-fusion or in association with b quarks. For this scan, we assume the $ggH$ and $bbH$ processes are only influenced by the Yukawa couplings to the top and bottom quarks and we scale the cross sections predicted for a SM-like Higgs boson of the same mass depending on these couplings. The scans are displayed for the product of the reduced Yukawa couplings $g_{b,\,t}^{H}$ and the square root of the branching fraction for the $H\rightarrow\tau\tau$ decay process, where the former is defined as the ratio of the Yukawa coupling of $H$ to the Yukawa coupling expected for a SM-like Higgs boson. Numerical values provided in this table correspond to Figure 77 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a pseudoscalar resonance ($A$) with a mass of $130\text{ GeV}$, produced via gluon-fusion or in association with b quarks. For this scan, we assume the $ggA$ and $bbA$ processes are only influenced by the Yukawa couplings to the top and bottom quarks and we scale the cross sections predicted for a SM-like Higgs boson of the same mass depending on these couplings. For the $ggA$ process, there is also an enhancement to the cross section for a pseudoscalar resonance compared to the equivalent process for the production of a scalar. This enhancement is taken into account when scaling the cross sections for the SM-like Higgs boson. The scans are displayed for the product of the reduced Yukawa couplings $g_{b,\,t}^{A}$ and the square root of the branching fraction for the $A\rightarrow\tau\tau$ decay process, where the former is defined as the ratio of the Yukawa coupling of $A$ to the Yukawa coupling expected for a SM-like Higgs boson. Numerical values provided in this table correspond to Figure 78 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a scalar resonance ($H$) with a mass of $140\text{ GeV}$, produced via gluon-fusion or in association with b quarks. For this scan, we assume the $ggH$ and $bbH$ processes are only influenced by the Yukawa couplings to the top and bottom quarks and we scale the cross sections predicted for a SM-like Higgs boson of the same mass depending on these couplings. The scans are displayed for the product of the reduced Yukawa couplings $g_{b,\,t}^{H}$ and the square root of the branching fraction for the $H\rightarrow\tau\tau$ decay process, where the former is defined as the ratio of the Yukawa coupling of $H$ to the Yukawa coupling expected for a SM-like Higgs boson. Numerical values provided in this table correspond to Figure 79 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a pseudoscalar resonance ($A$) with a mass of $140\text{ GeV}$, produced via gluon-fusion or in association with b quarks. For this scan, we assume the $ggA$ and $bbA$ processes are only influenced by the Yukawa couplings to the top and bottom quarks and we scale the cross sections predicted for a SM-like Higgs boson of the same mass depending on these couplings. For the $ggA$ process, there is also an enhancement to the cross section for a pseudoscalar resonance compared to the equivalent process for the production of a scalar. This enhancement is taken into account when scaling the cross sections for the SM-like Higgs boson. The scans are displayed for the product of the reduced Yukawa couplings $g_{b,\,t}^{A}$ and the square root of the branching fraction for the $A\rightarrow\tau\tau$ decay process, where the former is defined as the ratio of the Yukawa coupling of $A$ to the Yukawa coupling expected for a SM-like Higgs boson. Numerical values provided in this table correspond to Figure 80 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a scalar resonance ($H$) with a mass of $160\text{ GeV}$, produced via gluon-fusion or in association with b quarks. For this scan, we assume the $ggH$ and $bbH$ processes are only influenced by the Yukawa couplings to the top and bottom quarks and we scale the cross sections predicted for a SM-like Higgs boson of the same mass depending on these couplings. The scans are displayed for the product of the reduced Yukawa couplings $g_{b,\,t}^{H}$ and the square root of the branching fraction for the $H\rightarrow\tau\tau$ decay process, where the former is defined as the ratio of the Yukawa coupling of $H$ to the Yukawa coupling expected for a SM-like Higgs boson. Numerical values provided in this table correspond to Figure 81 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a pseudoscalar resonance ($A$) with a mass of $160\text{ GeV}$, produced via gluon-fusion or in association with b quarks. For this scan, we assume the $ggA$ and $bbA$ processes are only influenced by the Yukawa couplings to the top and bottom quarks and we scale the cross sections predicted for a SM-like Higgs boson of the same mass depending on these couplings. For the $ggA$ process, there is also an enhancement to the cross section for a pseudoscalar resonance compared to the equivalent process for the production of a scalar. This enhancement is taken into account when scaling the cross sections for the SM-like Higgs boson. The scans are displayed for the product of the reduced Yukawa couplings $g_{b,\,t}^{A}$ and the square root of the branching fraction for the $A\rightarrow\tau\tau$ decay process, where the former is defined as the ratio of the Yukawa coupling of $A$ to the Yukawa coupling expected for a SM-like Higgs boson. Numerical values provided in this table correspond to Figure 82 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a scalar resonance ($H$) with a mass of $180\text{ GeV}$, produced via gluon-fusion or in association with b quarks. For this scan, we assume the $ggH$ and $bbH$ processes are only influenced by the Yukawa couplings to the top and bottom quarks and we scale the cross sections predicted for a SM-like Higgs boson of the same mass depending on these couplings. The scans are displayed for the product of the reduced Yukawa couplings $g_{b,\,t}^{H}$ and the square root of the branching fraction for the $H\rightarrow\tau\tau$ decay process, where the former is defined as the ratio of the Yukawa coupling of $H$ to the Yukawa coupling expected for a SM-like Higgs boson. Numerical values provided in this table correspond to Figure 83 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a pseudoscalar resonance ($A$) with a mass of $180\text{ GeV}$, produced via gluon-fusion or in association with b quarks. For this scan, we assume the $ggA$ and $bbA$ processes are only influenced by the Yukawa couplings to the top and bottom quarks and we scale the cross sections predicted for a SM-like Higgs boson of the same mass depending on these couplings. For the $ggA$ process, there is also an enhancement to the cross section for a pseudoscalar resonance compared to the equivalent process for the production of a scalar. This enhancement is taken into account when scaling the cross sections for the SM-like Higgs boson. The scans are displayed for the product of the reduced Yukawa couplings $g_{b,\,t}^{A}$ and the square root of the branching fraction for the $A\rightarrow\tau\tau$ decay process, where the former is defined as the ratio of the Yukawa coupling of $A$ to the Yukawa coupling expected for a SM-like Higgs boson. Numerical values provided in this table correspond to Figure 84 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a scalar resonance ($H$) with a mass of $200\text{ GeV}$, produced via gluon-fusion or in association with b quarks. For this scan, we assume the $ggH$ and $bbH$ processes are only influenced by the Yukawa couplings to the top and bottom quarks and we scale the cross sections predicted for a SM-like Higgs boson of the same mass depending on these couplings. The scans are displayed for the product of the reduced Yukawa couplings $g_{b,\,t}^{H}$ and the square root of the branching fraction for the $H\rightarrow\tau\tau$ decay process, where the former is defined as the ratio of the Yukawa coupling of $H$ to the Yukawa coupling expected for a SM-like Higgs boson. Numerical values provided in this table correspond to Figure 85 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a pseudoscalar resonance ($A$) with a mass of $200\text{ GeV}$, produced via gluon-fusion or in association with b quarks. For this scan, we assume the $ggA$ and $bbA$ processes are only influenced by the Yukawa couplings to the top and bottom quarks and we scale the cross sections predicted for a SM-like Higgs boson of the same mass depending on these couplings. For the $ggA$ process, there is also an enhancement to the cross section for a pseudoscalar resonance compared to the equivalent process for the production of a scalar. This enhancement is taken into account when scaling the cross sections for the SM-like Higgs boson. The scans are displayed for the product of the reduced Yukawa couplings $g_{b,\,t}^{A}$ and the square root of the branching fraction for the $A\rightarrow\tau\tau$ decay process, where the former is defined as the ratio of the Yukawa coupling of $A$ to the Yukawa coupling expected for a SM-like Higgs boson. Numerical values provided in this table correspond to Figure 86 of the auxilliary material of the publication.

Expected and observed $95\%\text{ CL}$ upper limits on $g_U$ in the VLQ BM 1 scenario in a mass range of $1\leq m_U\leq 5\text{ TeV}$. The central $68$ and $95\%$ intervals are given in addition to the expected median value. Numerical values provided in this table correspond to Figure 12a of the publication.

Expected and observed $95\%\text{ CL}$ upper limits on $g_U$ in the VLQ BM 2 scenario in a mass range of $1\leq m_U\leq 5\text{ TeV}$. The central $68$ and $95\%$ intervals are given in addition to the expected median value. Numerical values provided in this table correspond to Figure 12b of the publication.

Expected and observed $95\%\text{ CL}$ upper limits on $g_U$ in the VLQ BM 3 scenario in a mass range of $1\leq m_U\leq 5\text{ TeV}$. The central $68$ and $95\%$ intervals are given in addition to the expected median value. Numerical values provided in this table correspond to Figure 92 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $60\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 11a of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $80\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 41 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $95\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 42 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $100\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 11b of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $120\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 43 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $125\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 11c of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $130\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 44 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $140\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 45 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $160\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 11d of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $180\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 46 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $200\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 47 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $250\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 11e of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $300\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 48 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $350\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 49 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $400\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 50 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $450\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 51 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $500\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 11f of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $600\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 52 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $700\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 53 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $800\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 54 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $900\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 55 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $1000\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 11g of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $1200\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 11h of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $1400\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 56 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $1600\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 57 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $1800\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 58 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $2000\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 59 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $2300\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 60 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $2600\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 61 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $2900\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 62 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $3200\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 63 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $3500\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 11i of the publication.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $60\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 11a of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $80\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 41 of the auxilliary material of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $95\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 42 of the auxilliary material of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $100\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 11b of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $120\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 43 of the auxilliary material of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $125\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 11c of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $130\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 44 of the auxilliary material of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $140\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 45 of the auxilliary material of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $160\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 11d of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $180\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 46 of the auxilliary material of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $200\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 47 of the auxilliary material of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $250\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 11e of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $300\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 48 of the auxilliary material of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $350\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 49 of the auxilliary material of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $400\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 50 of the auxilliary material of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $450\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 51 of the auxilliary material of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $500\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 11f of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $600\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 52 of the auxilliary material of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $700\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 53 of the auxilliary material of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $800\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 54 of the auxilliary material of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $900\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 55 of the auxilliary material of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $1000\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 11g of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $1200\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 11h of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $1400\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 56 of the auxilliary material of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $1600\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 57 of the auxilliary material of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $1800\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 58 of the auxilliary material of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $2000\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 59 of the auxilliary material of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $2300\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 60 of the auxilliary material of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $2600\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 61 of the auxilliary material of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $2900\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 62 of the auxilliary material of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $3200\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 63 of the auxilliary material of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a resonance ($\phi$) with a mass of $3500\text{ GeV}$, produced via gluon-fusion ($gg\phi$) or in association with b quarks ($bb\phi$). The scan is performed in the $gg\phi$ and $bb\phi$ production cross-sections, both multiplied with the branching fraction for the $\phi\rightarrow\tau\tau$ decay process. Numerical values provided in this table correspond to Figure 11i of the publication, but evaluated on Asimov pseudodata.

