Showing 25 of 297 results
We determine the CKM matrix-element magnitude $|V_{cb}|$ using $\overline{B}^0\to D^{*+}\ell^-\bar\nu_\ell$ decays reconstructed in $189 \, \mathrm{fb}^{-1}$ of collision data collected by the Belle II experiment, located at the SuperKEKB $e^+e^-$ collider. Partial decay rates are reported as functions of the recoil parameter $w$ and three decay angles separately for electron and muon final states. We obtain $|V_{cb}|$ using the Boyd-Grinstein-Lebed and Caprini-Lellouch-Neubert parametrizations, and find $|V_{cb}|_\mathrm{BGL}=(40.57\pm 0.31 \pm 0.95\pm 0.58)\times 10^{-3}$ and $|V_{cb}|_\mathrm{CLN}=(40.13 \pm 0.27 \pm 0.93\pm 0.58 )\times 10^{-3}$ with the uncertainties denoting statistical components, systematic components, and components from the lattice QCD input, respectively. The branching fraction is measured to be ${\cal B}(\overline{B}^0\to D^{*+}\ell^-\bar\nu_\ell)=(4.922 \pm 0.023 \pm 0.220)\%$. The ratio of branching fractions for electron and muon final states is found to be $0.998 \pm 0.009 \pm 0.020$. In addition, we determine the forward-backward angular asymmetry and the $D^{*+}$ longitudinal polarization fractions. All results are compatible with lepton-flavor universality in the Standard Model.
Measured partial decay rates $\Delta\Gamma$ (in units of $10^{-15}$ GeV)
Average of normalized decay rates over $\overline{B}^0\to D^{*+} e^- \bar\nu_e$ and $\overline{B}^0\to D^{*+} \mu^- \bar\nu_\mu$ decays
Full experimental (statistical and systematic) correlations (in \%) of the partial decay rates for the $\overline{B}^0\to D^{*+} e^- \bar\nu_e$ and $\overline{B}^0\to D^{*+} \mu^- \bar\nu_\mu$ decays.
Full experimental (statistical and systematic) correlations (in \%) of the normalized partial decay rates over the $\overline{B}^0\to D^{*+} e^- \bar\nu_e$ and $\overline{B}^0\to D^{*+} \mu^- \bar\nu_\mu$ decays.
Measured partial decay rates $\Delta\Gamma$ (in units of $10^{-15}$ GeV) using the matrix inversion unfolding method
Average of normalized decay rates that are determined using the matrix inversion unfolding method
Full experimental (statistical and systematic) correlations (in \%) of the partial decay rates determined with the matrix inversion unfolding method for the $\overline{B}^0\to D^{*+} e^- \bar\nu_e$ and $\overline{B}^0\to D^{*+} \mu^- \bar\nu_\mu$ decays.
Full experimental (statistical and systematic) correlations (in \%) of the normalized partial decay rates determined using the matrix inversion unfolding method
We present the first comprehensive tests of light-lepton universality in the angular distributions of semileptonic $B^0$-meson decays to charged spin-1 charmed mesons. We measure five angular-asymmetry observables as functions of the decay recoil that are sensitive to lepton-universality-violating contributions. We use events where one neutral $B$ is fully reconstructed in $\Upsilon\left(4S\right)\to{}B \overline{B}$ decays in data corresponding to $189~\mathrm{fb}^{-1}$ integrated luminosity from electron-positron collisions collected with the Belle II detector. We find no significant deviation from the standard model expectations.
Observed values of all angular asymmetry variables.
Full experimental covariance matrix of all angular asymmetry variables.
Additional spin-0 particles appear in many extensions of the standard model. We search for long-lived spin-0 particles $S$ in $B$-meson decays mediated by a $b\to s$ quark transition in $e^+e^-$ collisions at the $\Upsilon(4S)$ resonance at the Belle II experiment. Based on a sample corresponding to an integrated luminosity of $189 \mathrm{\,fb}^{-1}$, we observe no evidence for signal. We set model-independent upper limits on the product of branching fractions $\mathrm{Br}(B^0\to K^*(892)^0(\to K^+\pi^-)S)\times \mathrm{Br}(S\to x^+x^-)$ and $\mathrm{Br}(B^+\to K^+S)\times \mathrm{Br}(S\to x^+x^-)$, where $x^+x^-$ indicates $e^+e^-, \mu^+\mu^-, \pi^+\pi^-$, or $K^+K^-$, as functions of $S$ mass and lifetime at the level of $10^{-7}$.
Expected and observed candidates for $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) as a function of the reduced mediator candidate mass.
Expected and observed candidates for $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) as a function of the reduced mediator candidate mass.
Expected and observed candidates for $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) as a function of the reduced mediator candidate mass.
Expected and observed candidates for $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) as a function of the reduced mediator candidate mass.
Expected and observed candidates for $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) as a function of the reduced mediator candidate mass.
Expected and observed candidates for $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) as a function of the reduced mediator candidate mass.
Expected and observed candidates for $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) as a function of the reduced mediator candidate mass.
Expected and observed candidates for $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) as a function of the reduced mediator candidate mass.
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.001cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.003cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.005cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.007cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.01cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.025cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.05cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.1cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.25cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.5cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$1.0cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$2.5cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$5.0cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$10.0cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$25.0cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$50.0cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$100.0cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$200.0cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$400.0cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.001cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.003cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.005cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.007cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.01cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.025cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.05cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.1cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.25cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.5cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$1.0cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$2.5cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$5.0cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$10.0cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$25.0cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$50.0cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$100.0cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$200.0cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$400.0cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.001cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.003cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.005cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.007cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.01cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.025cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.05cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.1cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.25cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.5cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$1.0cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$2.5cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$5.0cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$10.0cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$25.0cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$50.0cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$100.0cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$200.0cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$400.0cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.001cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.003cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.005cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.007cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.01cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.025cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.05cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.1cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.25cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.5cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$1.0cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$2.5cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$5.0cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$10.0cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$25.0cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$50.0cm
Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$100.0cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.001cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.003cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.005cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.007cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.01cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.025cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.05cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.1cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.25cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.5cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$1.0cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$2.5cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$5.0cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$10.0cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$25.0cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$50.0cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$100.0cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$200.0cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$400.0cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.001cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.003cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.005cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.007cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.01cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.025cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.05cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.1cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.25cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.5cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$1.0cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$2.5cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$5.0cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$10.0cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$25.0cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$50.0cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$100.0cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$200.0cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$400.0cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.001cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.003cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.005cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.007cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.01cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.025cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.05cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.1cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.25cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.5cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$1.0cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$2.5cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$5.0cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$10.0cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$25.0cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$50.0cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$100.0cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$200.0cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$400.0cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.001cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.003cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.005cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.007cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.01cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.025cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.05cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.1cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.25cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.5cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$1.0cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$2.5cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$5.0cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$10.0cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$25.0cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$50.0cm
Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$100.0cm
Efficiencies for $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$)
Efficiencies for $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$)
Efficiencies for $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$)
Efficiencies for $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$)
Efficiencies for $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$)
Efficiencies for $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$)
Efficiencies for $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$)
Efficiencies for $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$)
We present a measurement of the differential shapes of exclusive $B\to D^* \ell \bar{\nu}_\ell$ ($B = B^-, \bar{B}^0 $ and $\ell = e, \mu$) decays with hadronic tag-side reconstruction for the full Belle data set of $711\,\mathrm{fb}^{-1}$ integrated luminosity. We extract the Caprini-Lellouch-Neubert (CLN) and Boyd-Grinstein-Lebed (BGL) form factor parameters and use an external input for the absolute branching fractions to determine the Cabibbo-Kobayashi-Maskawa matrix element and find $|V_{cb}|_\mathrm{CLN} = (40.1\pm0.9)\times 10^{-3}$ and $|V_{cb}|_\mathrm{BGL} = (40.6\pm 0.9)\times 10^{-3}$ with the zero-recoil lattice QCD point $\mathcal{F}(1) = 0.906 \pm 0.013$. We also perform a study of the impact of preliminary beyond zero-recoil lattice QCD calculations on the $|V_{cb}|$ determinations. Additionally, we present the lepton flavor universality ratio $R_{e\mu} = \mathcal{B}(B \to D^* e \bar{\nu}_e) / \mathcal{B}(B \to D^* \mu \bar{\nu}_\mu) = 0.990 \pm 0.021 \pm 0.023$, the electron and muon forward-backward asymmetry and their difference $\Delta A_{FB}=0.022\pm0.026\pm 0.007$, and the electron and muon $D^*$ longitudinal polarization fraction and their difference $\Delta F_L^{D^*} = 0.034 \pm 0.024 \pm 0.007$. The uncertainties quoted correspond to the statistical and systematic uncertainties, respectively.
Bins used in the average spectrum (equivalent to the B0 case binning)
Bins for each data point for B0 and B+ cases separately.
The fully averaged measured shape. The 40 entries correspond to 10 bins in w, cosThetaL, cosThetaV, and chi. For the binning see the file 'Binning.yaml'.
The full experimental statistical correlations for the averaged spectrum are shown. The index of the entry corresponds to the index of the corresponding central value.
The full experimental systematic correlations for the averaged spectrum are shown. The index of the entry corresponds to the index of the corresponding central value.
The individual measured shapes. The 160 entries correspond to the 10 bins in w, cosThetaL, cosThetaV, and chi. Index 0-40: B0 --> D* e nu Index 40-80: B0 --> D* mu nu Index 80-120: B+ --> D* e nu Index 120-160: B+ --> D* mu nu For the binning see the file 'Binning.yaml'.
The full experimental statistical correlations for the individual spectra are shown. The index of the entry corresponds to the index of the corresponding central value.
The full experimental systematic correlations for the individual spectra are shown. The index of the entry corresponds to the index of the corresponding central value.
The $L_{\mu}-L_{\tau}$ extension of the standard model predicts the existence of a lepton-flavor-universality-violating $Z^{\prime}$ boson that couples only to the heavier lepton families. We search for such a $Z^\prime$ through its invisible decay in the process $e^+ e^- \to \mu^+ \mu^- Z^{\prime}$. We use a sample of electron-positron collisions at a center-of-mass energy of 10.58GeV collected by the Belle II experiment in 2019-2020, corresponding to an integrated luminosity of 79.7fb$^{-1}$. We find no excess over the expected standard-model background. We set 90$\%$-confidence-level upper limits on the cross section for this process as well as on the coupling of the model, which ranges from $3 \times 10^{-3}$ at low $Z^{\prime}$ masses to 1 at $Z^{\prime}$ masses of 8$GeV/c^{2}$.
Observed 90% CL upper limits on the cross section $\sigma (e^+ e^- \to \mu^+ \mu^- Z', Z' \to $ invisible) as functions of the $Z'$ mass for the cases of negligible $\Gamma_{Z'}$ and for $\Gamma_{Z'} = 0.1 M_{Z'}$. Also shown are previous limits from Belle II.
Observed 90% CL upper limits on the coupling $g'$ for the fully invisible $L_\mu − L_\tau$ model as functions of the $Z'$ mass for the cases of negligible $\Gamma_{Z'}$ and for $\Gamma_{Z'} = 0.1 M_{Z'}$. Also shown are previous limits from NA64-e and Belle II searches. The red band shows the region that explains the muon anomalous magnetic moment $(g - 2)_\mu \pm 2 \sigma$. The vertical dashed line indicates the limit beyond which the hypothesis $B(Z' \to \chi\bar{\chi}) \approx 1$ is not respected in the negligible $\Gamma_{Z'}$ case.
Observed 90% CL upper limits on the coupling $g'$ for the vanilla $L_\mu − L_\tau$ model as functions of the $Z'$ mass. Also shown are previous limits from Belle II and NA64-e searches for invisible $Z'$ decays, and from Belle, BaBar and CMS searches for $Z'$ decays to muons (at 95% CL). The red band shows the region that explains the muon anomalous magnetic moment $(g - 2)_\mu \pm 2 \sigma$.
Best fit of the cross section.
A measurement of the top-quark mass ($m_t$) in the $t\bar{t}\rightarrow~\textrm{lepton}+\textrm{jets}$ channel is presented, with an experimental technique which exploits semileptonic decays of $b$-hadrons produced in the top-quark decay chain. The distribution of the invariant mass $m_{\ell\mu}$ of the lepton, $\ell$ (with $\ell=e,\mu$), from the $W$-boson decay and the muon, $\mu$, originating from the $b$-hadron decay is reconstructed, and a binned-template profile likelihood fit is performed to extract $m_t$. The measurement is based on data corresponding to an integrated luminosity of 36.1 fb$^{-1}$ of $\sqrt{s} = 13~\textrm{TeV}$$pp$ collisions provided by the Large Hadron Collider and recorded by the ATLAS detector. The measured value of the top-quark mass is $m_{t} = 174.41\pm0.39~(\textrm{stat.})\pm0.66~(\textrm{syst.})\pm0.25~(\textrm{recoil})~\textrm{GeV}$, where the third uncertainty arises from changing the PYTHIA8 parton shower gluon-recoil scheme, used in top-quark decays, to a recently developed setup.
Top mass measurement result.
List of all the individual sources of systematic uncertainty considered in the analysis. The individual sources, each corresponding to an independent nuisance parameter in the fit, are grouped into categories, as indicated in the first column. The second column shows the impact of each of the individual sources on the measurement, obtained as the shift on the top mass induced by a positive shift of the each of the nuisance parameters by its post-fit uncertainty. Sources for which no impact is indicated are neglected in the fit procedure as their impact on the total prediction is negligible in any of the bins. The last column shows the statistical uncertainty in each of the reported numbers as estimated with the bootstrap method.
Ranking, from top to bottom, of the main systematic uncertainties (excluding recoil) showing the pulls and the impact of the systematic uncertainties on the top mass, from the combined opposite sign (OS) and same sign (SS) binned-template profile likelihood fit to data. The OS or SS refers to the charge signs of the primary lepton and the soft muon. The gamma parameters are NPs used to describe the effect of the limited statistics of the sample.
Correlation matrix for the individual sources of systematic uncertainty considered in the analysis, for the combined opposite sign (OS) and same sign (SS) binned-template profile likelihood fit to data. The OS or SS refers to the charge signs of the primary lepton and the soft muon. The gamma parameters are NPs used to describe the effect of the limited statistics of the samples.
This paper presents studies of Bose-Einstein correlations (BEC) in proton-proton collisions at a centre-of-mass energy of 13 TeV, using data from the ATLAS detector at the CERN Large Hadron Collider. Data were collected in a special low-luminosity configuration with a minimum-bias trigger and a high-multiplicity track trigger, accumulating integrated luminosities of 151 $\mu$b$^{-1}$ and 8.4 nb$^{-1}$ respectively. The BEC are measured for pairs of like-sign charged particles, each with $|\eta|$ < 2.5, for two kinematic ranges: the first with particle $p_T$ > 100 MeV and the second with particle $p_T$ > 500 MeV. The BEC parameters, characterizing the source radius and particle correlation strength, are investigated as functions of charged-particle multiplicity (up to 300) and average transverse momentum of the pair (up to 1.5 GeV). The double-differential dependence on charged-particle multiplicity and average transverse momentum of the pair is also studied. The BEC radius is found to be independent of the charged-particle multiplicity for high charged-particle multiplicity (above 100), confirming a previous observation at lower energy. This saturation occurs independent of the transverse momentum of the pair.
Comparison of single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q) and C<sub>2</sub><sup>MC</sup>(Q), with the two-particle double-ratio correlation function, R<sub>2</sub>(Q), for the high-multiplicity track (HMT) events using the opposite hemisphere (OHP) like-charge particles pairs reference sample for k<sub>T</sub> - interval 1000 < k<sub>T</sub> ≤ 1500 MeV.
Comparison of single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q) and C<sub>2</sub><sup>MC</sup>(Q), with the two-particle double-ratio correlation function, R<sub>2</sub>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k<sub>T</sub> - interval 1000 < k<sub>T</sub> ≤ 1500 MeV.
The Bose-Einstein correlation (BEC) parameter R as a function of n<sub>ch</sub> for MB events using different MC generators in the calculation of R<sub>2</sub>(Q). The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.
The Bose-Einstein correlation (BEC) parameter R as a function of n<sub>ch</sub> for HMT events using different MC generators in the calculation of R<sub>2</sub>(Q). The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.
The Bose-Einstein correlation (BEC) parameter R as a function of k<sub>T</sub> for MB events using different MC generators in the calculation of R<sub>2</sub>(Q). The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.
The Bose-Einstein correlation (BEC) parameter λ as a function of k<sub>T</sub> for MB events using different MC generators in the calculation of R<sub>2</sub>(Q). The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.
The two-particle double-ratio correlation function, R<sub>2</sub>(Q), for pp collisions for track p<sub>T</sub> >100 MeV at √s=13 TeV in the multiplicity interval 71 ≤ n<sub>ch</sub> < 80 for the minimum-bias (MB) events. The blue dashed and red solid lines show the results of the exponential and Gaussian fits, respectively. The region excluded from the fits is shown. The statistical uncertainty and the systematic uncertainty for imperfections in the data reconstruction procedure are added in quadrature.
The two-particle double-ratio correlation function, R<sub>2</sub>(Q), for pp collisions for track p<sub>T</sub> >100 MeV at √s=13 TeV in the multiplicity interval 231 ≤ n<sub>ch</sub> < 300 for the high-multiplicity track (HMT) events. The blue dashed and red solid lines show the results of the exponential and Gaussian fits, respectively. The region excluded from the fits is shown. The statistical uncertainty and the systematic uncertainty for imperfections in the data reconstruction procedure are added in quadrature.
The dependence of the correlation strength, λ(m<sub>ch</sub>), on rescaled multiplicity, m<sub>ch</sub>, obtained from the exponential fit of the R<sub>2</sub>(Q) correlation functions for tracks with p<sub>T</sub> > 100 MeV and p<sub>T</sub> > 500 MeV at √s = 13 TeV for the minimum-bias (MB) and high multiplicity track (HMT) data. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the exponential fit of λ(m<sub>ch</sub>) for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively.
The dependence of the correlation strength, λ(m<sub>ch</sub>), on rescaled multiplicity, m<sub>ch</sub>, obtained from the exponential fit of the R<sub>2</sub>(Q) correlation functions for tracks with p<sub>T</sub> > 100 MeV and p<sub>T</sub> > 500 MeV at √s = 13 TeV for the minimum-bias (MB) and high multiplicity track (HMT) data. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the exponential fit of λ(m<sub>ch</sub>) for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively.
The dependence of the correlation strength, λ(m<sub>ch</sub>), on rescaled multiplicity, m<sub>ch</sub>, obtained from the exponential fit of the R<sub>2</sub>(Q) correlation functions for tracks with p<sub>T</sub> > 100 MeV and p<sub>T</sub> > 500 MeV at √s = 13 TeV for the minimum-bias (MB) and high multiplicity track (HMT) data. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the exponential fit of λ(m<sub>ch</sub>) for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively.
The dependence of the correlation strength, λ(m<sub>ch</sub>), on rescaled multiplicity, m<sub>ch</sub>, obtained from the exponential fit of the R<sub>2</sub>(Q) correlation functions for tracks with p<sub>T</sub> > 100 MeV and p<sub>T</sub> > 500 MeV at √s = 13 TeV for the minimum-bias (MB) and high multiplicity track (HMT) data. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the exponential fit of λ(m<sub>ch</sub>) for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively.