Scan of the likelihood function for the search for a vector leptoquark with $m_{U} = 1\text{ TeV}$, in the VLQ BM 1 scenario. The scan is performed in the $g_{U}$ coupling, for three different categorization strategies, combining only "No b tag" categories, only "b tag" categories, and all categories. Numerical values provided in this table correspond to Figure 99 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a vector leptoquark with $m_{U} = 2\text{ TeV}$, in the VLQ BM 1 scenario. The scan is performed in the $g_{U}$ coupling, for three different categorization strategies, combining only "No b tag" categories, only "b tag" categories, and all categories. Numerical values provided in this table correspond to Figure 100 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a vector leptoquark with $m_{U} = 3\text{ TeV}$, in the VLQ BM 1 scenario. The scan is performed in the $g_{U}$ coupling, for three different categorization strategies, combining only "No b tag" categories, only "b tag" categories, and all categories. Numerical values provided in this table correspond to Figure 101 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a vector leptoquark with $m_{U} = 4\text{ TeV}$, in the VLQ BM 1 scenario. The scan is performed in the $g_{U}$ coupling, for three different categorization strategies, combining only "No b tag" categories, only "b tag" categories, and all categories. Numerical values provided in this table correspond to Figure 102 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a vector leptoquark with $m_{U} = 5\text{ TeV}$, in the VLQ BM 1 scenario. The scan is performed in the $g_{U}$ coupling, for three different categorization strategies, combining only "No b tag" categories, only "b tag" categories, and all categories. Numerical values provided in this table correspond to Figure 103 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a vector leptoquark with $m_{U} = 1\text{ TeV}$, in the VLQ BM 2 scenario. The scan is performed in the $g_{U}$ coupling, for three different categorization strategies, combining only "No b tag" categories, only "b tag" categories, and all categories. Numerical values provided in this table correspond to Figure 104 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a vector leptoquark with $m_{U} = 2\text{ TeV}$, in the VLQ BM 2 scenario. The scan is performed in the $g_{U}$ coupling, for three different categorization strategies, combining only "No b tag" categories, only "b tag" categories, and all categories. Numerical values provided in this table correspond to Figure 105 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a vector leptoquark with $m_{U} = 3\text{ TeV}$, in the VLQ BM 2 scenario. The scan is performed in the $g_{U}$ coupling, for three different categorization strategies, combining only "No b tag" categories, only "b tag" categories, and all categories. Numerical values provided in this table correspond to Figure 106 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a vector leptoquark with $m_{U} = 4\text{ TeV}$, in the VLQ BM 2 scenario. The scan is performed in the $g_{U}$ coupling, for three different categorization strategies, combining only "No b tag" categories, only "b tag" categories, and all categories. Numerical values provided in this table correspond to Figure 107 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a vector leptoquark with $m_{U} = 5\text{ TeV}$, in the VLQ BM 2 scenario. The scan is performed in the $g_{U}$ coupling, for three different categorization strategies, combining only "No b tag" categories, only "b tag" categories, and all categories. Numerical values provided in this table correspond to Figure 108 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a vector leptoquark with $m_{U} = 1\text{ TeV}$, in the VLQ BM 3 scenario. The scan is performed in the $g_{U}$ coupling, for three different categorization strategies, combining only "No b tag" categories, only "b tag" categories, and all categories. Numerical values provided in this table correspond to Figure 109 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a vector leptoquark with $m_{U} = 2\text{ TeV}$, in the VLQ BM 3 scenario. The scan is performed in the $g_{U}$ coupling, for three different categorization strategies, combining only "No b tag" categories, only "b tag" categories, and all categories. Numerical values provided in this table correspond to Figure 110 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a vector leptoquark with $m_{U} = 3\text{ TeV}$, in the VLQ BM 3 scenario. The scan is performed in the $g_{U}$ coupling, for three different categorization strategies, combining only "No b tag" categories, only "b tag" categories, and all categories. Numerical values provided in this table correspond to Figure 111 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a vector leptoquark with $m_{U} = 4\text{ TeV}$, in the VLQ BM 3 scenario. The scan is performed in the $g_{U}$ coupling, for three different categorization strategies, combining only "No b tag" categories, only "b tag" categories, and all categories. Numerical values provided in this table correspond to Figure 112 of the auxilliary material of the publication.

Scan of the likelihood function for the search for a vector leptoquark with $m_{U} = 5\text{ TeV}$, in the VLQ BM 3 scenario. The scan is performed in the $g_{U}$ coupling, for three different categorization strategies, combining only "No b tag" categories, only "b tag" categories, and all categories. Numerical values provided in this table correspond to Figure 113 of the auxilliary material of the publication.

Observed $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h}^{125}$ scenario. Numerical values provided in this table correspond to the observed contour of Figure 13a of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h}^{125}$ scenario, evaluated at the median of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. Numerical values provided in this table correspond to the expected median contour of Figure 13a of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h}^{125}$ scenario, evaluated at the $16\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $68\%$ confidence interval band. Numerical values provided in this table correspond to the expected $16\%$ quantile contour of Figure 13a of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h}^{125}$ scenario, evaluated at the $84\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $68\%$ confidence interval band. Numerical values provided in this table correspond to the expected $84\%$ quantile contour of Figure 13a of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h}^{125}$ scenario, evaluated at the $2.5\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $95\%$ confidence interval band. Numerical values provided in this table correspond to the expected $2.5\%$ quantile contour of Figure 13a of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h}^{125}$ scenario, evaluated at the $97.5\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $95\%$ confidence interval band. Numerical values provided in this table correspond to the expected $97.5\%$ quantile contour of Figure 13a of the publication.

Observed $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h,\,\text{EFT}}^{125}$ scenario. Numerical values provided in this table correspond to the observed contour of Figure 13b of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h,\,\text{EFT}}^{125}$ scenario, evaluated at the median of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. Numerical values provided in this table correspond to the expected median contour of Figure 13b of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h,\,\text{EFT}}^{125}$ scenario, evaluated at the $16\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $68\%$ confidence interval band. Numerical values provided in this table correspond to the expected $16\%$ quantile contour of Figure 13b of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h,\,\text{EFT}}^{125}$ scenario, evaluated at the $84\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $68\%$ confidence interval band. Numerical values provided in this table correspond to the expected $84\%$ quantile contour of Figure 13b of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h,\,\text{EFT}}^{125}$ scenario, evaluated at the $2.5\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $95\%$ confidence interval band. Numerical values provided in this table correspond to the expected $2.5\%$ quantile contour of Figure 13b of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h,\,\text{EFT}}^{125}$ scenario, evaluated at the $97.5\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $95\%$ confidence interval band. Numerical values provided in this table correspond to the expected $97.5\%$ quantile contour of Figure 13b of the publication.

Observed $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h}^{125}(\tilde{\tau})$ scenario. Numerical values provided in this table correspond to the observed contour of Figure 114 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h}^{125}(\tilde{\tau})$ scenario, evaluated at the median of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. Numerical values provided in this table correspond to the expected median contour of Figure 114 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h}^{125}(\tilde{\tau})$ scenario, evaluated at the $16\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $68\%$ confidence interval band. Numerical values provided in this table correspond to the expected $16\%$ contour of Figure 114 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h}^{125}(\tilde{\tau})$ scenario, evaluated at the $84\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $68\%$ confidence interval band. Numerical values provided in this table correspond to the expected $84\%$ contour of Figure 114 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h}^{125}(\tilde{\tau})$ scenario, evaluated at the $2.5\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $95\%$ confidence interval band. Numerical values provided in this table correspond to the expected $2.5\%$ contour of Figure 114 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h}^{125}(\tilde{\tau})$ scenario, evaluated at the $97.5\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $95\%$ confidence interval band. Numerical values provided in this table correspond to the expected $97.5\%$ contour of Figure 114 of the auxilliary material of the publication.

Observed $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h}^{125}(\tilde{\chi})$ scenario. Numerical values provided in this table correspond to the observed contour of Figure 115 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h}^{125}(\tilde{\chi})$ scenario, evaluated at the median of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. Numerical values provided in this table correspond to the expected median contour of Figure 115 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h}^{125}(\tilde{\chi})$ scenario, evaluated at the $16\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $68\%$ confidence interval band. Numerical values provided in this table correspond to the expected $16\%$ contour of Figure 115 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h}^{125}(\tilde{\chi})$ scenario, evaluated at the $84\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $68\%$ confidence interval band. Numerical values provided in this table correspond to the expected $84\%$ contour of Figure 115 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h}^{125}(\tilde{\chi})$ scenario, evaluated at the $2.5\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $95\%$ confidence interval band. Numerical values provided in this table correspond to the expected $2.5\%$ contour of Figure 115 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h}^{125}(\tilde{\chi})$ scenario, evaluated at the $97.5\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $95\%$ confidence interval band. Numerical values provided in this table correspond to the expected $97.5\%$ contour of Figure 115 of the auxilliary material of the publication.

Observed $95\%\text{ CL}$ exclusion contour in the MSSM $M_h^{125\,\mu_{1}-}$ scenario. Numerical values provided in this table correspond to the observed contour of Figure 116 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_h^{125\,\mu_{1}-}$ scenario, evaluated at the median of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. Numerical values provided in this table correspond to the expected median contour of Figure 116 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_h^{125\,\mu_{1}-}$ scenario, evaluated at the $16\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $68\%$ confidence interval band. Numerical values provided in this table correspond to the expected $16\%$ contour of Figure 116 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_h^{125\,\mu_{1}-}$ scenario, evaluated at the $84\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $68\%$ confidence interval band. Numerical values provided in this table correspond to the expected $84\%$ contour of Figure 116 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_h^{125\,\mu_{1}-}$ scenario, evaluated at the $2.5\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $95\%$ confidence interval band. Numerical values provided in this table correspond to the expected $2.5\%$ contour of Figure 116 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_h^{125\,\mu_{1}-}$ scenario, evaluated at the $97.5\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $95\%$ confidence interval band. Numerical values provided in this table correspond to the expected $97.5\%$ contour of Figure 116 of the auxilliary material of the publication.

Observed $95\%\text{ CL}$ exclusion contour in the MSSM $M_h^{125\,\mu_{2}-}$ scenario. Numerical values provided in this table correspond to the observed contour of Figure 117 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_h^{125\,\mu_{2}-}$ scenario, evaluated at the median of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. Numerical values provided in this table correspond to the expected median contour of Figure 117 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_h^{125\,\mu_{2}-}$ scenario, evaluated at the $16\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $68\%$ confidence interval band. Numerical values provided in this table correspond to the expected $16\%$ contour of Figure 117 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_h^{125\,\mu_{2}-}$ scenario, evaluated at the $84\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $68\%$ confidence interval band. Numerical values provided in this table correspond to the expected $84\%$ contour of Figure 117 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_h^{125\,\mu_{2}-}$ scenario, evaluated at the $2.5\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $95\%$ confidence interval band. Numerical values provided in this table correspond to the expected $2.5\%$ contour of Figure 117 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_h^{125\,\mu_{2}-}$ scenario, evaluated at the $97.5\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $95\%$ confidence interval band. Numerical values provided in this table correspond to the expected $97.5\%$ contour of Figure 117 of the auxilliary material of the publication.

Observed $95\%\text{ CL}$ exclusion contour in the MSSM $M_h^{125\,\mu_{3}-}$ scenario. Numerical values provided in this table correspond to the observed contour of Figure 118 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_h^{125\,\mu_{3}-}$ scenario, evaluated at the median of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. Numerical values provided in this table correspond to the expected median contour of Figure 118 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_h^{125\,\mu_{3}-}$ scenario, evaluated at the $16\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $68\%$ confidence interval band. Numerical values provided in this table correspond to the expected $16\%$ contour of Figure 118 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_h^{125\,\mu_{3}-}$ scenario, evaluated at the $84\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $68\%$ confidence interval band. Numerical values provided in this table correspond to the expected $84\%$ contour of Figure 118 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_h^{125\,\mu_{3}-}$ scenario, evaluated at the $2.5\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $95\%$ confidence interval band. Numerical values provided in this table correspond to the expected $2.5\%$ contour of Figure 118 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_h^{125\,\mu_{3}-}$ scenario, evaluated at the $97.5\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $95\%$ confidence interval band. Numerical values provided in this table correspond to the expected $97.5\%$ contour of Figure 118 of the auxilliary material of the publication.

Observed $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h_{1}}^{125}(CPV)$ scenario. Numerical values provided in this table correspond to the observed contour of Figure 119 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h_{1}}^{125}(CPV)$ scenario, evaluated at the median of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. Numerical values provided in this table correspond to the expected median contour of Figure 119 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h_{1}}^{125}(CPV)$ scenario, evaluated at the $16\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $68\%$ confidence interval band. Numerical values provided in this table correspond to the expected $16\%$ contour of Figure 119 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h_{1}}^{125}(CPV)$ scenario, evaluated at the $84\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $68\%$ confidence interval band. Numerical values provided in this table correspond to the expected $84\%$ contour of Figure 119 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h_{1}}^{125}(CPV)$ scenario, evaluated at the $2.5\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $95\%$ confidence interval band. Numerical values provided in this table correspond to the expected $2.5\%$ contour of Figure 119 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h_{1}}^{125}(CPV)$ scenario, evaluated at the $97.5\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $95\%$ confidence interval band. Numerical values provided in this table correspond to the expected $97.5\%$ contour of Figure 119 of the auxilliary material of the publication.