The dependence of the source radius, R(m<sub>ch</sub>), on m<sub>ch</sub>. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> < 1.2 for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m<sub>ch</sub> > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> > 1.45 with p<sub>T</sub> >100 MeV and for ∛m<sub>ch</sub> > 1.6 with p<sub>T</sub> >500 MeV, respectively.
The dependence of the source radius, R(m<sub>ch</sub>), on m<sub>ch</sub>. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> < 1.2 for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m<sub>ch</sub> > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> > 1.45 with p<sub>T</sub> >100 MeV and for ∛m<sub>ch</sub> > 1.6 with p<sub>T</sub> >500 MeV, respectively.
The dependence of the source radius, R(m<sub>ch</sub>), on m<sub>ch</sub>. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> < 1.2 for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m<sub>ch</sub> > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> > 1.45 with p<sub>T</sub> >100 MeV and for ∛m<sub>ch</sub> > 1.6 with p<sub>T</sub> >500 MeV, respectively.
The dependence of the source radius, R(m<sub>ch</sub>), on m<sub>ch</sub>. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> < 1.2 for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m<sub>ch</sub> > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> > 1.45 with p<sub>T</sub> >100 MeV and for ∛m<sub>ch</sub> > 1.6 with p<sub>T</sub> >500 MeV, respectively.
The dependence of the R(m<sub>ch</sub>) on ∛m<sub>ch</sub>. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> < 1.2 for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m<sub>ch</sub> > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> > 1.45 with p<sub>T</sub> >100 MeV and for ∛m<sub>ch</sub> > 1.6 with p<sub>T</sub> >500 MeV, respectively
The dependence of the R(m<sub>ch</sub>) on ∛m<sub>ch</sub>. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> < 1.2 for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m<sub>ch</sub> > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> > 1.45 with p<sub>T</sub> >100 MeV and for ∛m<sub>ch</sub> > 1.6 with p<sub>T</sub> >500 MeV, respectively
The dependence of the R(m<sub>ch</sub>) on ∛m<sub>ch</sub>. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> < 1.2 for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m<sub>ch</sub> > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> > 1.45 with p<sub>T</sub> >100 MeV and for ∛m<sub>ch</sub> > 1.6 with p<sub>T</sub> >500 MeV, respectively
The dependence of the R(m<sub>ch</sub>) on ∛m<sub>ch</sub>. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> < 1.2 for p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond ∛m<sub>ch</sub> > 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m<sub>ch</sub>) for ∛m<sub>ch</sub> > 1.45 with p<sub>T</sub> >100 MeV and for ∛m<sub>ch</sub> > 1.6 with p<sub>T</sub> >500 MeV, respectively
Comparison of single-ratio two-particle correlation functions, using the unlike-charge particle (UCP) pair reference sample, for minimum-bias (MB) events, showing C<sub>2</sub><sup>data</sup>(Q) (top panel) at 13 TeV (black circles) and 7 TeV (open blue circles), and the ratio of C<sub>2</sub><sup>7 TeV</sup> (Q) to C<sub>2</sub><sup>13 TeV</sup> (Q) (bottom panel). Comparison of C<sub>2</sub><sup>data</sup> (Q) for representative multiplicity region 3.09 < m<sub>ch</sub> ≤ 3.86. The statistical and systematic uncertainties, combined in quadrature, are presented. The systematic uncertainties include track efficiency, Coulomb correction, non-closure and multiplicity-unfolding uncertainties.
Comparison of single-ratio two-particle correlation functions, using the unlike-charge particle (UCP) pair reference sample, for minimum-bias (MB) events, showing C<sub>2</sub><sup>data</sup>(Q) (top panel) at 13 TeV (black circles) and 7 TeV (open blue circles), and the ratio of C<sub>2</sub><sup>7 TeV</sup> (Q) to C<sub>2</sub><sup>13 TeV</sup> (Q) (bottom panel). Comparison of C<sub>2</sub><sup>data</sup> (Q) for representative k<sub>T</sub> region 400 < k<sub>T</sub> ≤500 MeV. The statistical and systematic uncertainties, combined in quadrature, are presented. The systematic uncertainties include track efficiency, Coulomb correction, non-closure and multiplicity-unfolding uncertainties.
The k<sub>T</sub> dependence of the correlation strength, λ(k<sub>T</sub>), obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions for events with multiplicity n<sub>ch</sub> ≥ 2 and transfer momentum of tracks with p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to λ(k<sub>T</sub>).
The k<sub>T</sub> dependence of the correlation strength, λ(k<sub>T</sub>), obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions for events with multiplicity n<sub>ch</sub> ≥ 2 and transfer momentum of tracks with p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to λ(k<sub>T</sub>).
The k<sub>T</sub> dependence of the correlation strength, λ(k<sub>T</sub>), obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions for events with multiplicity n<sub>ch</sub> ≥ 2 and transfer momentum of tracks with p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to λ(k<sub>T</sub>).
The k<sub>T</sub> dependence of the correlation strength, λ(k<sub>T</sub>), obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions for events with multiplicity n<sub>ch</sub> ≥ 2 and transfer momentum of tracks with p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to λ(k<sub>T</sub>).
The k<sub>T</sub> dependence of the source radius, R(k<sub>T</sub>), obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions for events with multiplicity n<sub>ch</sub> ≥ 2 and transfer momentum of tracks with p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to R(k<sub>T</sub>).
The k<sub>T</sub> dependence of the source radius, R(k<sub>T</sub>), obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions for events with multiplicity n<sub>ch</sub> ≥ 2 and transfer momentum of tracks with p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to R(k<sub>T</sub>).
The k<sub>T</sub> dependence of the source radius, R(k<sub>T</sub>), obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions for events with multiplicity n<sub>ch</sub> ≥ 2 and transfer momentum of tracks with p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to R(k<sub>T</sub>).
The k<sub>T</sub> dependence of the source radius, R(k<sub>T</sub>), obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions for events with multiplicity n<sub>ch</sub> ≥ 2 and transfer momentum of tracks with p<sub>T</sub> >100 MeV and p<sub>T</sub> >500 MeV at √s=13 TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to R(k<sub>T</sub>).
The two-dimensional dependence on m<sub>ch</sub> and k<sub>T</sub> for p<sub>T</sub> > 100 MeV for the correlation strength, λ, obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions using the MB sample for m<sub>ch</sub> ≤ 3.08 and the HMT sample for m<sub>ch</sub> > 3.08.
The two-dimensional dependence on m<sub>ch</sub> and k<sub>T</sub> for p<sub>T</sub> > 100 MeV for the source radius, R, obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions using the MB sample for m<sub>ch</sub> ≤ 3.08 and the HMT sample for m<sub>ch</sub> > 3.08.
The parameter λ for p<sub>T</sub> > 100 MeV as a function of k<sub>T</sub> in selected low m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter λ for p<sub>T</sub> > 100 MeV as a function of k<sub>T</sub> in selected low m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter λ for p<sub>T</sub> > 100 MeV as a function of k<sub>T</sub> in selected high m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter λ for p<sub>T</sub> > 100 MeV as a function of k<sub>T</sub> in selected high m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter λ for p<sub>T</sub> > 100 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.1 and 0.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter λ for p<sub>T</sub> > 100 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.1 and 0.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter λ for p<sub>T</sub> > 100 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.5 and 1.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter λ for p<sub>T</sub> > 100 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.5 and 1.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 100 MeV as a function of k<sub>T</sub> in selected low m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 100 MeV as a function of k<sub>T</sub> in selected low m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 100 MeV as a function of k<sub>T</sub> in selected high m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 100 MeV as a function of k<sub>T</sub> in selected high m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 100 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.1 and 0.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 100 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.1 and 0.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 100 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.5 and 1.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 100 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.5 and 1.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
The fit parameter μ describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter μ on m<sub>ch</sub> for tracks with p<sub>T</sub> >100 MeV (p<sub>T</sub> >500 MeV).
The fit parameter μ describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter μ on m<sub>ch</sub> for tracks with p<sub>T</sub> >100 MeV (p<sub>T</sub> >500 MeV).
The fit parameter μ describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter μ on m<sub>ch</sub> for tracks with p<sub>T</sub> >100 MeV (p<sub>T</sub> >500 MeV).
The fit parameter μ describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter μ on m<sub>ch</sub> for tracks with p<sub>T</sub> >100 MeV (p<sub>T</sub> >500 MeV).
The fit parameter ν describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter ν on m<sub>ch</sub> for tracks with p<sub>T</sub> >100 MeV (p<sub>T</sub> >500 MeV).
The fit parameter ν describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter ν on m<sub>ch</sub> for tracks with p<sub>T</sub> >100 MeV (p<sub>T</sub> >500 MeV).
The fit parameter ν describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter ν on m<sub>ch</sub> for tracks with p<sub>T</sub> >100 MeV (p<sub>T</sub> >500 MeV).
The fit parameter ν describing the dependence of the correlation strength, λ, on charged-particle scaled multiplicity, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter ν on m<sub>ch</sub> for tracks with p<sub>T</sub> >100 MeV (p<sub>T</sub> >500 MeV).
The parameter ξ describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m<sub>ch</sub>, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the saturated value of the parameter ξ for m<sub>ch</sub> > 3.0 for tracks with p<sub>T</sub> >100 MeV and for m<sub>ch</sub> > 2.8 for tracks with p<sub>T</sub> >500 MeV, respectively.
The parameter ξ describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m<sub>ch</sub>, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the saturated value of the parameter ξ for m<sub>ch</sub> > 3.0 for tracks with p<sub>T</sub> >100 MeV and for m<sub>ch</sub> > 2.8 for tracks with p<sub>T</sub> >500 MeV, respectively.
The parameter ξ describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m<sub>ch</sub>, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the saturated value of the parameter ξ for m<sub>ch</sub> > 3.0 for tracks with p<sub>T</sub> >100 MeV and for m<sub>ch</sub> > 2.8 for tracks with p<sub>T</sub> >500 MeV, respectively.
The parameter ξ describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m<sub>ch</sub>, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the saturated value of the parameter ξ for m<sub>ch</sub> > 3.0 for tracks with p<sub>T</sub> >100 MeV and for m<sub>ch</sub> > 2.8 for tracks with p<sub>T</sub> >500 MeV, respectively.
The parameter κ describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m<sub>ch</sub>, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the exponential fit to the parameter κ for tracks with p<sub>T</sub> >100 MeV and for tracks with p<sub>T</sub> >500 MeV, respectively.
The parameter κ describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m<sub>ch</sub>, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the exponential fit to the parameter κ for tracks with p<sub>T</sub> >100 MeV and for tracks with p<sub>T</sub> >500 MeV, respectively.
The parameter κ describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m<sub>ch</sub>, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the exponential fit to the parameter κ for tracks with p<sub>T</sub> >100 MeV and for tracks with p<sub>T</sub> >500 MeV, respectively.
The parameter κ describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m<sub>ch</sub>, for track p<sub>T</sub>>100 MeV and track p<sub>T</sub>>500 MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at √s = 13 TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the exponential fit to the parameter κ for tracks with p<sub>T</sub> >100 MeV and for tracks with p<sub>T</sub> >500 MeV, respectively.
The two-dimensional dependence on m<sub>ch</sub> and k<sub>T</sub> for p<sub>T</sub> > 500 MeV for the correlation strength, λ, obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions using the MB sample for m<sub>ch</sub> ≤ 3.08 and the HMT sample for m<sub>ch</sub> > 3.08.
The two-dimensional dependence on m<sub>ch</sub> and k<sub>T</sub> for p<sub>T</sub> > 500 MeV for the source radius, R, obtained from the exponential fit to the R<sub>2</sub>(Q) correlation functions using the MB sample for m<sub>ch</sub> ≤ 3.08 and the HMT sample for m<sub>ch</sub> > 3.08.
The parameter λ for p<sub>T</sub> > 500 MeV as a function of k<sub>T</sub> in selected low m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter λ for p<sub>T</sub> > 500 MeV as a function of k<sub>T</sub> in selected low m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter λ for p<sub>T</sub> > 500 MeV as a function of k<sub>T</sub> in selected high m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter λ for p<sub>T</sub> > 500 MeV as a function of k<sub>T</sub> in selected high m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter λ for p<sub>T</sub> > 500 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.5 and 1.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter λ for p<sub>T</sub> > 500 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.5 and 1.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 500 MeV as a function of k<sub>T</sub> in selected low m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 500 MeV as a function of k<sub>T</sub> in selected low m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 500 MeV as a function of k<sub>T</sub> in selected high m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 500 MeV as a function of k<sub>T</sub> in selected high m<sub>ch</sub> intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 500 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.5 and 1.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
The parameter R for p<sub>T</sub> > 500 MeV as a function of m<sub>ch</sub> in k<sub>T</sub> intervals between 0.5 and 1.5 GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.
ATLAS and CMS results for the source radius R as a function of n<sub>ch</sub> in pp interactions at 13 TeV. The CMS results (open circles) have been adjusted (by the CMS collaboration) to the ATLAS kinematic region∶ p<sub>T</sub> > 100 MeV and |η|<2.5. The ATLAS uncertainties are the sum in quadrature of the statistical and asymmetric systematic uncertainties. For CMS, only the systematic uncertainties are shown since the statistical uncertainties are smaller than the marker size. The dashed blue (ATLAS) and black (CMS) lines represent the fit to ∛n<sub>ch</sub> at low multiplicity, continued as dotted lines beyond the fit range. The solid green (ATLAS) and broken black (CMS) lines indicate the plateau level at high multiplicity.
ATLAS and CMS results for the source radius R as a function of n<sub>ch</sub> in pp interactions at 13 TeV. The CMS results (open circles) have been adjusted (by the CMS collaboration) to the ATLAS kinematic region∶ p<sub>T</sub> > 100 MeV and |η|<2.5. The ATLAS uncertainties are the sum in quadrature of the statistical and asymmetric systematic uncertainties. For CMS, only the systematic uncertainties are shown since the statistical uncertainties are smaller than the marker size. The dashed blue (ATLAS) and black (CMS) lines represent the fit to ∛n<sub>ch</sub> at low multiplicity, continued as dotted lines beyond the fit range. The solid green (ATLAS) and broken black (CMS) lines indicate the plateau level at high multiplicity.
ATLAS and CMS results for the source radius R as a function of n<sub>ch</sub> in pp interactions at 13 TeV. The CMS results (open circles) have been adjusted (by the CMS collaboration) to the ATLAS kinematic region∶ p<sub>T</sub> > 100 MeV and |η|<2.5. The ATLAS uncertainties are the sum in quadrature of the statistical and asymmetric systematic uncertainties. For CMS, only the systematic uncertainties are shown since the statistical uncertainties are smaller than the marker size. The dashed blue (ATLAS) and black (CMS) lines represent the fit to ∛n<sub>ch</sub> at low multiplicity, continued as dotted lines beyond the fit range. The solid green (ATLAS) and broken black (CMS) lines indicate the plateau level at high multiplicity.
ATLAS and CMS results for the source radius R as a function of ∛n<sub>ch</sub> in pp interactions at 13 TeV. The CMS results (open circles) have been adjusted (by the CMS collaboration) to the ATLAS kinematic region∶ p<sub>T</sub> > 100 MeV and |η|<2.5. The ATLAS uncertainties are the sum in quadrature of the statistical and asymmetric systematic uncertainties. For CMS, only the systematic uncertainties are shown since the statistical uncertainties are smaller than the marker size. The dashed blue (ATLAS) and black (CMS) lines represent the fit to ∛n<sub>ch</sub> at low multiplicity, continued as dotted lines beyond the fit range. The solid green (ATLAS) and broken black (CMS) lines indicate the plateau level at high multiplicity.
ATLAS and CMS results for the source radius R as a function of ∛n<sub>ch</sub> in pp interactions at 13 TeV. The CMS results (open circles) have been adjusted (by the CMS collaboration) to the ATLAS kinematic region∶ p<sub>T</sub> > 100 MeV and |η|<2.5. The ATLAS uncertainties are the sum in quadrature of the statistical and asymmetric systematic uncertainties. For CMS, only the systematic uncertainties are shown since the statistical uncertainties are smaller than the marker size. The dashed blue (ATLAS) and black (CMS) lines represent the fit to ∛n<sub>ch</sub> at low multiplicity, continued as dotted lines beyond the fit range. The solid green (ATLAS) and broken black (CMS) lines indicate the plateau level at high multiplicity.
ATLAS and CMS results for the source radius R as a function of ∛n<sub>ch</sub> in pp interactions at 13 TeV. The CMS results (open circles) have been adjusted (by the CMS collaboration) to the ATLAS kinematic region∶ p<sub>T</sub> > 100 MeV and |η|<2.5. The ATLAS uncertainties are the sum in quadrature of the statistical and asymmetric systematic uncertainties. For CMS, only the systematic uncertainties are shown since the statistical uncertainties are smaller than the marker size. The dashed blue (ATLAS) and black (CMS) lines represent the fit to ∛n<sub>ch</sub> at low multiplicity, continued as dotted lines beyond the fit range. The solid green (ATLAS) and broken black (CMS) lines indicate the plateau level at high multiplicity.
Systematic uncertainties (in percent) in the correlation strength, λ, and source radius, R, for the exponential fit of the two-particle double-ratio correlation functions, R<sub>2</sub>(Q), for p<sub>T</sub> > 100 MeV at √s= 13 TeV for the MB and HMT events. The choice of MC generator gives rise to asymmetric uncertainties, denoted by uparrow and downarrow. This asymmetry propagates through to the cumulative uncertainty. The columns under ‘Uncertainty range’ show the range of systematic uncertainty from the fits in the various n<sub>ch</sub> intervals.
The results of the fits to the dependencies of the correlation strength, λ, and source radius, R, on the average rescaled charged-particle multiplicity, m<sub>ch</sub>, for |η| < 2.5 and both p<sub>T</sub> > 100 MeV and p<sub>T</sub> > 500 MeV at √s = 13 TeV for the minimum-bias (MB) and the high-multiplicity track (HMT) events. The parameters γ and δ resulting from a joint fit to the MB and HMT data are presented. The total uncertainties are shown.
The results of the fits to the dependencies of the correlation strength, λ, and source radius, R, on the pair average transverse momentum, k<sub>T</sub>, for various functional forms and for minimum-bias (MB) and high-multiplicity track (HMT) events for p<sub>T</sub> > 100 MeV and p<sub>T</sub> > 500 MeV at √s = 13 TeV. The total uncertainties are shown.
The Bose-Einstein correlation (BEC) parameters λ and R as a function of n<sub>ch</sub> and k<sub>T</sub> using different MC generators in the calculation of R<sub>2</sub>(Q). (a) λ versus n<sub>ch</sub> for MB events, (b) λ versus n<sub>ch</sub> for HMT events, (c) λ versus k<sub>T</sub> and (d) R versus k<sub>T</sub> for MB events. The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.
The Bose-Einstein correlation (BEC) parameters λ and R as a function of n<sub>ch</sub> and k<sub>T</sub> using different MC generators in the calculation of R<sub>2</sub>(Q). (a) λ versus n<sub>ch</sub> for MB events, (b) λ versus n<sub>ch</sub> for HMT events, (c) λ versus k<sub>T</sub> and (d) R versus k<sub>T</sub> for MB events. The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.