Observed $95\%\text{ CL}$ exclusion contour in the MSSM hMSSM scenario. Numerical values provided in this table correspond to the observed contour of Figure 120 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM hMSSM scenario, evaluated at the median of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. Numerical values provided in this table correspond to the expected median contour of Figure 120 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM hMSSM scenario, evaluated at the $16\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $68\%$ confidence interval band. Numerical values provided in this table correspond to the expected $16\%$ contour of Figure 120 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM hMSSM scenario, evaluated at the $84\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $68\%$ confidence interval band. Numerical values provided in this table correspond to the expected $84\%$ contour of Figure 120 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM hMSSM scenario, evaluated at the $2.5\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $95\%$ confidence interval band. Numerical values provided in this table correspond to the expected $2.5\%$ contour of Figure 120 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM hMSSM scenario, evaluated at the $97.5\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $95\%$ confidence interval band. Numerical values provided in this table correspond to the expected $97.5\%$ contour of Figure 120 of the auxilliary material of the publication.

Observed $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h,\,\text{EFT}}^{125}(\tilde{\chi})$ scenario. Numerical values provided in this table correspond to the observed contour of Figure 122 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h,\,\text{EFT}}^{125}(\tilde{\chi})$ scenario, evaluated at the median of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. Numerical values provided in this table correspond to the expected median contour of Figure 122 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h,\,\text{EFT}}^{125}(\tilde{\chi})$ scenario, evaluated at the $16\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $68\%$ confidence interval band. Numerical values provided in this table correspond to the expected $16\%$ contour of Figure 122 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h,\,\text{EFT}}^{125}(\tilde{\chi})$ scenario, evaluated at the $84\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $68\%$ confidence interval band. Numerical values provided in this table correspond to the expected $84\%$ contour of Figure 122 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h,\,\text{EFT}}^{125}(\tilde{\chi})$ scenario, evaluated at the $2.5\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $95\%$ confidence interval band. Numerical values provided in this table correspond to the expected $2.5\%$ contour of Figure 122 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h,\,\text{EFT}}^{125}(\tilde{\chi})$ scenario, evaluated at the $97.5\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $95\%$ confidence interval band. Numerical values provided in this table correspond to the expected $97.5\%$ contour of Figure 122 of the auxilliary material of the publication.

Observed $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h}^{125}(\text{alignment})$ scenario. Numerical values provided in this table correspond to the observed contour of Figure 123 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h}^{125}(\text{alignment})$ scenario, evaluated at the median of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. Numerical values provided in this table correspond to the expected median contour of Figure 123 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h}^{125}(\text{alignment})$ scenario, evaluated at the $16\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $68\%$ confidence interval band. Numerical values provided in this table correspond to the expected $16\%$ contour of Figure 123 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h}^{125}(\text{alignment})$ scenario, evaluated at the $84\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $68\%$ confidence interval band. Numerical values provided in this table correspond to the expected $84\%$ contour of Figure 123 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h}^{125}(\text{alignment})$ scenario, evaluated at the $2.5\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $95\%$ confidence interval band. Numerical values provided in this table correspond to the expected $2.5\%$ contour of Figure 123 of the auxilliary material of the publication.

Expected $95\%\text{ CL}$ exclusion contour in the MSSM $M_{h}^{125}(\text{alignment})$ scenario, evaluated at the $97.5\%$ quantile of the test-statistic distribution $f(\tilde{q}_\mu|\text{SM})$ under SM hypothesis. This contour is part of the $95\%$ confidence interval band. Numerical values provided in this table correspond to the expected $97.5\%$ contour of Figure 123 of the auxilliary material of the publication.

Fractions of the cross-section $\sigma(gg\phi)$ as expected from SM for the loop contributions with only top quarks, only bottom quarks and from the top-bottom interference. These values are used to scale the corresponding signal components for a given mass $m_\phi$.

Observed and expected distributions of the variable chosen for statistical inference in the $t\bar{t}$ control region $m_{T}^{tot}$ for high-mass analysis. Numerical values provided in this table correspond to the $t\bar{t}$ control region of the publication, restricted to 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the $t\bar{t}$ control region $m_{T}^{tot}$ for high-mass analysis. Numerical values provided in this table correspond to the $t\bar{t}$ control region of the publication, restricted to 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the $t\bar{t}$ control region $m_{T}^{tot}$ for high-mass analysis. Numerical values provided in this table correspond to the $t\bar{t}$ control region of the publication, restricted to 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 25 of the auxilliary material of the publication, but restricted to 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 25 of the auxilliary material of the publication, but restricted to and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 25 of the auxilliary material of the publication, but restricted to and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 8a of the publication, but restricted to 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 8a of the publication, but restricted to and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 8a of the publication, but restricted to and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 26 of the auxilliary material of the publication, but restricted to 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 26 of the auxilliary material of the publication, but restricted to and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 26 of the auxilliary material of the publication, but restricted to and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 8b of the publication, but restricted to 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 8b of the publication, but restricted to and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 8b of the publication, but restricted to and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 27 of the auxilliary material of the publication, but restricted to 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 27 of the auxilliary material of the publication, but restricted to and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 27 of the auxilliary material of the publication, but restricted to and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 28 of the auxilliary material of the publication, but restricted to 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 28 of the auxilliary material of the publication, but restricted to and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 28 of the auxilliary material of the publication, but restricted to and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 8c of the publication, but restricted to $e\tau_{h}$ final state and 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 8c of the publication, but restricted to $e\tau_{h}$ final state and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 8c of the publication, but restricted to $e\tau_{h}$ final state and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 29 of the auxilliary material of the publication, but restricted to $e\tau_{h}$ final state and 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 29 of the auxilliary material of the publication, but restricted to $e\tau_{h}$ final state and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 29 of the auxilliary material of the publication, but restricted to $e\tau_{h}$ final state and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 8d of the publication, but restricted to $e\tau_{h}$ final state and 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 8d of the publication, but restricted to $e\tau_{h}$ final state and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 8d of the publication, but restricted to $e\tau_{h}$ final state and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 30 of the auxilliary material of the publication, but restricted to $e\tau_{h}$ final state and 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 30 of the auxilliary material of the publication, but restricted to $e\tau_{h}$ final state and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 30 of the auxilliary material of the publication, but restricted to $e\tau_{h}$ final state and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 8c of the publication, but restricted to $\mu\tau_{h}$ final state and 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 8c of the publication, but restricted to $\mu\tau_{h}$ final state and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 8c of the publication, but restricted to $\mu\tau_{h}$ final state and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 29 of the auxilliary material of the publication, but restricted to $\mu\tau_{h}$ final state and 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 29 of the auxilliary material of the publication, but restricted to $\mu\tau_{h}$ final state and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 29 of the auxilliary material of the publication, but restricted to $\mu\tau_{h}$ final state and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 8d of the publication, but restricted to $\mu\tau_{h}$ final state and 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 8d of the publication, but restricted to $\mu\tau_{h}$ final state and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 8d of the publication, but restricted to $\mu\tau_{h}$ final state and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 30 of the auxilliary material of the publication, but restricted to $\mu\tau_{h}$ final state and 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 30 of the auxilliary material of the publication, but restricted to $\mu\tau_{h}$ final state and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 30 of the auxilliary material of the publication, but restricted to $\mu\tau_{h}$ final state and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 8e of the publication, but restricted to 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 8e of the publication, but restricted to 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 8e of the publication, but restricted to 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 8f of the publication, but restricted to 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 8f of the publication, but restricted to 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the high-mass analysis $m_{T}^{tot}$. Numerical values provided in this table correspond to Figure 8f of the publication, but restricted to 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the $t\bar{t}$ control region $m_{T}^{tot}$ for low-mass analysis. Numerical values provided in this table correspond to the $t\bar{t}$ control region of the publication, restricted to 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the $t\bar{t}$ control region $m_{T}^{tot}$ for low-mass analysis. Numerical values provided in this table correspond to the $t\bar{t}$ control region of the publication, restricted to 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the $t\bar{t}$ control region $m_{T}^{tot}$ for low-mass analysis. Numerical values provided in this table correspond to the $t\bar{t}$ control region of the publication, restricted to 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 11 of the auxilliary material of the publication, but restricted to High-$D_\zeta$ category and 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 11 of the auxilliary material of the publication, but restricted to High-$D_\zeta$ category and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 11 of the auxilliary material of the publication, but restricted to High-$D_\zeta$ category and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 11 of the auxilliary material of the publication, but restricted to Medium-$D_\zeta$ category and 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 11 of the auxilliary material of the publication, but restricted to Medium-$D_\zeta$ category and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 11 of the auxilliary material of the publication, but restricted to Medium-$D_\zeta$ category and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 12 of the auxilliary material of the publication, but restricted to High-$D_\zeta$ category and 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 12 of the auxilliary material of the publication, but restricted to High-$D_\zeta$ category and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 12 of the auxilliary material of the publication, but restricted to High-$D_\zeta$ category and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 12 of the auxilliary material of the publication, but restricted to Medium-$D_\zeta$ category and 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 12 of the auxilliary material of the publication, but restricted to Medium-$D_\zeta$ category and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 12 of the auxilliary material of the publication, but restricted to Medium-$D_\zeta$ category and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 13 of the auxilliary material of the publication, but restricted to High-$D_\zeta$ category and 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 13 of the auxilliary material of the publication, but restricted to High-$D_\zeta$ category and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 13 of the auxilliary material of the publication, but restricted to High-$D_\zeta$ category and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 13 of the auxilliary material of the publication, but restricted to Medium-$D_\zeta$ category and 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 13 of the auxilliary material of the publication, but restricted to Medium-$D_\zeta$ category and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 13 of the auxilliary material of the publication, but restricted to Medium-$D_\zeta$ category and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 14 of the auxilliary material of the publication, but restricted to High-$D_\zeta$ category and 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 14 of the auxilliary material of the publication, but restricted to High-$D_\zeta$ category and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 14 of the auxilliary material of the publication, but restricted to High-$D_\zeta$ category and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 14 of the auxilliary material of the publication, but restricted to Medium-$D_\zeta$ category and 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 14 of the auxilliary material of the publication, but restricted to Medium-$D_\zeta$ category and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 14 of the auxilliary material of the publication, but restricted to Medium-$D_\zeta$ category and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 10 of the auxilliary material of the publication, but restricted to High-$D_\zeta$ category and 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 10 of the auxilliary material of the publication, but restricted to High-$D_\zeta$ category and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 10 of the auxilliary material of the publication, but restricted to High-$D_\zeta$ category and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 10 of the auxilliary material of the publication, but restricted to Medium-$D_\zeta$ category and 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 10 of the auxilliary material of the publication, but restricted to Medium-$D_\zeta$ category and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 10 of the auxilliary material of the publication, but restricted to Medium-$D_\zeta$ category and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 16 of the auxilliary material of the publication, but restricted to $e\tau_{h}$ final state and 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 16 of the auxilliary material of the publication, but restricted to $e\tau_{h}$ final state and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 16 of the auxilliary material of the publication, but restricted to $e\tau_{h}$ final state and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 17 of the auxilliary material of the publication, but restricted to $e\tau_{h}$ final state and 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 17 of the auxilliary material of the publication, but restricted to $e\tau_{h}$ final state and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 17 of the auxilliary material of the publication, but restricted to $e\tau_{h}$ final state and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 18 of the auxilliary material of the publication, but restricted to $e\tau_{h}$ final state and 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 18 of the auxilliary material of the publication, but restricted to $e\tau_{h}$ final state and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 18 of the auxilliary material of the publication, but restricted to $e\tau_{h}$ final state and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 19 of the auxilliary material of the publication, but restricted to $e\tau_{h}$ final state and 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 19 of the auxilliary material of the publication, but restricted to $e\tau_{h}$ final state and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 19 of the auxilliary material of the publication, but restricted to $e\tau_{h}$ final state and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 15 of the auxilliary material of the publication, but restricted to $e\tau_{h}$ final state and 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 15 of the auxilliary material of the publication, but restricted to $e\tau_{h}$ final state and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 15 of the auxilliary material of the publication, but restricted to $e\tau_{h}$ final state and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 16 of the auxilliary material of the publication, but restricted to $\mu\tau_{h}$ final state and 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 16 of the auxilliary material of the publication, but restricted to $\mu\tau_{h}$ final state and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 16 of the auxilliary material of the publication, but restricted to $\mu\tau_{h}$ final state and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 17 of the auxilliary material of the publication, but restricted to $\mu\tau_{h}$ final state and 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 17 of the auxilliary material of the publication, but restricted to $\mu\tau_{h}$ final state and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 17 of the auxilliary material of the publication, but restricted to $\mu\tau_{h}$ final state and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 18 of the auxilliary material of the publication, but restricted to $\mu\tau_{h}$ final state and 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 18 of the auxilliary material of the publication, but restricted to $\mu\tau_{h}$ final state and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 18 of the auxilliary material of the publication, but restricted to $\mu\tau_{h}$ final state and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 19 of the auxilliary material of the publication, but restricted to $\mu\tau_{h}$ final state and 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 19 of the auxilliary material of the publication, but restricted to $\mu\tau_{h}$ final state and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 19 of the auxilliary material of the publication, but restricted to $\mu\tau_{h}$ final state and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 15 of the auxilliary material of the publication, but restricted to $\mu\tau_{h}$ final state and 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 15 of the auxilliary material of the publication, but restricted to $\mu\tau_{h}$ final state and 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 15 of the auxilliary material of the publication, but restricted to $\mu\tau_{h}$ final state and 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 21 of the auxilliary material of the publication, but restricted to 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 21 of the auxilliary material of the publication, but restricted to 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 21 of the auxilliary material of the publication, but restricted to 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 22 of the auxilliary material of the publication, but restricted to 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 22 of the auxilliary material of the publication, but restricted to 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 22 of the auxilliary material of the publication, but restricted to 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 23 of the auxilliary material of the publication, but restricted to 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 23 of the auxilliary material of the publication, but restricted to 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 23 of the auxilliary material of the publication, but restricted to 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 24 of the auxilliary material of the publication, but restricted to 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 24 of the auxilliary material of the publication, but restricted to 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 24 of the auxilliary material of the publication, but restricted to 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 20 of the auxilliary material of the publication, but restricted to 2016 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 20 of the auxilliary material of the publication, but restricted to 2017 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