The Bose-Einstein correlation (BEC) parameters λ and R as a function of n<sub>ch</sub> and k<sub>T</sub> using different MC generators in the calculation of R<sub>2</sub>(Q). (a) λ versus n<sub>ch</sub> for MB events, (b) λ versus n<sub>ch</sub> for HMT events, (c) λ versus k<sub>T</sub> and (d) R versus k<sub>T</sub> for MB events. The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.
The Bose-Einstein correlation (BEC) parameters λ and R as a function of n<sub>ch</sub> and k<sub>T</sub> using different MC generators in the calculation of R<sub>2</sub>(Q). (a) λ versus n<sub>ch</sub> for MB events, (b) λ versus n<sub>ch</sub> for HMT events, (c) λ versus k<sub>T</sub> and (d) R versus k<sub>T</sub> for MB events. The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 10, (b) 11 < n<sub>ch</sub> ≤ 20, (c) 21 < n<sub>ch</sub> ≤ 30, (d) 31 < n<sub>ch</sub> ≤ 40, (e) 41 < n<sub>ch</sub> ≤ 50, (f) 51 < n<sub>ch</sub> ≤ 60, (g) 61 < n<sub>ch</sub> ≤ 70, (h) 71 < n<sub>ch</sub> ≤ 80 and (i) 81 < n<sub>ch</sub> ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 10, (b) 11 < n<sub>ch</sub> ≤ 20, (c) 21 < n<sub>ch</sub> ≤ 30, (d) 31 < n<sub>ch</sub> ≤ 40, (e) 41 < n<sub>ch</sub> ≤ 50, (f) 51 < n<sub>ch</sub> ≤ 60, (g) 61 < n<sub>ch</sub> ≤ 70, (h) 71 < n<sub>ch</sub> ≤ 80 and (i) 81 < n<sub>ch</sub> ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 10, (b) 11 < n<sub>ch</sub> ≤ 20, (c) 21 < n<sub>ch</sub> ≤ 30, (d) 31 < n<sub>ch</sub> ≤ 40, (e) 41 < n<sub>ch</sub> ≤ 50, (f) 51 < n<sub>ch</sub> ≤ 60, (g) 61 < n<sub>ch</sub> ≤ 70, (h) 71 < n<sub>ch</sub> ≤ 80 and (i) 81 < n<sub>ch</sub> ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 10, (b) 11 < n<sub>ch</sub> ≤ 20, (c) 21 < n<sub>ch</sub> ≤ 30, (d) 31 < n<sub>ch</sub> ≤ 40, (e) 41 < n<sub>ch</sub> ≤ 50, (f) 51 < n<sub>ch</sub> ≤ 60, (g) 61 < n<sub>ch</sub> ≤ 70, (h) 71 < n<sub>ch</sub> ≤ 80 and (i) 81 < n<sub>ch</sub> ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 10, (b) 11 < n<sub>ch</sub> ≤ 20, (c) 21 < n<sub>ch</sub> ≤ 30, (d) 31 < n<sub>ch</sub> ≤ 40, (e) 41 < n<sub>ch</sub> ≤ 50, (f) 51 < n<sub>ch</sub> ≤ 60, (g) 61 < n<sub>ch</sub> ≤ 70, (h) 71 < n<sub>ch</sub> ≤ 80 and (i) 81 < n<sub>ch</sub> ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 10, (b) 11 < n<sub>ch</sub> ≤ 20, (c) 21 < n<sub>ch</sub> ≤ 30, (d) 31 < n<sub>ch</sub> ≤ 40, (e) 41 < n<sub>ch</sub> ≤ 50, (f) 51 < n<sub>ch</sub> ≤ 60, (g) 61 < n<sub>ch</sub> ≤ 70, (h) 71 < n<sub>ch</sub> ≤ 80 and (i) 81 < n<sub>ch</sub> ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 10, (b) 11 < n<sub>ch</sub> ≤ 20, (c) 21 < n<sub>ch</sub> ≤ 30, (d) 31 < n<sub>ch</sub> ≤ 40, (e) 41 < n<sub>ch</sub> ≤ 50, (f) 51 < n<sub>ch</sub> ≤ 60, (g) 61 < n<sub>ch</sub> ≤ 70, (h) 71 < n<sub>ch</sub> ≤ 80 and (i) 81 < n<sub>ch</sub> ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 10, (b) 11 < n<sub>ch</sub> ≤ 20, (c) 21 < n<sub>ch</sub> ≤ 30, (d) 31 < n<sub>ch</sub> ≤ 40, (e) 41 < n<sub>ch</sub> ≤ 50, (f) 51 < n<sub>ch</sub> ≤ 60, (g) 61 < n<sub>ch</sub> ≤ 70, (h) 71 < n<sub>ch</sub> ≤ 80 and (i) 81 < n<sub>ch</sub> ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 10, (b) 11 < n<sub>ch</sub> ≤ 20, (c) 21 < n<sub>ch</sub> ≤ 30, (d) 31 < n<sub>ch</sub> ≤ 40, (e) 41 < n<sub>ch</sub> ≤ 50, (f) 51 < n<sub>ch</sub> ≤ 60, (g) 61 < n<sub>ch</sub> ≤ 70, (h) 71 < n<sub>ch</sub> ≤ 80 and (i) 81 < n<sub>ch</sub> ≤ 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 91 < n<sub>ch</sub> ≤ 100, (b) 101 < n<sub>ch</sub> ≤ 125, (c) 126 < n<sub>ch</sub> ≤ 150, (d) 151 < n<sub>ch</sub> ≤ 200, (e) 201 < n<sub>ch</sub> ≤ 250. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 91 < n<sub>ch</sub> ≤ 100, (b) 101 < n<sub>ch</sub> ≤ 125, (c) 126 < n<sub>ch</sub> ≤ 150, (d) 151 < n<sub>ch</sub> ≤ 200, (e) 201 < n<sub>ch</sub> ≤ 250. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 91 < n<sub>ch</sub> ≤ 100, (b) 101 < n<sub>ch</sub> ≤ 125, (c) 126 < n<sub>ch</sub> ≤ 150, (d) 151 < n<sub>ch</sub> ≤ 200, (e) 201 < n<sub>ch</sub> ≤ 250. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 91 < n<sub>ch</sub> ≤ 100, (b) 101 < n<sub>ch</sub> ≤ 125, (c) 126 < n<sub>ch</sub> ≤ 150, (d) 151 < n<sub>ch</sub> ≤ 200, (e) 201 < n<sub>ch</sub> ≤ 250. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 91 < n<sub>ch</sub> ≤ 100, (b) 101 < n<sub>ch</sub> ≤ 125, (c) 126 < n<sub>ch</sub> ≤ 150, (d) 151 < n<sub>ch</sub> ≤ 200, (e) 201 < n<sub>ch</sub> ≤ 250. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 101 < n<sub>ch</sub> ≤ 110, (b) 111 < n<sub>ch</sub> ≤ 120, (c) 121 < n<sub>ch</sub> ≤ 130, (d) 131 < n<sub>ch</sub> ≤ 140, (e) 141 < n<sub>ch</sub> ≤ 155, (f) 156 < n<sub>ch</sub> ≤ 175, (g) 176 < n<sub>ch</sub> ≤ 200, (h) 201 < n<sub>ch</sub> ≤ 230 and (i) 231 < n<sub>ch</sub> ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 101 < n<sub>ch</sub> ≤ 110, (b) 111 < n<sub>ch</sub> ≤ 120, (c) 121 < n<sub>ch</sub> ≤ 130, (d) 131 < n<sub>ch</sub> ≤ 140, (e) 141 < n<sub>ch</sub> ≤ 155, (f) 156 < n<sub>ch</sub> ≤ 175, (g) 176 < n<sub>ch</sub> ≤ 200, (h) 201 < n<sub>ch</sub> ≤ 230 and (i) 231 < n<sub>ch</sub> ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 101 < n<sub>ch</sub> ≤ 110, (b) 111 < n<sub>ch</sub> ≤ 120, (c) 121 < n<sub>ch</sub> ≤ 130, (d) 131 < n<sub>ch</sub> ≤ 140, (e) 141 < n<sub>ch</sub> ≤ 155, (f) 156 < n<sub>ch</sub> ≤ 175, (g) 176 < n<sub>ch</sub> ≤ 200, (h) 201 < n<sub>ch</sub> ≤ 230 and (i) 231 < n<sub>ch</sub> ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 101 < n<sub>ch</sub> ≤ 110, (b) 111 < n<sub>ch</sub> ≤ 120, (c) 121 < n<sub>ch</sub> ≤ 130, (d) 131 < n<sub>ch</sub> ≤ 140, (e) 141 < n<sub>ch</sub> ≤ 155, (f) 156 < n<sub>ch</sub> ≤ 175, (g) 176 < n<sub>ch</sub> ≤ 200, (h) 201 < n<sub>ch</sub> ≤ 230 and (i) 231 < n<sub>ch</sub> ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 101 < n<sub>ch</sub> ≤ 110, (b) 111 < n<sub>ch</sub> ≤ 120, (c) 121 < n<sub>ch</sub> ≤ 130, (d) 131 < n<sub>ch</sub> ≤ 140, (e) 141 < n<sub>ch</sub> ≤ 155, (f) 156 < n<sub>ch</sub> ≤ 175, (g) 176 < n<sub>ch</sub> ≤ 200, (h) 201 < n<sub>ch</sub> ≤ 230 and (i) 231 < n<sub>ch</sub> ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 101 < n<sub>ch</sub> ≤ 110, (b) 111 < n<sub>ch</sub> ≤ 120, (c) 121 < n<sub>ch</sub> ≤ 130, (d) 131 < n<sub>ch</sub> ≤ 140, (e) 141 < n<sub>ch</sub> ≤ 155, (f) 156 < n<sub>ch</sub> ≤ 175, (g) 176 < n<sub>ch</sub> ≤ 200, (h) 201 < n<sub>ch</sub> ≤ 230 and (i) 231 < n<sub>ch</sub> ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 101 < n<sub>ch</sub> ≤ 110, (b) 111 < n<sub>ch</sub> ≤ 120, (c) 121 < n<sub>ch</sub> ≤ 130, (d) 131 < n<sub>ch</sub> ≤ 140, (e) 141 < n<sub>ch</sub> ≤ 155, (f) 156 < n<sub>ch</sub> ≤ 175, (g) 176 < n<sub>ch</sub> ≤ 200, (h) 201 < n<sub>ch</sub> ≤ 230 and (i) 231 < n<sub>ch</sub> ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 101 < n<sub>ch</sub> ≤ 110, (b) 111 < n<sub>ch</sub> ≤ 120, (c) 121 < n<sub>ch</sub> ≤ 130, (d) 131 < n<sub>ch</sub> ≤ 140, (e) 141 < n<sub>ch</sub> ≤ 155, (f) 156 < n<sub>ch</sub> ≤ 175, (g) 176 < n<sub>ch</sub> ≤ 200, (h) 201 < n<sub>ch</sub> ≤ 230 and (i) 231 < n<sub>ch</sub> ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 101 < n<sub>ch</sub> ≤ 110, (b) 111 < n<sub>ch</sub> ≤ 120, (c) 121 < n<sub>ch</sub> ≤ 130, (d) 131 < n<sub>ch</sub> ≤ 140, (e) 141 < n<sub>ch</sub> ≤ 155, (f) 156 < n<sub>ch</sub> ≤ 175, (g) 176 < n<sub>ch</sub> ≤ 200, (h) 201 < n<sub>ch</sub> ≤ 230 and (i) 231 < n<sub>ch</sub> ≤ 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n<sub>ch</sub> - intervals∶ (a) 2 < n<sub>ch</sub> ≤ 9, (b) 10 < n<sub>ch</sub> ≤ 18, (c) 19 < n<sub>ch</sub> ≤ 27, (d) 28 < n<sub>ch</sub> ≤ 36, (e) 37 < n<sub>ch</sub> ≤ 45, (f) 46 < n<sub>ch</sub> ≤ 54, (g) 55 < n<sub>ch</sub> ≤ 63, (h) 64 < n<sub>ch</sub> ≤ 72, (i) 73 < n<sub>ch</sub> ≤ 81, (j) 82 < n<sub>ch</sub> ≤ 90, (k) 91 < n<sub>ch</sub> ≤ 113, and (l) 114 < n<sub>ch</sub> ≤ 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The single-ratio two-particle correlation functions, C<sub>2</sub><sup>data</sup>(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k<sub>T</sub> - intervals∶ (a) 100 < k<sub>T</sub> ≤ 200 MeV, (b) 200 < k<sub>T</sub> ≤ 300 MeV, (c) 300 < k<sub>T</sub> ≤ 400 MeV, (d) 400 < k<sub>T</sub> ≤ 500 MeV, (e) 500 < k<sub>T</sub> ≤ 600 MeV, (f) 600 < k<sub>T</sub> ≤ 700 MeV, (g) 700 < k<sub>T</sub> ≤ 1000 MeV, and (h) 1000 < k<sub>T</sub> ≤ 1500 MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.
The correlation strength, λ, and source radius, R, of the exponential fits to the two-particle double-ratio correlation functions, R<sub>2</sub>(Q), in dependence on the multiplicity, m<sub>ch</sub>, intervals for the minimum-bias (MB) and the high-multiplicity track (HMT) events for p<sub>T</sub> > 100 MeV at √s = 13 TeV. Statistical uncertainties for √χ<sup>2</sup>/ndf>1 are corrected by the √χ<sup>2</sup>/ndf. The total uncertainties are shown.
The correlation strength, λ, and source radius, R, of the exponential fits to the two-particle double-ratio correlation functions, R<sub>2</sub>(Q), in dependence on the multiplicity, m<sub>ch</sub>, intervals for the minimum-bias (MB) and the high-multiplicity track (HMT) events for p<sub>T</sub> > 500 MeV at √s = 13 TeV. Statistical uncertainties for √χ<sup>2</sup>/ndf>1 are corrected by the √χ<sup>2</sup>/ndf. The total uncertainties are shown.
The correlation strength, λ, and source radius, R, of the exponential fits to the two-particle double-ratio correlation functions, R<sub>2</sub>(Q), in dependence on the pair transverse momentum, k<sub>T</sub>, intervals for the minimum-bias (MB) and the high-multiplicity track (HMT) events for p<sub>T</sub> > 100 MeV at √s = 13 TeV. Statistical uncertainties for √χ<sup>2</sup>/ndf>1 are corrected by the √χ<sup>2</sup>/ndf. The total uncertainties are shown.
The correlation strength, λ, and source radius, R, of the exponential fits to the two-particle double-ratio correlation functions, R<sub>2</sub>(Q), in dependence on the pair transverse momentum, k<sub>T</sub>, intervals for the minimum-bias (MB) and the high-multiplicity track (HMT) events for p<sub>T</sub> > 500 MeV at √s = 13 TeV. Statistical uncertainties for √χ<sup>2</sup>/ndf>1 are corrected by the √χ<sup>2</sup>/ndf. The total uncertainties are shown.
We present the measurement of the first to fourth order moments of the four-momentum transfer squared, $q^2$, of inclusive $B \rightarrow X_c \ell^+ \nu_{\ell}$ decays using the full Belle data set of 711 $\mathrm{fb}^{-1}$ of integrated luminosity at the $\Upsilon(4S)$ resonance where $\ell = e, \mu$. The determination of these moments and their systematic uncertainties open new pathways to determine the absolute value of the CKM matrix element $V_{cb}$ using a reduced set of matrix elements of the heavy quark expansion. In order to identify and reconstruct the $X_c$ system, we reconstruct one of the two $B$-mesons using machine learning techniques in fully hadronic decay modes. The moments are measured with progressively increasing threshold selections on $q^2$ starting with a lower value of 3.0 $\mathrm{GeV}^2$ in steps of 0.5 $\mathrm{GeV}^2$ up to a value of 10.0 $\mathrm{GeV}^2$. The measured moments are further unfolded, correcting for reconstruction and selection effects as well as QED final state radiation. We report the moments separately for electron and muon final states and observe no lepton flavor universality violating effects.
First $q^2$ moment in GeV$^2$ for the electron channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Second $q^2$ moment in GeV$^4$ for the electron channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Third $q^2$ moment in GeV$^6$ for the electron channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Fourth $q^2$ moment in GeV$^8$ for the electron channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
First $q^2$ moment in GeV$^2$ for the muon channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Second $q^2$ moment in GeV$^4$ for the muon channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Third $q^2$ moment in GeV$^6$ for the muon channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Fourth $q^2$ moment in GeV$^8$ for the muon channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Second central $q^2$ moment in GeV$^4$ for the electron channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Third central $q^2$ moment in GeV$^6$ for the electron channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Fourth central $q^2$ moment in GeV$^8$ for the electron channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Second central $q^2$ moment in GeV$^4$ for the muon channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Third central $q^2$ moment in GeV$^6$ for the muon channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Fourth central $q^2$ moment in GeV$^8$ for the muon channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the first and the first $q^2$ moment in the electron channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the first and the second $q^2$ moment in the electron channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the first and the third $q^2$ moment in the electron channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the first and the fourth $q^2$ moment in the electron channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the second and the second $q^2$ moment in the electron channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the second and the third $q^2$ moment in the electron channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the second and the fourth $q^2$ moment in the electron channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the third and the third $q^2$ moment in the electron channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the third and the fourth $q^2$ moment in the electron channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the fourth and the fourth $q^2$ moment in the electron channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the first and the first $q^2$ moment in the muon channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the first and the second $q^2$ moment in the muon channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the first and the third $q^2$ moment in the muon channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the first and the fourth $q^2$ moment in the muon channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the second and the second $q^2$ moment in the muon channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the second and the third $q^2$ moment in the muon channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the second and the fourth $q^2$ moment in the muon channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the third and the third $q^2$ moment in the muon channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the third and the fourth $q^2$ moment in the muon channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the fourth and the fourth $q^2$ moment in the muon channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the first and the second central central $q^2$ moment in the electron channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the first and the third central $q^2$ moment in the electron channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the first and the fourth central $q^2$ moment in the electron channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the second and the second central $q^2$ moment in the electron channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the second and the third central $q^2$ moment in the electron channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the second and the fourth central $q^2$ moment in the electron channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the third and the third central $q^2$ moment in the electron channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the third and the fourth central $q^2$ moment in the electron channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the fourth and the fourth central $q^2$ moment in the electron channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the first and the second central central $q^2$ moment in the muon channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the first and the third central $q^2$ moment in the muon channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the first and the fourth central $q^2$ moment in the muon channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the second and the second central $q^2$ moment in the muon channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the second and the third central $q^2$ moment in the muon channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the second and the fourth central $q^2$ moment in the muon channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the third and the third central $q^2$ moment in the muon channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the third and the fourth central $q^2$ moment in the muon channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
Correlation coefficients for the different lower thresholds between the fourth and the fourth central $q^2$ moment in the muon channel with lower $q^2$ thresholds ranging from $3.0$ GeV$^2$ to $10.0$ GeV$^2$ in steps of $0.5$ GeV$^2$.