Observed and expected distributions of the variable chosen for statistical inference in the low-mass analysis $m_{\tau\tau}$. Numerical values provided in this table correspond to Figure 20 of the auxilliary material of the publication, but restricted to 2018 data-taking year. All distributions are considered after a fit to data is performed using a background-only model, which includes the $\text{H}(125)$ boson. Some details on how the distributions should be used: 1) All given uncertainties correspond to systematic variations of $\pm1\sigma$. 2) Upper values ('plus' in the yaml file) correspond to an upward systematic variation of the parameter ($+1\sigma$). 3) Lower values ('minus' in the yaml file) correspond to a downward systematic variation of the parameter ($-1\sigma$). 4) These variations can have both positive and negative values, depending on the modelled effect. 5) Uncertainties with the same name should be treated as correlated, consistently across the upper and lower variations. 6) Systematic uncertainties with 'prop_' in the name treat limited background statistics per histogram bin, and are deployed with 'Barlow-Beeston-lite' approach. Details in https://arxiv.org/abs/1103.0354 section 5 7) Remaining systematic uncertainties alter the normalization, the shape, or both for a distribution. The nuisance parameter for such an uncertainty is mapped separately on the normalization and the shape variation components of the uncertainty. For normalization, $\ln$ mapping is used, for shape a spline. Details in https://cms-analysis.github.io/HiggsAnalysis-CombinedLimit/part2/settinguptheanalysis/#binned-shape-analysis 8) All nuisance parameters for the systematic uncertainties are modelled with a Gaussian pdf. 9) Gluon fusion contributions are all scaled to 1 pb. Please combine them using either the scale factors from 'Table SM Gluon Fusion Fractions', or using your own composition.

The measured differential cross section in the $76 \le M_{ll} < 106$ GeV mass window, in bins of the dilepton transverse momentum. The values are normalized by the bin width. This entry contains the covariance matrix of the results.

The measured differential cross section in the $106 \le M_{ll} < 170$ GeV mass window, in bins of the dilepton transverse momentum. The values are normalized by the bin width.

The measured differential cross section in the $106 \le M_{ll} < 170$ GeV mass window, in bins of the dilepton transverse momentum. The values are normalized by the bin width. This entry contains the covariance matrix of the results.

The measured differential cross section in the $170 \le M_{ll} < 350$ GeV mass window, in bins of the dilepton transverse momentum. The values are normalized by the bin width.

The measured differential cross section in the $170 \le M_{ll} < 350$ GeV mass window, in bins of the dilepton transverse momentum. The values are normalized by the bin width. This entry contains the covariance matrix of the results.

The measured differential cross section in the $350 \le M_{ll} < 1000$ GeV mass window, in bins of the dilepton transverse momentum. The values are normalized by the bin width.

The measured differential cross section in the $350 \le M_{ll} < 1000$ GeV mass window, in bins of the dilepton transverse momentum. The values are normalized by the bin width. This entry contains the covariance matrix of the results.

The measured differential cross section in the $50 \le M_{ll} < 76$ GeV mass window, in bins of the dilepton transverse momentum. At least one jet is required. The values are normalized by the bin width.

The measured differential cross section in the $50 \le M_{ll} < 76$ GeV mass window, in bins of the dilepton transverse momentum. At least one jet is required. The values are normalized by the bin width. This entry contains the covariance matrix of the results.

The measured differential cross section in the $76 \le M_{ll} < 106$ GeV mass window, in bins of the dilepton transverse momentum. At least one jet is required. The values are normalized by the bin width.

The measured differential cross section in the $76 \le M_{ll} < 106$ GeV mass window, in bins of the dilepton transverse momentum. At least one jet is required. The values are normalized by the bin width. This entry contains the covariance matrix of the results.

The measured differential cross section in the $106 \le M_{ll} < 170$ GeV mass window, in bins of the dilepton transverse momentum. At least one jet is required. The values are normalized by the bin width.

The measured differential cross section in the $106 \le M_{ll} < 170$ GeV mass window, in bins of the dilepton transverse momentum. At least one jet is required. The values are normalized by the bin width. This entry contains the covariance matrix of the results.

The measured differential cross section in the $170 \le M_{ll} < 350$ GeV mass window, in bins of the dilepton transverse momentum. At least one jet is required. The values are normalized by the bin width.

The measured differential cross section in the $170 \le M_{ll} < 350$ GeV mass window, in bins of the dilepton transverse momentum. At least one jet is required. The values are normalized by the bin width. This entry contains the covariance matrix of the results.

The measured differential cross section in the $50 \le M_{ll} < 76$ GeV mass window, in bins of the $\varphi^*$ variable. The values are normalized by the bin width.

The measured differential cross section in the $50 \le M_{ll} < 76$ GeV mass window, in bins of the $\varphi^*$ variable. The values are normalized by the bin width. This entry contains the covariance matrix of the results.

The measured differential cross section in the $76 \le M_{ll} < 106$ GeV mass window, in bins of the $\varphi^*$ variable. The values are normalized by the bin width.

The measured differential cross section in the $76 \le M_{ll} < 106$ GeV mass window, in bins of the $\varphi^*$ variable. The values are normalized by the bin width. This entry contains the covariance matrix of the results.

The measured differential cross section in the $106 \le M_{ll} < 170$ GeV mass window, in bins of the $\varphi^*$ variable. The values are normalized by the bin width.

The measured differential cross section in the $106 \le M_{ll} < 170$ GeV mass window, in bins of the $\varphi^*$ variable. The values are normalized by the bin width. This entry contains the covariance matrix of the results.

The measured differential cross section in the $170 \le M_{ll} < 350$ GeV mass window, in bins of the $\varphi^*$ variable. The values are normalized by the bin width.

The measured differential cross section in the $170 \le M_{ll} < 350$ GeV mass window, in bins of the $\varphi^*$ variable. The values are normalized by the bin width. This entry contains the covariance matrix of the results.

The measured differential cross section in the $350 \le M_{ll} < 1000$ GeV mass window, in bins of the $\varphi^*$ variable. The values are normalized by the bin width.

The measured differential cross section in the $350 \le M_{ll} < 1000$ GeV mass window, in bins of the $\varphi^*$ variable. The values are normalized by the bin width. This entry contains the covariance matrix of the results.

The measured differential cross section in the $50 \le M_{ll} < 76$ GeV mass window, in bins of the dilepton transverse momentum, divided by the measured differential cross section in the $76 \le M_{ll} < 106$ GeV mass window. The values are not normalized by the bin width.

The measured differential cross section in the $50 \le M_{ll} < 76$ GeV mass window, in bins of the dilepton transverse momentum, divided by the measured differential cross section in the $76 \le M_{ll} < 106$ GeV mass window. The values are not normalized by the bin width. This entry contains the covariance matrix of the results.

The measured differential cross section in the $106 \le M_{ll} < 170$ GeV mass window, in bins of the dilepton transverse momentum, divided by the measured differential cross section in the $76 \le M_{ll} < 106$ GeV mass window. The values are not normalized by the bin width.

The measured differential cross section in the $106 \le M_{ll} < 170$ GeV mass window, in bins of the dilepton transverse momentum, divided by the measured differential cross section in the $76 \le M_{ll} < 106$ GeV mass window. The values are not normalized by the bin width. This entry contains the covariance matrix of the results.

The measured differential cross section in the $170 \le M_{ll} < 350$ GeV mass window, in bins of the dilepton transverse momentum, divided by the measured differential cross section in the $76 \le M_{ll} < 106$ GeV mass window. The values are not normalized by the bin width.

The measured differential cross section in the $170 \le M_{ll} < 350$ GeV mass window, in bins of the dilepton transverse momentum, divided by the measured differential cross section in the $76 \le M_{ll} < 106$ GeV mass window. The values are not normalized by the bin width. This entry contains the covariance matrix of the results.

The measured differential cross section in the $350 \le M_{ll} < 1000$ GeV mass window, in bins of the dilepton transverse momentum, divided by the measured differential cross section in the $76 \le M_{ll} < 106$ GeV mass window. The values are not normalized by the bin width.

The measured differential cross section in the $350 \le M_{ll} < 1000$ GeV mass window, in bins of the dilepton transverse momentum, divided by the measured differential cross section in the $76 \le M_{ll} < 106$ GeV mass window. The values are not normalized by the bin width. This entry contains the covariance matrix of the results.

The measured differential cross section in the $50 \le M_{ll} < 76$ GeV mass window, in bins of the dilepton transverse momentum, divided by the measured differential cross section in the $76 \le M_{ll} < 106$ GeV mass window. At least one jet is required. The values are not normalized by the bin width.

The measured differential cross section in the $50 \le M_{ll} < 76$ GeV mass window, in bins of the dilepton transverse momentum, divided by the measured differential cross section in the $76 \le M_{ll} < 106$ GeV mass window. At least one jet is required. The values are not normalized by the bin width. This entry contains the covariance matrix of the results.

The measured differential cross section in the $106 \le M_{ll} < 170$ GeV mass window, in bins of the dilepton transverse momentum, divided by the measured differential cross section in the $76 \le M_{ll} < 106$ GeV mass window. At least one jet is required. The values are not normalized by the bin width.

The measured differential cross section in the $106 \le M_{ll} < 170$ GeV mass window, in bins of the dilepton transverse momentum, divided by the measured differential cross section in the $76 \le M_{ll} < 106$ GeV mass window. At least one jet is required. The values are not normalized by the bin width. This entry contains the covariance matrix of the results.

The measured differential cross section in the $170 \le M_{ll} < 350$ GeV mass window, in bins of the dilepton transverse momentum, divided by the measured differential cross section in the $76 \le M_{ll} < 106$ GeV mass window. At least one jet is required. The values are not normalized by the bin width.

The measured differential cross section in the $170 \le M_{ll} < 350$ GeV mass window, in bins of the dilepton transverse momentum, divided by the measured differential cross section in the $76 \le M_{ll} < 106$ GeV mass window. At least one jet is required. The values are not normalized by the bin width. This entry contains the covariance matrix of the results.

The measured differential cross section in the $50 \le M_{ll} < 76$ GeV mass window, in bins of the $\varphi^*$ variable, divided by the measured differential cross section in the $76 \le M_{ll} < 106$ GeV mass window. At least one jet is required. The values are not normalized by the bin width.

The measured differential cross section in the $50 \le M_{ll} < 76$ GeV mass window, in bins of the $\varphi^*$ variable, divided by the measured differential cross section in the $76 \le M_{ll} < 106$ GeV mass window. At least one jet is required. The values are not normalized by the bin width. This entry contains the covariance matrix of the results.