The first measurements of differential branching fractions of inclusive semileptonic ${B \to X_u \, \ell^+\, \nu_{\ell}}$ decays are performed using the full Belle data set of 711 fb$^{-1}$ of integrated luminosity at the $\Upsilon(4S)$ resonance and for $\ell = e, \mu$. Differential branching fractions are reported as a function of the lepton momentum, the four-momentum-transfer squared, light-cone momenta, the hadronic mass, and the hadronic mass squared. They are obtained by subtracting the backgrounds from semileptonic ${B \to X_c \, \ell^+\, \nu_{\ell}}$ decays and other processes, and corrected for resolution and acceptance effects. The measured distributions are compared to predictions from inclusive and hybrid ${B \to X_u \, \ell^+\, \nu_{\ell}}$ calculations.
The measured differential branching fractions as a function of the lepton energy in the $B$ rest frame ($E_\ell^B$).
The measured differential branching fractions as a function of the four-momentum-transfer squared of the $B$ to the $X_u$ system $q^{2}$.
The measured differential branching fractions as a function of the invariant hadronic mass of the $X_u$ system ($M_X$).
The measured differential branching fractions as a function of the invariant hadronic mass squared of the $X_u$ system ($M_X^2$).
The measured differential branching fractions as a function of the light-cone momenta of the hadronic $X_u$ system [$P_+ = (E_X^B - |old{p}_X^B|)$].
The measured differential branching fractions as a function of the light-cone momenta of the hadronic $X_u$ system [$P_- = (E_X^B + |old{p}_X^B|)$].
The background-subtracted yields as a function of $E_\ell^B$.
The background-subtracted yields as a function of $q^2$.
The background-subtracted yields as a function of $M_X$.
The background-subtracted yields as a function of $M_X^2$.
The background-subtracted yields as a function of $P_+$. [$P_+ = (E_X^B - |P_X^B|)$]
The background-subtracted yields as a function of $P_-$. [$P_- = (E_X^B + |P_X^B|)$].
The full experimental correlation matrix for the background-subtracted spectrum of the lepton energy in the $B$ rest frame ($E_\ell^B$).
The full experimental correlation matrix for the background-subtracted spectrum of $q^2$).
The full experimental correlation matrix for the background-subtracted spectrum of $M_X$.
The full experimental correlation matrix for the background-subtracted spectrum of $M_X^2$.
The full experimental correlation matrix for the background-subtracted spectrum of $P_+$.
The full experimental correlation matrix for the background-subtracted spectrum of $P_-$.
Migration matrix of $E_\ell^B$ [in %].
Migration matrix of $q^2$ [in %].
Migration matrix of $M_X$ [in %].
Migration matrix of $M_X^2$ [in %].
Migration matrix of $P_+$ [in %].
Migration matrix of $P_-$ [in %].
The total correction factors and phase space acceptance as a function of the invariant hadronic mass of the $X_u$ system ($M_X$).
The total correction factors and phase space acceptance as a function of the invariant hadronic mass squared of the $X_u$ system ($M_X^2$).
The total correction factors and phase space acceptance as a function of the lepton energy in the $B$ rest frame ($E_\ell^B$).
The total correction factors and phase space acceptance as a function of the four-momentum-transfer squared of the $B$ to the $X_u$ system ($q^2$).
The total correction factors and phase space acceptance as a function of $P_+$.
The total correction factors and phase space acceptance as a function of $P_-$.
The statistical correlations of the differential branching fractions are shown. The matrix elements are ordered for $M_{X}$, $M_{X}^{2}$, $q^{2}$, $E_{\ell}^{B}$, $P_{+}$ and $P_{-}$.
The full experimental (statistical and systematical) correlations of the differential branching fractions are shown. The matrix elements are ordered for $M_{X}$, $M_{X}^{2}$, $q^{2}$, $E_{\ell}^{B}$, $P_{+}$ and $P_{-}$.
The total partial branching fraction with $E_{\ell}^{B} > 1$ GeV. The order of entries is: the 2D fit result of Phys. Rev. D 104, 012008 (2021), the results calcuated with the differential branching fractions of $M_{X}$, $M_{X}^{2}$, $q^{2}$, $E_{\ell}^{B}$, $P_{+}$ and $P_{-}$
The full experimental correlations between the total partial branching fractions from summing the individual bins are shown. The matrix elements are saved in the order of $M_{X}$, $M_{X}^{2}$, $q^{2}$, $E_{\ell}^{B}$, $P_{+}$ and $P_{-}$.
The first moment of the measured differential branching fraction of the lepton energy in the $B$ rest frame ($E_\ell^B$).
The second moment of the measured differential branching fraction of the lepton energy in the $B$ rest frame ($E_\ell^B$).
The third moment of the measured differential branching fraction of the lepton energy in the $B$ rest frame ($E_\ell^B$).
The first moment of the measured differential branching fraction of $q^2$.
The second moment of the measured differential branching fraction of $q^2$.
The third moment of the measured differential branching fraction of $q^2$.
The first moment of the measured differential branching fraction of $M_{X}$.
The second moment of the measured differential branching fraction of $M_{X}$.
The third moment of the measured differential branching fraction of $M_{X}$.
The first moment of the measured differential branching fraction of $P_{+}$.
The second moment of the measured differential branching fraction of $P_{+}$.
The third moment of the measured differential branching fraction of $P_{+}$.
The first moment of the measured differential branching fraction of $P_{-}$.
The second moment of the measured differential branching fraction of $P_{-}$.
The third moment of the measured differential branching fraction of $P_{-}$.
The matrix elements are saved in the order of $M_{X}$, $q^{2}$, $E_{\ell}^{B}$, $P_{+}$ and $P_{-}$. For each variable, the entries is ordered for the first, second and third moments.
A search for the flavor-changing neutral-current decay $B^{+}\to K^{+}\nu\bar{\nu}$ is performed at the Belle II experiment at the SuperKEKB asymmetric energy electron-positron collider. The results are based on a data sample corresponding to an integrated luminosity of $63\,\mbox{fb}^{-1}$ collected at the $\Upsilon{(4S)}$ resonance and a sample of $9\,\mbox{fb}^{-1}$ collected at an energy $60\mathrm{\,Me\kern -0.1em V}$ below the resonance. A novel measurement method is employed, which exploits topological properties of the $B^{+}\to K^{+}\nu\bar{\nu}$ decay that differ from both generic bottom-meson decays and light-quark pair production. This inclusive tagging approach offers a higher signal efficiency compared to previous searches. No significant signal is observed. An upper limit on the branching fraction of $B^{+}\to K^{+}\nu\bar{\nu}$ of $4.1 \times 10^{-5}$ is set at the 90% confidence level.
- - - - - - - - Overview of HEPData Record - - - - - - - - <br/><br/> </ul> <b>Post-fit yields:</b> <ul> <li><a href="130199?version=1&table=Postfit%20yields%20Y(4S)">Y(4S)</a> <li><a href="130199?version=1&table=Postfit%20yields%20off-resonance">Off-resonance</a> </ul> <b>Exclusion limit:</b> <ul> <li><a href="130199?version=1&table=Expected%20and%20observed%20Limit">Expected limit and observed limit</a> </ul> <b>Efficiency:</b> <ul> <li><a href="130199?version=1&table=Selection%20efficiency">Selection efficiency as a function of $q^{2}$</a> </ul>
Yields in on-resonance data and as predicted by the simultaneous fit to the on- and off-resonance data, corresponding to an integrated luminosity of 63 and 9 fb$^{−1}$, respectively. The predicted yields are shown individually for charged and neutral B-meson decays and the five continuum background categories. The leftmost three bins belong to the first control region (CR1) with BDT$_{2} \in [0.93; 0.95]$ and the other nine bins correspond to the signal region (SR), three for each range of BDT$_{2} \in [0.95; 0.97; 0.99; 1.0]$. Each set of three bins is defined by $p_{T}(K^{+}) \in [0.5; 2.0; 2.4; 3.5] \rm{GeV}/c^{2}$.
Yields in off-resonance data and as predicted by the simultaneous fit to the on- and off-resonance data, corresponding to an integrated luminosity of 63 and 9 fb$^{−1}$, respectively. The predicted yields are shown individually for the five continuum background categories. The leftmost three bins belong to the third control region (CR3) with BDT$_{2} \in [0.93; 0.95]$ and the other nine bins correspond to the second control region (CR2), three for each range of BDT$_{2} \in [0.95; 0.97; 0.99; 1.0]$. Each set of three bins is defined by $p_{T}(K^{+}) \in [0.5; 2.0; 2.4; 3.5] \rm{GeV}/c^{2}$.
CL$_{s}$ value as a function of the branching fraction of $B^{+} \rightarrow K^{+} \nu \bar{\nu}$ for expected and observed signal yields and the corresponding upper limits at 90% confidence level (CL). The expected limit is derived for the background-only hypothesis. The observed limit is derived from a simultaneous fit to the on-resonance and off-resonance data, corresponding to an integrated luminosity of 63 fb$^{−1}$ and 9 fb$^{−1}$, respectively.
Signal efficiency as a function of the dineutrino invariant mass squared $q^{2}$ for events in the signal region (SR) ($\rm{BDT}_{1} > 0.9$ and $\rm{BDT}_{2} > 0.95$). The error bars indicate the statistical uncertainty.