The measured differential cross section in the $106 \le M_{ll} < 170$ GeV mass window, in bins of the $\varphi^*$ variable, divided by the measured differential cross section in the $76 \le M_{ll} < 106$ GeV mass window. At least one jet is required. The values are not normalized by the bin width.

The measured differential cross section in the $106 \le M_{ll} < 170$ GeV mass window, in bins of the $\varphi^*$ variable, divided by the measured differential cross section in the $76 \le M_{ll} < 106$ GeV mass window. At least one jet is required. The values are not normalized by the bin width. This entry contains the covariance matrix of the results.

The measured differential cross section in the $170 \le M_{ll} < 350$ GeV mass window, in bins of the $\varphi^*$ variable, divided by the measured differential cross section in the $76 \le M_{ll} < 106$ GeV mass window. At least one jet is required. The values are not normalized by the bin width.

The measured differential cross section in the $170 \le M_{ll} < 350$ GeV mass window, in bins of the $\varphi^*$ variable, divided by the measured differential cross section in the $76 \le M_{ll} < 106$ GeV mass window. At least one jet is required. The values are not normalized by the bin width. This entry contains the covariance matrix of the results.

The measured differential cross section in the $350 \le M_{ll} < 1000$ GeV mass window, in bins of the $\varphi^*$ variable, divided by the measured differential cross section in the $76 \le M_{ll} < 106$ GeV mass window. At least one jet is required. The values are not normalized by the bin width.

The measured differential cross section in the $350 \le M_{ll} < 1000$ GeV mass window, in bins of the $\varphi^*$ variable, divided by the measured differential cross section in the $76 \le M_{ll} < 106$ GeV mass window. At least one jet is required. The values are not normalized by the bin width. This entry contains the covariance matrix of the results.

Response matrix for pT ll mass 50-76 (electron channel)

Response matrix for pT ll mass 50-76 (muon channel)

Response matrix for pT ll mass 76-106 (electron channel)

Response matrix for pT ll mass 76-106 (muon channel)

Response matrix for pT ll mass 106-170 (electron channel)

Response matrix for pT ll mass 106-170 (muon channel)

Response matrix for pT ll mass 170-350 (electron channel)

Response matrix for pT ll mass 170-350 (muon channel)

Response matrix for pT ll mass 350-1000 (electron channel)

Response matrix for pT ll mass 50-76 jet (electron channel)

Response matrix for pT ll mass 50-76 jet (muon channel)

Response matrix for pT ll mass 76-106 jet (electron channel)

Response matrix for pT ll mass 76-106 jet (muon channel)

Response matrix for pT ll mass 106-170 jet (electron channel)

Response matrix for pT ll mass 106-170 jet (muon channel)

Response matrix for pT ll mass 170-350 jet (electron channel)

Response matrix for pT ll mass 170-350 jet (muon channel)

Response matrix for phistar mass 50-76 (electron channel)

Response matrix for phistar mass 50-76 (muon channel)

Response matrix for phistar mass 76-106 (electron channel)

Response matrix for phistar mass 76-106 (muon channel)

Response matrix for phistar mass 106-170 (electron channel)

Response matrix for phistar mass 106-170 (muon channel)

Response matrix for phistar mass 170-350 (electron channel)

Response matrix for phistar mass 170-350 (muon channel)

Response matrix for phistar mass 350-1000 (electron channel)

Response matrix for phistar mass 350-1000 (muon channel)

Bin-to-bin correlation in the measured cross section as a function of the rapidity absolute value of the first jet, $|y(\text{j}_1)|$.

Measured cross section as a function of the transverse momenum of the first jet, $p_{\text{T}}(\text{j}_1)$, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured cross section as a function of the transverse momenum of the first jet, $p_{\text{T}}(\text{j}_1)$.

Measured cross section as a function of the rapidity absolute value of the second jet, $|y(\text{j}_2)|$, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured cross section as a function of the rapidity absolute value of the second jet, $|y(\text{j}_2)|$.

Measured cross section as a function of the transverse momenum of the second jet, $p_{\text{T}}(\text{j}_2)$, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured cross section as a function of the transverse momenum of the second jet, $p_{\text{T}}(\text{j}_2)$.

Measured cross section as a function of the rapidity absolute value of the third jet, $|y(\text{j}_3)|$, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured cross section as a function of the rapidity absolute value of the third jet, $|y(\text{j}_3)|$.

Measured cross section as a function of the transverse momenum of the third jet, $p_{\text{T}}(\text{j}_3)$, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured cross section as a function of the transverse momenum of the third jet, $p_{\text{T}}(\text{j}_3)$.

Measured cross section as a function of the $H_{\text{T}}$ observable for events with at least one jet and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured cross section as a function of the $H_{\text{T}}$ observable for events with at least one jet.

Measured cross section as a function of the $H_{\text{T}}$ observable for events with at least two jets and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured cross section as a function of the $H_{\text{T}}$ observable for events with at least two jets.

Measured cross section as a function of the $H_{\text{T}}$ observable for events with at least three jets and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured cross section as a function of the $H_{\text{T}}$ observable for events with at least three jets.

Measured differential cross section as a function of dijet mass, $M_{\text{j}_1\text{j}_2}$, for events with at least two jets and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured differential cross section as a function of dijet mass, $M_{\text{j}_1\text{j}_2}$, for events with at least two jets.

Measured differential cross section as a function of Z boson rapidity absolute value, $|y(\text{Z})|$ for events with at least one jet and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured differential cross section as a function of Z boson rapidity absolute value, $|y(\text{Z})|$ for events with at least one jet.

Measured differential cross section as a function of the leading and subleading jet rapidity difference, $y_{\text{diff}}(\text{j}_1,\text{j}_2)$, for events with at least two jets and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured differential cross section as a function of the leading and subleading jet rapidity difference, $y_{\text{diff}}(\text{j}_1,\text{j}_2)$, for events with at least two jets.

Measured differential cross section as a function of the leading and subleading jet rapidity sum, $y_{\text{sum}}(\text{j}_1,\text{j}_2)$, for events with at least two jets and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured differential cross section as a function of the leading and subleading jet rapidity sum, $y_{\text{sum}}(\text{j}_1,\text{j}_2)$, for events with at least two jets.

Measured differential cross section as a function of the Z boson and leading jet rapidity difference, $y_{\text{diff}}(\text{Z},\text{j}_1)$, for events with at least one jet and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured differential cross section as a function of the Z boson and leading jet rapidity difference, $y_{\text{diff}}(\text{Z},\text{j}_1)$, for events with at least one jet.

Measured differential cross section as a function of the Z boson and leading jet rapidity sum, $y_{\text{sum}}(\text{Z},\text{j}_1)$, for events with at least one jet and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured differential cross section as a function of the Z boson and leading jet rapidity sum, $y_{\text{sum}}(\text{Z},\text{j}_1)$, for events with at least one jet.

Measured differential cross section as a function of the Z boson and leading jet rapidity difference, $y_{\text{diff}}(\text{Z},\text{j}_1)$, for events with at least two jets and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured differential cross section as a function of the Z boson and leading jet rapidity difference, $y_{\text{diff}}(\text{Z},\text{j}_1)$, for events with at least two jets.

Measured differential cross section as a function of the Z boson and leading jet rapidity sum, $y_{\text{sum}}(\text{Z},\text{j}_1)$, for events with at least two jets and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured differential cross section as a function of the Z boson and leading jet rapidity sum, $y_{\text{sum}}(\text{Z},\text{j}_1)$, for events with at least two jets.

Measured differential cross section as a function of the Z boson and subleading jet rapidity difference, $y_{\text{diff}}(\text{Z},\text{j}_2)$, for events with at least two jets and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured differential cross section as a function of the Z boson and subleading jet rapidity difference, $y_{\text{diff}}(\text{Z},\text{j}_2)$, for events with at least two jets.

Measured differential cross section as a function of the Z boson and subleading jet rapidity sum, $y_{\text{sum}}(\text{Z},\text{j}_2)$, for events with at least two jets and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured differential cross section as a function of the Z boson and subleading jet rapidity sum, $y_{\text{sum}}(\text{Z},\text{j}_2)$, for events with at least two jets.

Measured differential cross section as a function of the Z boson and dijet rapidity difference, $y_{\text{diff}}(\text{Z},\text{dijet})$, for events with at least two jets and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured differential cross section as a function of the Z boson and dijet rapidity difference, $y_{\text{diff}}(\text{Z},\text{dijet})$, for events with at least two jets.

Measured differential cross section as a function of the Z boson and dijet rapidity sum, $y_{\text{sum}}(\text{Z},\text{dijet})$, for events with at least two jets and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured differential cross section as a function of the Z boson and dijet rapidity sum, $y_{\text{sum}}(\text{Z},\text{dijet})$, for events with at least two jets.

Measured differential cross section as a function of the Z boson and leading jet azimuthal difference, $\Delta\phi(\text{Z},\text{j}_1)$, for events with at least one jet and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured differential cross section as a function of the Z boson and leading jet azimuthal difference, $\Delta\phi(\text{Z},\text{j}_1)$, for events with at least one jet.

Measured differential cross section as a function of the Z boson and leading jet azimuthal difference, $\Delta\phi(\text{Z},\text{j}_1)$, for events with at least two jets and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured differential cross section as a function of the Z boson and leading jet azimuthal difference, $\Delta\phi(\text{Z},\text{j}_1)$, for events with at least two jets.

Measured differential cross section as a function of the Z boson and leading jet azimuthal difference for events, $\Delta\phi(\text{Z},\text{j}_1)$, with at least three jets and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured differential cross section as a function of the Z boson and leading jet azimuthal difference for events, $\Delta\phi(\text{Z},\text{j}_1)$, with at least three jets.

Measured differential cross section as a function of the Z boson and subleading jet azimuthal difference for events with at least two jets and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured differential cross section as a function of the Z boson and subleading jet azimuthal difference for events with at least two jets.

Measured differential cross section as a function of the Z boson and subleading jet azimuthal difference, $\Delta\phi(\text{Z},\text{j}_2)$, for events with at least three jets and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured differential cross section as a function of the Z boson and subleading jet azimuthal difference, $\Delta\phi(\text{Z},\text{j}_2)$, for events with at least three jets.

Measured differential cross section as a function of the Z boson and third jet azimuthal difference, $\Delta\phi(\text{Z},\text{j}_3)$, for events with at least three jets and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured differential cross section as a function of the Z boson and third jet azimuthal difference, $\Delta\phi(\text{Z},\text{j}_3)$, for events with at least three jets.

Measured differential cross section as a function of the leading and subleading jet azimuthal difference, $\Delta\phi(\text{j}_1,\text{j}_2)$, for events with at least two jets and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured differential cross section as a function of the leading and subleading jet azimuthal difference, $\Delta\phi(\text{j}_1,\text{j}_2)$, for events with at least two jets.

Measured differential cross section as a function of the leading and subleading jet azimuthal difference, $\Delta\phi(\text{j}_1,\text{j}_2)$, for events with at least three jets and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured differential cross section as a function of the leading and subleading jet azimuthal difference, $\Delta\phi(\text{j}_1,\text{j}_2)$, for events with at least three jets.

Measured differential cross section as a function of the leading and third jet azimuthal difference, $\Delta\phi(\text{j}_1,\text{j}_3)$, for events with at least three jets and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured differential cross section as a function of the leading and third jet azimuthal difference, $\Delta\phi(\text{j}_1,\text{j}_3)$, for events with at least three jets.

Measured differential cross section as a function of the subleading and third jet azimuthal difference, $\Delta\phi(\text{j}_2,\text{j}_3)$, for events with at least three jets and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured differential cross section as a function of the subleading and third jet azimuthal difference, $\Delta\phi(\text{j}_2,\text{j}_3)$, for events with at least three jets.

Measured cross section as a function of the leading jet transverse momentum, $p_{\text{T}}(\text{j}_1)$, and rapidity absolute value, $|y(\text{j}_1)|$ for events with at least one jet and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured cross section as a function of the leading jet transverse momentum, $p_{\text{T}}(\text{j}_1)$, and rapidity absolute value, $|y(\text{j}_1)|$ for events with at least one jet.

Measured cross section as a function of the leading jet and Z boson rapidity abosolute values, $|y(\text{j}_1|$ and $|y(\text(Z))|$, for events with at least one jet with $p_\text{T}>20\,\text{Gev}$ and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured cross section as a function of the leading jet and Z boson rapidity abosolute values, $|y(\text{j}_1|$ and $|y(\text(Z))|$, for events with at least one jet with $p_\text{T}>20\,\text{Gev}$.

Measured cross section as a function of the transverse momementum, $p_{\text{T}}(\text{Z})$, and rapidity, $y(\text{Z})$, of the Z boson, for events with at least one jet with $p_\text{T}>20\,\text{Gev}$ and breakdown of the relative uncertainty.

Bin-to-bin correlation in the measured cross section as a function of the transverse momementum, $p_{\text{T}}(\text{Z})$, and rapidity, $y(\text{Z})$, of the Z boson, for events with at least one jet with $p_\text{T}>20\,\text{Gev}$.

Measured inclusive fiducial $tt\gamma$ production cross section in the dilepton final state for the different dilepton-flavour channels and combined.

Absolute differential $tt\gamma$ production cross section as a function of $p_{T}(\gamma)$ . The values provided in the table are not divided by the bin width.

Absolute differential $tt\gamma$ production cross section as a function of $|\eta |(\gamma)$. The values provided in the table are not divided by the bin width.

Absolute differential $tt\gamma$ production cross section as a function of min $\Delta R(\gamma, \ell)$. The values provided in the table are not divided by the bin width.

Absolute differential $tt\gamma$ production cross section as a function of $\Delta R(\gamma, \ell_{1})$. The values provided in the table are not divided by the bin width.

Absolute differential $tt\gamma$ production cross section as a function of $\Delta R(\gamma, \ell_{2})$. The values provided in the table are not divided by the bin width.

Absolute differential $tt\gamma$ production cross section as a function of min $\Delta R(\gamma, b)$. The values provided in the table are not divided by the bin width.

Absolute differential $tt\gamma$ production cross section as a function of $|\Delta\eta(\ell\ell)|$. The values provided in the table are not divided by the bin width.

Absolute differential $tt\gamma$ production cross section as a function of $\Delta \phi(\ell\ell)$. The values provided in the table are not divided by the bin width.

Absolute differential $tt\gamma$ production cross section as a function of $p_{T}(\ell\ell) $. The values provided in the table are not divided by the bin width.

Absolute differential $tt\gamma$ production cross section as a function of $p_{T}(\ell_{1})+p_{T}(\ell_{2})$ . The values provided in the table are not divided by the bin width.

Absolute differential $tt\gamma$ production cross section as a function of min $\Delta R(\ell, j)$. The values provided in the table are not divided by the bin width.

Absolute differential $tt\gamma$ production cross section as a function of $p_{T}(j_{1})$ .

Normalized differential $tt\gamma$ production cross section as a function of $p_{T}(\gamma)$ . The values provided in the table are not divided by the bin width.

Normalized differential $tt\gamma$ production cross section as a function of $|\eta |(\gamma)$. The values provided in the table are not divided by the bin width.

Normalized differential $tt\gamma$ production cross section as a function of min $\Delta R(\gamma, \ell)$. The values provided in the table are not divided by the bin width.

Normalized differential $tt\gamma$ production cross section as a function of $\Delta R(\gamma, \ell_{1})$. The values provided in the table are not divided by the bin width.

Normalized differential $tt\gamma$ production cross section as a function of $\Delta R(\gamma, \ell_{2})$. The values provided in the table are not divided by the bin width.

Normalized differential $tt\gamma$ production cross section as a function of min $\Delta R(\gamma, b)$. The values provided in the table are not divided by the bin width.

Normalized differential $tt\gamma$ production cross section as a function of $|\Delta\eta(\ell\ell)|$. The values provided in the table are not divided by the bin width.

Normalized differential $tt\gamma$ production cross section as a function of $\Delta \phi(\ell\ell)$. The values provided in the table are not divided by the bin width.

Normalized differential $tt\gamma$ production cross section as a function of $p_{T}(\ell\ell) $. The values provided in the table are not divided by the bin width.

Normalized differential $tt\gamma$ production cross section as a function of $p_{T}(\ell_{1})+p_{T}(\ell_{2})$ . The values provided in the table are not divided by the bin width.

Normalized differential $tt\gamma$ production cross section as a function of min $\Delta R(\ell, j)$. The values provided in the table are not divided by the bin width.

Normalized differential $tt\gamma$ production cross section as a function of $p_{T}(j_{1})$ . The values provided in the table are not divided by the bin width.

Correlation matrix of the systematic uncertainty in the absolute differential cross section as a function of $p_{T}(\gamma)$ .

Correlation matrix of the statistical uncertainty in the absolute differential cross section as a function of $p_{T}(\gamma)$ .

Correlation matrix of the systematic uncertainty in the absolute differential cross section as a function of $|\eta |(\gamma)$.

Correlation matrix of the statistical uncertainty in the absolute differential cross section as a function of $|\eta |(\gamma)$.

Correlation matrix of the systematic uncertainty in the absolute differential cross section as a function of min $\Delta R(\gamma, \ell)$.

Correlation matrix of the statistical uncertainty in the absolute differential cross section as a function of min $\Delta R(\gamma, \ell)$.

Correlation matrix of the systematic uncertainty in the absolute differential cross section as a function of $\Delta R(\gamma, \ell_{1})$.

Correlation matrix of the statistical uncertainty in the absolute differential cross section as a function of $\Delta R(\gamma, \ell_{1})$.

Correlation matrix of the systematic uncertainty in the absolute differential cross section as a function of $\Delta R(\gamma, \ell_{2})$.

Correlation matrix of the statistical uncertainty in the absolute differential cross section as a function of $\Delta R(\gamma, \ell_{2})$.

Correlation matrix of the systematic uncertainty in the absolute differential cross section as a function of min $\Delta R(\gamma, b)$.

Correlation matrix of the statistical uncertainty in the absolute differential cross section as a function of min $\Delta R(\gamma, b)$.

Correlation matrix of the systematic uncertainty in the absolute differential cross section as a function of $|\Delta\eta(\ell\ell)|$.

Correlation matrix of the statistical uncertainty in the absolute differential cross section as a function of $|\Delta\eta(\ell\ell)|$.

Correlation matrix of the systematic uncertainty in the absolute differential cross section as a function of $\Delta \phi(\ell\ell)$.

Correlation matrix of the statistical uncertainty in the absolute differential cross section as a function of $\Delta \phi(\ell\ell)$.

Correlation matrix of the systematic uncertainty in the absolute differential cross section as a function of $p_{T}(\ell\ell) $.

Correlation matrix of the statistical uncertainty in the absolute differential cross section as a function of $p_{T}(\ell\ell) $.

Correlation matrix of the systematic uncertainty in the absolute differential cross section as a function of $p_{T}(\ell_{1})+p_{T}(\ell_{2})$ .

Correlation matrix of the statistical uncertainty in the absolute differential cross section as a function of $p_{T}(\ell_{1})+p_{T}(\ell_{2})$ .

Correlation matrix of the systematic uncertainty in the absolute differential cross section as a function of min $\Delta R(\ell, j)$.

Correlation matrix of the statistical uncertainty in the absolute differential cross section as a function of min $\Delta R(\ell, j)$.

Correlation matrix of the systematic uncertainty in the absolute differential cross section as a function of $p_{T}(j_{1})$ .

Correlation matrix of the statistical uncertainty in the absolute differential cross section as a function of $p_{T}(j_{1})$ .

Negative log-likelihood difference from the best-fit value for the one-dimensional scans of the Wilson coefficient $c_{tZ}$, using the photon pT distribution from the dilepton analysis. The value of $c^{I}_{tZ}$ is fixed to zero in the fit.

Negative log-likelihood difference from the best-fit value for the one-dimensional scans of the Wilson coefficient $c_{tZ}$, using the combination of photon pT distributions from the dilepton and lepton+jets analyses. The value of $c^{I}_{tZ}$ is fixed to zero in the fit.

Negative log-likelihood difference from the best-fit value for the one-dimensional scans of the Wilson coefficient $c^{I}_{tZ}$, using the photon pT distribution from the dilepton analysis. The value of $c_{tZ}$ is fixed to zero in the fit.

Negative log-likelihood difference from the best-fit value for the one-dimensional scans of the Wilson coefficient $c^{I}_{tZ}$, using the combination of photon pT distributions from the dilepton and lepton+jets analyses. The value of $c_{tZ}$ is fixed to zero in the fit.

Negative log-likelihood difference from the best-fit value for the one-dimensional scans of the Wilson coefficient $c_{tZ}$, using the photon pT distribution from the dilepton analysis. The value of $c^{I}_{tZ}$ is profiled in the fit.

Negative log-likelihood difference from the best-fit value for the one-dimensional scans of the Wilson coefficient $c_{tZ}$, using the combination of photon pT distributions from the dilepton and lepton+jets analyses. The value of $c^{I}_{tZ}$ is profiled in the fit.

Negative log-likelihood difference from the best-fit value for the one-dimensional scans of the Wilson coefficient $c^{I}_{tZ}$, using the photon pT distribution from the dilepton analysis. The value of $c_{tZ}$ is profiled in the fit.

Negative log-likelihood difference from the best-fit value for the one-dimensional scans of the Wilson coefficient $c^{I}_{tZ}$, using the combination of photon pT distributions from the dilepton and lepton+jets analyses. The value of $c_{tZ}$ is profiled in the fit.

Negative log-likelihood difference from the best-fit value as a function of Wilson coefficients $c_{tZ}$ and $c^{I}_{tZ}$ from the interpretation of the dilepton measurement.

Negative log-likelihood difference from the best-fit value as a function of Wilson coefficients $c_{tZ}$ and $c^{I}_{tZ}$ from the interpretation of the dilepton and lepton+jets measurements combined.

One-dimensional 68 and 95% CL intervals obtained for the Wilson coefficients $c_{tZ}$ and $c^{I}_{tZ}$, using the photon $p_{T}$ distribution from the dilepton analysis, or the combination of photon pT distributions from the dilepton and lepton+jets analyses.

Comparison of observed $95\%$ CL intervals for the Wilson coefficients $c_{tZ}$ and $c^{I}_{tZ}$. Results are shown from a CMS ttZ measurement [JHEP 03 (2020) 056], from a CMS ttZ & tZq interpretation [arXiv:2107.13896], from a CMS ttG (lepton+jets) measurement [arXiv:2107.01508], from this measurement, and from a global fit by J. Ellis et al. [JHEP 04 (2021) 279].

Azimuthal correlation distribution between heavy-flavour decay electrons and charged hadrons, scaled by the number of electrons in EMCal triggered events in the electron transverse momentum range 4.5-6 GeV/c.

Relative beauty contribution to the heavy-flavour electron yield obtained with the method based on the track impact parameter.

Relative beauty contribution to the heavy-flavour electron yield obtained with the method based on the track impact parameter.

Relative beauty contribution to the heavy-flavour electron yield obtained from the method based on the azimuthal correlation of heavy-flavour decay electrons and charged tracks.

Relative beauty contribution to the heavy-flavour electron yield obtained from the method based on the azimuthal correlation of heavy-flavour decay electrons and charged tracks.

The $p_{\rm T}$-differential inclusive cross section of electrons (multiplied by $10^3$ for readability) from beauty hadron decays using the electron-hadron azimuthal correlation method.

The pT-differential inclusive cross section of electrons from beauty hadron decays using the electron-hadron azimuthal correlation method.

The $p_{\rm T}$-differential inclusive cross section of electrons (multiplied by $10^3$ for readability) from beauty hadron decays. A 1.9% normalization uncertainty not shown.

The pT-differential inclusive cross section of electrons from beauty hadron decays. A 1.9% normalization uncertainty not shown.

Inclusive bbbar production cross section per rapidity unit measured in mid-rapidity.

Inclusive bbbar production cross section per rapidity unit measured.

Total bbbar production cross section.

Total bbbar production cross section.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the 1$^\text{st}$ jet $p_{\text{T}}$, $p_{\text{T}}(\text{j}_1)$.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the 2$^\text{nd}$ jet $p_{\text{T}}$, $p_{\text{T}}(\text{j}_2)$, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the 2$^\text{nd}$ jet $p_{\text{T}}$, $p_{\text{T}}(\text{j}_2)$.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the 3$^\text{rd}$ jet $p_{\text{T}}$, $p_{\text{T}}(\text{j}_3)$, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the 3$^\text{rd}$ jet $p_{\text{T}}$, $p_{\text{T}}(\text{j}_3)$.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the 4$^\text{th}$ jet $p_{\text{T}}$, $p_{\text{T}}(\text{j}_4)$, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the 4$^\text{th}$ jet $p_{\text{T}}$, $p_{\text{T}}(\text{j}_4)$.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the 5$^\text{th}$ jet $p_{\text{T}}$, $p_{\text{T}}(\text{j}_5)$, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the 5$^\text{th}$ jet $p_{\text{T}}$, $p_{\text{T}}(\text{j}_5)$.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the 1$^\text{st}$ jet $|y|$, $|y(\text{j}_1)|$, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the 1$^\text{st}$ jet $|y|$, $|y(\text{j}_1)|$.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the 2$^\text{nd}$ jet $|y|$, $|y(\text{j}_2)|$, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the 2$^\text{nd}$ jet $|y|$, $|y(\text{j}_2)|$.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the 3$^\text{rd}$ jet $|y|$, $|y(\text{j}_3)|$, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the 3$^\text{rd}$ jet $|y|$, $|y(\text{j}_3)|$.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the 4$^\text{th}$ jet $|y|$, $|y(\text{j}_4)|$, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the 4$^\text{th}$ jet $|y|$, $|y(\text{j}_4)|$.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the 5$^\text{th}$ jet $|y|$, $|y(\text{j}_5)|$, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the 5$^\text{th}$ jet $|y|$, $|y(\text{j}_5)|$.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the Z boson $|y|$, $|y(\text{Z})|$, for events with at least one jet and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the Z boson $|y|$, $|y(\text{Z})|$, for events with at least one jet.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the Z boson $|y|$, $|y(\text{Z})|$ for events with at least one jet and $p_\text{T}(\text{Z}) > 150\,$GeV, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the Z boson $|y|$, $|y(\text{Z})|$ for events with at least one jet and $p_\text{T}(\text{Z}) > 150\,$GeV.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the Z boson $|y|$, $|y(\text{Z})|$ for events with at least $p_\text{T}(\text{Z}) > 300\,$GeV, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the Z boson $|y|$, $|y(\text{Z})|$ for events with at least $p_\text{T}(\text{Z}) > 300\,$GeV.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the $y_{\text{diff}}$ of the Z boson and the leading jet, $y_{\text{diff}}(\text{Z}, \text{j}_1)$, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the $y_{\text{diff}}$ of the Z boson and the leading jet, $y_{\text{diff}}(\text{Z}, \text{j}_1)$.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the $y_{\text{diff}}$ of the Z boson and the leading jet, $y_{\text{diff}}(\text{Z}, \text{j}_1)$ for events with $p_{\text{T}}(\text{Z}) > 150\,$GeV, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the $y_{\text{diff}}$ of the Z boson and the leading jet, $y_{\text{diff}}(\text{Z}, \text{j}_1)$ for events with $p_{\text{T}}(\text{Z}) > 150\,$GeV.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the $y_{\text{diff}}$ of the Z boson and the leading jet, $y_{\text{diff}}(\text{Z}, \text{j}_1)$ for events with $p_{\text{T}}(\text{Z}) > 300\,$GeV, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the $y_{\text{diff}}$ of the Z boson and the leading jet, $y_{\text{diff}}(\text{Z}, \text{j}_1)$ for events with $p_{\text{T}}(\text{Z}) > 300\,$GeV.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the $y_{\text{diff}}$ of the Z boson and the 2$^\text{nd}$leading jet, $y_{\text{diff}}(\text{Z}, \text{j}_2)$, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the $y_{\text{diff}}$ of the Z boson and the 2$^\text{nd}$leading jet, $y_{\text{diff}}(\text{Z}, \text{j}_2)$.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the $y_{\text{diff}}$ of the Z boson and the 3$^\text{rd}$leading jet, $y_{\text{diff}}(\text{Z}, \text{j}_3)$, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the $y_{\text{diff}}$ of the Z boson and the 3$^\text{rd}$leading jet, $y_{\text{diff}}(\text{Z}, \text{j}_3)$.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the $y_{\text{diff}}$ of the Z boson and the system constituted of the two leading jets, $y_{\text{diff}}(\text{Z}, \text{dijet})$, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the $y_{\text{diff}}$ of the Z boson and the system constituted of the two leading jets, $y_{\text{diff}}(\text{Z}, \text{dijet})$.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the $y_{\text{diff}}$ of the two leading jets, $y_{\text{diff}}(\text{j}_1, \text{j}_2)$, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the $y_{\text{diff}}$ of the two leading jets, $y_{\text{diff}}(\text{j}_1, \text{j}_2)$.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the $y_{\text{sum}}$ of the two leading jets, $y_{\text{sum}}(\text{j}_1, \text{j}_2)$, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the $y_{\text{sum}}$ of the two leading jets, $y_{\text{sum}}(\text{j}_1, \text{j}_2)$.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the $y_{\text{sum}}$ of the Z boson and the leading jet, $y_{\text{sum}}(\text{Z}, \text{j}_1)$, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the $y_{\text{sum}}$ of the Z boson and the leading jet, $y_{\text{sum}}(\text{Z}, \text{j}_1)$.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the $y_{\text{sum}}$ of the Z boson and the leading jet, $y_{\text{sum}}(\text{Z}, \text{j}_1)$ for events with $p_{\text{T}}(\text{Z}) > 150\,$GeV, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the $y_{\text{sum}}$ of the Z boson and the leading jet, $y_{\text{sum}}(\text{Z}, \text{j}_1)$ for events with $p_{\text{T}}(\text{Z}) > 150\,$GeV.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the $y_{\text{sum}}$ of the Z boson and the leading jet, $y_{\text{sum}}(\text{Z}, \text{j}_1)$ for events with $p_{\text{T}}(\text{Z}) > 300\,$GeV, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the $y_{\text{sum}}$ of the Z boson and the leading jet, $y_{\text{sum}}(\text{Z}, \text{j}_1)$ for events with $p_{\text{T}}(\text{Z}) > 300\,$GeV.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the $y_{\text{sum}}$ of the Z boson and the 2$^\text{nd}$leading jet, $y_{\text{sum}}(\text{Z}, \text{j}_2)$, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the $y_{\text{sum}}$ of the Z boson and the 2$^\text{nd}$leading jet, $y_{\text{sum}}(\text{Z}, \text{j}_2)$.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the $y_{\text{sum}}$ of the Z boson and the 3$^\text{rd}$leading jet, $y_{\text{sum}}(\text{Z}, \text{j}_3)$, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the $y_{\text{sum}}$ of the Z boson and the 3$^\text{rd}$leading jet, $y_{\text{sum}}(\text{Z}, \text{j}_3)$.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the $y_{\text{sum}}$ of the Z boson and the system constituted of the two leading jets, $y_{\text{sum}}(\text{Z}, \text{dijet})$, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the $y_{\text{sum}}$ of the Z boson and the system constituted of the two leading jets, $y_{\text{sum}}(\text{Z}, \text{dijet})$.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of $H_\text{T}$ for events with at least one jet, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of $H_\text{T}$ for events with at least one jet.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of $H_\text{T}$ for events with at least two jets, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of $H_\text{T}$ for events with at least two jets.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of $H_\text{T}$ for events with at least three jets, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of $H_\text{T}$ for events with at least three jets.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of $H_\text{T}$ for events with at least four jets, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of $H_\text{T}$ for events with at least four jets.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of $H_\text{T}$ for events with at least five jets, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of $H_\text{T}$ for events with at least five jets.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the leading jet for events with at least ine jet, $\Delta\Phi(\text{Z},\text{j}_1)$, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the leading jet for events with at least ine jet, $\Delta\Phi(\text{Z},\text{j}_1)$.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the leading jet for events with at least two jets, $\Delta\Phi(\text{Z},\text{j}_1)$, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the leading jet for events with at least two jets, $\Delta\Phi(\text{Z},\text{j}_1)$.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the leading jet for events with at least three jets, $\Delta\Phi(\text{Z},\text{j}_1)$, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the leading jet for events with at least three jets, $\Delta\Phi(\text{Z},\text{j}_1)$.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the 2$^\text{nd}$ leading jet for events with at least three jets, $\Delta\Phi(\text{Z},\text{j}_1)$, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the 2$^\text{nd}$ leading jet for events with at least three jets, $\Delta\Phi(\text{Z},\text{j}_1)$.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the 3$^\text{rd}$ leading jet for events with at least three jets, $\Delta\Phi(\text{Z},\text{j}_1)$, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the 3$^\text{rd}$ leading jet for events with at least three jets, $\Delta\Phi(\text{Z},\text{j}_1)$.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the leading jet$\Delta\Phi(\text{Z},\text{j}_1)$, for events with $p_{\text{T}}(\text{Z})>150\,$GeV and at least two jets, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the leading jet$\Delta\Phi(\text{Z},\text{j}_1)$, for events with $p_{\text{T}}(\text{Z})>150\,$GeV and at least two jets.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the leading jet$\Delta\Phi(\text{Z},\text{j}_1)$, for events with $p_{\text{T}}(\text{Z})>150\,$GeV and at least two jets, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the leading jet$\Delta\Phi(\text{Z},\text{j}_1)$, for events with $p_{\text{T}}(\text{Z})>150\,$GeV and at least two jets.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the leading jet$\Delta\Phi(\text{Z},\text{j}_1)$, for events with $p_{\text{T}}(\text{Z})>150\,$GeV and at least three jets, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the leading jet$\Delta\Phi(\text{Z},\text{j}_1)$, for events with $p_{\text{T}}(\text{Z})>150\,$GeV and at least three jets.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the 2$^{\text{nd}}$ leading jet$\Delta\Phi(\text{Z},\text{j}_2)$, for events with $p_{\text{T}}(\text{Z})>150\,$GeV and at least three jets, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the 2$^{\text{nd}}$ leading jet$\Delta\Phi(\text{Z},\text{j}_2)$, for events with $p_{\text{T}}(\text{Z})>150\,$GeV and at least three jets.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the 3$^{\text{rd}}$ leading jet$\Delta\Phi(\text{Z},\text{j}_3)$, for events with $p_{\text{T}}(\text{Z})>150\,$GeV and at least three jets, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the 3$^{\text{rd}}$ leading jet$\Delta\Phi(\text{Z},\text{j}_3)$, for events with $p_{\text{T}}(\text{Z})>150\,$GeV and at least three jets.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the leading jet, $\Delta\Phi(\text{Z},\text{j}_1)$, for events with $p_{\text{T}}(\text{Z})>300\,$GeV and at least one jet, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the leading jet, $\Delta\Phi(\text{Z},\text{j}_1)$, for events with $p_{\text{T}}(\text{Z})>300\,$GeV and at least one jet.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the leading jet, $\Delta\Phi(\text{Z},\text{j}_1)$, for events with $p_{\text{T}}(\text{Z})>300\,$GeV and at least two jets, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the leading jet, $\Delta\Phi(\text{Z},\text{j}_1)$, for events with $p_{\text{T}}(\text{Z})>300\,$GeV and at least two jets.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the leading jet, $\Delta\Phi(\text{Z},\text{j}_1)$, for events with $p_{\text{T}}(\text{Z})>300\,$GeV and at least three jets, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the leading jet, $\Delta\Phi(\text{Z},\text{j}_1)$, for events with $p_{\text{T}}(\text{Z})>300\,$GeV and at least three jets.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the 2$^{\text{nd}}$ leading jet, $\Delta\Phi(\text{Z},\text{j}_2)$, for events with $p_{\text{T}}(\text{Z})>300\,$GeV, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the 2$^{\text{nd}}$ leading jet, $\Delta\Phi(\text{Z},\text{j}_2)$, for events with $p_{\text{T}}(\text{Z})>300\,$GeV.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the 3$^{\text{rd}}$ leading jet, $\Delta\Phi(\text{Z},\text{j}_3)$, for events with $p_{\text{T}}(\text{Z})>300\,$GeV, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the 3$^{\text{rd}}$ leading jet, $\Delta\Phi(\text{Z},\text{j}_3)$, for events with $p_{\text{T}}(\text{Z})>300\,$GeV.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the leading jet, $\Delta\Phi(\text{Z},\text{j}_1)$, for events with at least three jets, $p_{\text{T}}(\text{Z})>150\,$GeV, and $H_{\text{T}}>300\,$GeV, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the leading jet, $\Delta\Phi(\text{Z},\text{j}_1)$, for events with at least three jets, $p_{\text{T}}(\text{Z})>150\,$GeV, and $H_{\text{T}}>300\,$GeV.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the 2$^{\text{nd}}$ leading jet, $\Delta\Phi(\text{Z},\text{j}_2)$, for events with at least three jets, $p_{\text{T}}(\text{Z})>150\,$GeV, and $H_{\text{T}}>300\,$GeV, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the 2$^{\text{nd}}$ leading jet, $\Delta\Phi(\text{Z},\text{j}_2)$, for events with at least three jets, $p_{\text{T}}(\text{Z})>150\,$GeV, and $H_{\text{T}}>300\,$GeV.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the 3$^{\text{rd}}$ leading jet, $\Delta\Phi(\text{Z},\text{j}_1)$, for events with at least three jets, $p_{\text{T}}(\text{Z})>150\,$GeV, and $H_{\text{T}}>300\,$GeV, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the Z boson and the 3$^{\text{rd}}$ leading jet, $\Delta\Phi(\text{Z},\text{j}_1)$, for events with at least three jets, $p_{\text{T}}(\text{Z})>150\,$GeV, and $H_{\text{T}}>300\,$GeV.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the two leading jets, $\Delta\Phi(\text{j}_1,\text{j}_2)$, for events with at least three jets, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the two leading jets, $\Delta\Phi(\text{j}_1,\text{j}_2)$, for events with at least three jets.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the two 1$^{\text{st}}$ and 3$^{\text{rd}}$ leading jets, $\Delta\Phi(\text{j}_1,\text{j}_3)$, for events with at least three jets, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the two 1$^{\text{st}}$ and 3$^{\text{rd}}$ leading jets, $\Delta\Phi(\text{j}_1,\text{j}_3)$, for events with at least three jets.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the two 2$^{\text{nd}}$ and 3$^{\text{rd}}$ leading jets, $\Delta\Phi(\text{j}_1,\text{j}_3)$, for events with at least three jets, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the two 2$^{\text{nd}}$ and 3$^{\text{rd}}$ leading jets, $\Delta\Phi(\text{j}_1,\text{j}_3)$, for events with at least three jets.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the two leading jets, $\Delta\Phi(\text{j}_1,\text{j}_2)$, for events with at least three jets and $p_{\text{T}}(\text{Z})>150\,$GeV, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the two leading jets, $\Delta\Phi(\text{j}_1,\text{j}_2)$, for events with at least three jets and $p_{\text{T}}(\text{Z})>150\,$GeV.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the 1$^{\text{st}}$ and 3$^{\text{rd}}$ leading jets, $\Delta\Phi(\text{j}_1,\text{j}_3)$, for events with at least three jets and $p_{\text{T}}(\text{Z})>150\,$GeV, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the 1$^{\text{st}}$ and 3$^{\text{rd}}$ leading jets, $\Delta\Phi(\text{j}_1,\text{j}_3)$, for events with at least three jets and $p_{\text{T}}(\text{Z})>150\,$GeV.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the 2$^{\text{nd}}$ and 3$^{\text{rd}}$ leading jets, $\Delta\Phi(\text{j}_2,\text{j}_3)$, for events with at least three jets and $p_{\text{T}}(\text{Z})>150\,$GeV, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the 2$^{\text{nd}}$ and 3$^{\text{rd}}$ leading jets, $\Delta\Phi(\text{j}_2,\text{j}_3)$, for events with at least three jets and $p_{\text{T}}(\text{Z})>150\,$GeV.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the 1$^{\text{st}}$ and 2$^{\text{nd}}$ leading jets, $\Delta\Phi(\text{j}_1,\text{j}_2)$, for events with at least three jets and $p_{\text{T}}(\text{Z})>300\,$GeV, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the 1$^{\text{st}}$ and 2$^{\text{nd}}$ leading jets, $\Delta\Phi(\text{j}_1,\text{j}_2)$, for events with at least three jets and $p_{\text{T}}(\text{Z})>300\,$GeV.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the 1$^{\text{st}}$ and 3$^{\text{rd}}$ leading jets, $\Delta\Phi(\text{j}_1,\text{j}_3)$, for events with at least three jets and $p_{\text{T}}(\text{Z})>300\,$GeV, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the 1$^{\text{st}}$ and 3$^{\text{rd}}$ leading jets, $\Delta\Phi(\text{j}_1,\text{j}_3)$, for events with at least three jets and $p_{\text{T}}(\text{Z})>300\,$GeV.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the 2$^{\text{nd}}$ and 3$^{\text{rd}}$ leading jets, $\Delta\Phi(\text{j}_1,\text{j}_3)$, for events with at least three jets and $p_{\text{T}}(\text{Z})>300\,$GeV, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the azimuthal angle between the 2$^{\text{nd}}$ and 3$^{\text{rd}}$ leading jets, $\Delta\Phi(\text{j}_1,\text{j}_3)$, for events with at least three jets and $p_{\text{T}}(\text{Z})>300\,$GeV.

The cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the mass of the system made of the two leading jets, $m_{\text{j}_1\text{j}_1}$, and breakdown of the relative uncertainty.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production measured as a function of the mass of the system made of the two leading jets, $m_{\text{j}_1\text{j}_1}$.

The cross section for Z($\rightarrow\ell\ell$) + jets production as a function of the leading jet transverse momentum and rapidity

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production as a function of the leading jet transverse momentum and rapidity

The cross section for Z($\rightarrow\ell\ell$) + jets production as a function of the Z boson and leading jet rapidities

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production as a function of the Z boson and leading jet rapidities

The cross section for Z($\rightarrow\ell\ell$) + jets production as a function of the rapidities of the Z boson and leading jet, and of the transverse momentum of the jet for the same configuration.

Bin-to-bin correlation in the the cross section for Z($\rightarrow\ell\ell$) + jets production as a function of the rapidities of the Z boson and leading jet, and of the transverse momentum of the jet for the same configuration.

Differential cross section times dimuon branching fraction of Y(1S) as a function of $y^{Y}_{CM}$ in pPb collisions. The global uncertainty arises from the integrated luminosity uncertainty in pPb collisions.

Differential cross section times dimuon branching fraction of Y(2S) as a function of $y^{Y}_{CM}$ in pPb collisions. The global uncertainty arises from the integrated luminosity uncertainty in pPb collisions.

Differential cross section times dimuon branching fraction of Y(3S) as a function of $y^{Y}_{CM}$ in pPb collisions. The global uncertainty arises from the integrated luminosity uncertainty in pPb collisions.

Differential cross section times dimuon branching fraction of Y(1S) as a function of pT in pp collisions. The global uncertainty arises from the integrated luminosity uncertainty in pp collisions.

Differential cross section times dimuon branching fraction of Y(2S) as a function of pT in pp collisions. The global uncertainty arises from the integrated luminosity uncertainty in pp collisions.

Differential cross section times dimuon branching fraction of Y(3S) as a function of pT in pp collisions. The global uncertainty arises from the integrated luminosity uncertainty in pp collisions.

Differential cross section times dimuon branching fraction of Y(1S) as a function of $|y^{Y}_{CM}|$ in pp collisions. The global uncertainty arises from the integrated luminosity uncertainty in pp collisions.

Differential cross section times dimuon branching fraction of Y(2S) as a function of $|y^{Y}_{CM}|$ in pp collisions. The global uncertainty arises from the integrated luminosity uncertainty in pp collisions.

Differential cross section times dimuon branching fraction of Y(3S) as a function of $|y^{Y}_{CM}|$ in pp collisions. The global uncertainty arises from the integrated luminosity uncertainty in pp collisions.

Nuclear modification factor of Y(1S) as a function of pT. The global uncertainty arises from the integrated luminosity uncertainties in pPb and pp collisions.

Nuclear modification factor of Y(2S) as a function of pT. The global uncertainty arises from the integrated luminosity uncertainties in pPb and pp collisions.

Nuclear modification factor of Y(3S) as a function of pT. The global uncertainty arises from the integrated luminosity uncertainties in pPb and pp collisions.

Nuclear modification factor of Y(1S) as a function of $y^{Y}_{CM}$. The global uncertainty arises from the integrated luminosity uncertainties in pPb and pp collisions.

Nuclear modification factor of Y(2S) as a function of $y^{Y}_{CM}$. The global uncertainty arises from the integrated luminosity uncertainties in pPb and pp collisions.

Nuclear modification factor of Y(3S) as a function of $y^{Y}_{CM}$. The global uncertainty arises from the integrated luminosity uncertainties in pPb and pp collisions.

Nuclear modification factor of Y(1S) at forward and backward $y^{Y}_{CM}$ for pT < 6 GeV/c. The global uncertainty arises from the integrated luminosity uncertainties in pPb and pp collisions.

Nuclear modification factor of Y(2S) at forward and backward $y^{Y}_{CM}$ for pT < 6 GeV/c. The global uncertainty arises from the integrated luminosity uncertainties in pPb and pp collisions.

Nuclear modification factor of Y(3S) at forward and backward $y^{Y}_{CM}$ for pT < 6 GeV/c. The global uncertainty arises from the integrated luminosity uncertainties in pPb and pp collisions.

Nuclear modification factor of Y(1S) at forward and backward $y^{Y}_{CM}$ for 6 < pT < 30 GeV/c. The global uncertainty arises from the integrated luminosity uncertainties in pPb and pp collisions.

Nuclear modification factor of Y(2S) at forward and backward $y^{Y}_{CM}$ for 6 < pT < 30 GeV/c. The global uncertainty arises from the integrated luminosity uncertainties in pPb and pp collisions.

Nuclear modification factor of Y(3S) at forward and backward $y^{Y}_{CM}$ for 6 < pT < 30 GeV/c. The global uncertainty arises from the integrated luminosity uncertainties in pPb and pp collisions.

RFB of Y(1S) versus $N^{|\eta_{lab}|<2.4}_{tracks}$.

RFB of Y(2S) versus $N^{|\eta_{lab}|<2.4}_{tracks}$.

RFB of Y(3S) versus $N^{|\eta_{lab}|<2.4}_{tracks}$.

RFB of Y(1S) versus $E^{|\eta_{lab}|>4}_{T}$.

RFB of Y(2S) versus $E^{|\eta_{lab}|>4}_{T}$.

RFB of Y(3S) versus $E^{|\eta_{lab}|>4}_{T}$.

Nuclear modification factor of Y(1S), Y(2S), and Y(3S) integrated over pT and $y^{Y}_{CM}$. The global uncertainty arises from the integrated luminosity uncertainties in pPb and pp collisions.

Expected $+ 1$ s.d. lower limit contour on the $m_{\mathrm{W}_{\mathrm{KK}}}$ and $m_{\mathrm{R}}$ plane after combinign with an analysis of the all-hadronic final state.

Expected - 1 s.d. lower limit contour on the $m_{\mathrm{W}_{\mathrm{KK}}}$ and $m_{\mathrm{R}}$ plane after combinign with an analysis of the all-hadronic final state.

Observed lower limit contour on the $m_{\mathrm{W}_{\mathrm{KK}}}$ and $m_{\mathrm{R}}$ plane after combinign with an analysis of the all-hadronic final state.

Post-fit distributions of the reconstructed $\ell\nu$+jets system ($m_{\mathrm{j}\ell\nu}$, $m_{\mathrm{jj}\ell\nu}$) in data and simulation for SR1.

Post-fit distributions of the reconstructed $\ell\nu$+jets system ($m_{\mathrm{j}\ell\nu}$, $m_{\mathrm{jj}\ell\nu}$) in data and simulation for SR2.

Post-fit distributions of the reconstructed $\ell\nu$+jets system ($m_{\mathrm{j}\ell\nu}$, $m_{\mathrm{jj}\ell\nu}$) in data and simulation for SR3.

Post-fit distributions of the reconstructed $\ell\nu$+jets system ($m_{\mathrm{j}\ell\nu}$, $m_{\mathrm{jj}\ell\nu}$) in data and simulation for SR5.

Post-fit distributions of the reconstructed $\ell\nu$+jets system ($m_{\mathrm{j}\ell\nu}$, $m_{\mathrm{jj}\ell\nu}$) in data and simulation for SR6.