A search for a chargino$-$neutralino pair decaying via the 125 GeV Higgs boson into photons is presented. The study is based on the data collected between 2015 and 2018 with the ATLAS detector at the LHC, corresponding to an integrated luminosity of 139 fb$^{-1}$ of $pp$ collisions at a centre-of-mass energy of 13 TeV. No significant excess over the expected background is observed. Upper limits at 95% confidence level for a massless $\tilde{\chi}^{0}_{1}$ are set on several electroweakino production cross-sections and the visible cross-section for beyond the Standard Model processes. In the context of simplified supersymmetric models, 95% confidence-level limits of up to 310 GeV in $m(\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2})$, where $m(\tilde{\chi}^{0}_{1})=0.5$ GeV, are set. Limits at 95% confidence level are also set on the $\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2}$ cross-section in the mass plane of $m(\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2})$ and $m(\tilde{\chi}^{0}_{1})$, and on scenarios with gravitino as the lightest supersymmetric particle. Upper limits at the 95% confidence-level are set on the higgsino production cross-section. Higgsino masses below 380 GeV are excluded for the case of the higgsino fully decaying into a Higgs boson and a gravitino.
The 95% CL model-independent upper limits computed from individual fits in each of 12 categories on the visible cross-section $\sigma_{\mathrm{vis}}^{\mathrm{BSM}} = \sigma \times A \times \epsilon$ for any $pp\to h(125~GeV) + E^{miss}_{T} \to \gamma\gamma + E^{miss}_{T}$ BSM processes.
Expected and observed 95% CL exclusion upper limits on the production cross-section of $\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2} \to W^{\pm}\tilde{\chi}^{0}_{1} h \tilde{\chi}^{0}_{1}$ as a function of $m(\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2})$.
The observed exclusion limit contours at 95% CL for the $\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2}$ production in the $m(\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2})$-$m(\tilde{\chi}^{0}_{1})$ plane.
The expected exclusion limit contours at 95% CL for the $\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2}$ production in the $m(\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2})$-$m(\tilde{\chi}^{0}_{1})$ plane.
The +1 $\sigma$ expected exclusion limit contours at 95% CL for the $\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2}$ production in the $m(\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2})$-$m(\tilde{\chi}^{0}_{1})$ plane.
The -1 $\sigma$ expected exclusion limit contours at 95% CL for the $\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2}$ production in the $m(\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2})$-$m(\tilde{\chi}^{0}_{1})$ plane.
The +1 $\sigma$ observed exclusion limit contours at 95% CL for the $\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2}$ production in the $m(\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2})$-$m(\tilde{\chi}^{0}_{1})$ plane.
The -1 $\sigma$ observed exclusion limit contours at 95% CL for the $\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2}$ production in the $m(\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2})$-$m(\tilde{\chi}^{0}_{1})$ plane.
The observed and expected exclusion limit at 95% CL for the $\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2}$ production in the $m(\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2})$-$m(\tilde{\chi}^{0}_{1})$ plane.
Expected and observed 95% CL exclusion upper limits on the higgsino production ($\tilde{\chi}\tilde{\chi} \equiv \tilde{\chi}^{0}_{1}\tilde{\chi}^{0}_{2}, \tilde{\chi}^{0}_{1}\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{0}_{2}\tilde{\chi}^{\pm}_{1}, \tilde{\chi}^{\pm}_{1}\tilde{\chi}^{\mp}_{1}$) cross-section in the signal of $h \tilde{G} h \tilde{G} $ as a function of the higgsino mass.
The distribution of $S_{E_\mathrm{T}^{\mathrm{miss}}}$ after the selection of diphoton candidates with $120~GeV < m_{\gamma\gamma} < 130~GeV$. Expected distributions are shown for the $\tilde{\chi}^{\pm}_{1} \tilde{\chi}^{0}_{2} \to W^{\pm} \tilde{\chi}^{0}_{1} h \tilde{\chi}^{0}_{1} $ signal with $m(\tilde{\chi}^{\pm}_{1} \tilde{\chi}^{0}_{2})=200~GeV$ and $m(\tilde{\chi}^{0}_{1})=0.5~GeV$, and the $h\tilde{G} h\tilde{G}$ signal with $m(\tilde{\chi}^{0}_{1})=150~GeV$ and $m(\tilde{G})=1~MeV$. These overlaid signal points are representative of the model kinematics. The sum in quadrature of the MC statistical and experimental systematic uncertainties in the total background is shown as the hatched bands, while the theoretical uncertainties in the background normalisation are not included. The $t\bar{t}\gamma$ and $t\bar{t}\gamma\gamma$ processes have a negligible contribution and are not represented. Overflow events are included in the rightmost bin. The lower panel shows the ratio of the data to the background.
Acceptance and efficiency for the $W^{\pm} \tilde{\chi}^{0}_{1} h \tilde{\chi}^{0}_{1}$ signal in each category.
Acceptance and efficiency for the $h \tilde{G} h \tilde{G}$ signal in each category.
Cut flow for the $W^{\pm} \tilde{\chi}^{0}_{1} h \tilde{\chi}^{0}_{1}$ signal sample at $m(\tilde{\chi}^{\pm}_{1} \tilde{\chi}^{0}_{2})=200~GeV$, $m(\tilde{\chi}^{0}_{1})=0.5~GeV$, with 260000 entries.
Cut flow for the $h \tilde{G} h \tilde{G}$ signal sample at $m(\tilde{\chi}^{0}_{1})=150~GeV$, $m(\tilde{G})=1~MeV$, with 50000 entries.
Event yields in the range 120 <$m\gamma\gamma$< 130 GeV for data, signal models, the SM Higgs boson background and non-resonant background in each analysis category after the fit.
Event yields in the range 120 <$m\gamma\gamma$< 130 GeV for data, signal models, the SM Higgs boson background and non-resonant background in each analysis category before the fit.
Acceptance for the $W^{\pm} \tilde{\chi}^{0}_{1} h \tilde{\chi}^{0}_{1}$ signals in the leptonic channel.
Efficiency for the $W^{\pm} \tilde{\chi}^{0}_{1} h \tilde{\chi}^{0}_{1}$ signals in the leptonic channel.
Acceptance for the $W^{\pm} \tilde{\chi}^{0}_{1} h \tilde{\chi}^{0}_{1}$ signals in the hadronic channel.
Efficiency for the $W^{\pm} \tilde{\chi}^{0}_{1} h \tilde{\chi}^{0}_{1}$ signals in the hadronic channel.
Acceptance for the $W^{\pm} \tilde{\chi}^{0}_{1} h \tilde{\chi}^{0}_{1}$ signals in the rest channel.
Efficiency for the $W^{\pm} \tilde{\chi}^{0}_{1} h \tilde{\chi}^{0}_{1}$ signals in the rest channel.
Acceptance for the $h \tilde{G} h \tilde{G}$ signals in the each channel.
Efficiency for the $h \tilde{G} h \tilde{G}$ signals in the each channel.
Electroweak symmetry breaking explains the origin of the masses of elementary particles through their interactions with the Higgs field. Besides the measurements of the Higgs boson properties, the study of the scattering of massive vector bosons with spin one allows the nature of electroweak symmetry breaking to be probed. Among all processes related to vector-boson scattering, the electroweak production of two jets and a $Z$-boson pair is a rare and important one. Here we report the observation of this process from proton-proton collision data corresponding to an integrated luminosity of 139/fb recorded at a centre-of-mass energy of 13 TeV with the ATLAS detector at the Large Hadron Collider. We consider two different final states originating from the decays of the $Z$-boson pair - one containing four charged leptons and the other containing two charged leptons and two neutrinos. The hypothesis of no electroweak production is rejected with a statistical significance of 5.7 $\sigma$, and the measured cross-section for electroweak production is consistent with the standard model prediction. In addition, we report cross-sections for inclusive production of a $Z$-boson pair and two jets for the two final states.
Measured and predicted fiducial cross-sections in both the lllljj and ll$\nu\nu$jj channels for the inclusive ZZjj processes. Uncertainties due to different sources are presented
Signal strength and significance of EW ZZjj processes
Signal strength and significance of EW ZZjj processes
Measured and predicted fiducial cross-sections in both the lllljj and ll$\nu\nu$jj channels for the inclusive ZZjj processes. Uncertainties due to different sources are presented.
Measured and predicted fiducial cross-sections in both the lllljj and ll$\nu\nu$jj channels for the inclusive ZZjj processes. Uncertainties due to different sources are presented.
Observed and expected multivariate discriminant distribution in the $\ell\ell\ell\ell jj$ QCD CR.
Observed and expected multivariate discriminant distribution in the $\ell\ell\ell\ell jj$ QCD CR.
Observed and expected multivariate discriminant distribution in the $\ell\ell\ell\ell jj$ SR.
Observed and expected multivariate discriminant distribution in the $\ell\ell\ell\ell jj$ SR.
Observed and expected multivariate discriminant distribution in the $\ell\ell\nu\nu jj$ SR.
Observed and expected multivariate discriminant distribution in the $\ell\ell\nu\nu jj$ SR.
The prevalence of hadronic jets at the LHC requires that a deep understanding of jet formation and structure is achieved in order to reach the highest levels of experimental and theoretical precision. There have been many measurements of jet substructure at the LHC and previous colliders, but the targeted observables mix physical effects from various origins. Based on a recent proposal to factorize physical effects, this Letter presents a double-differential cross-section measurement of the Lund jet plane using 139 fb$^{-1}$ of $\sqrt{s}=13$ TeV proton-proton collision data collected with the ATLAS detector using jets with transverse momentum above 675 GeV. The measurement uses charged particles to achieve a fine angular resolution and is corrected for acceptance and detector effects. Several parton shower Monte Carlo models are compared with the data. No single model is found to be in agreement with the measured data across the entire plane.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for use in MC tuning.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 0.00 < ln(R/#DeltaR) < 0.33.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 0.33 < ln(R/#DeltaR) < 0.67.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 0.67 < ln(R/#DeltaR) < 1.00.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 1.00 < ln(R/#DeltaR) < 1.33.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 1.33 < ln(R/#DeltaR) < 1.67.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 1.67 < ln(R/#DeltaR) < 2.00.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 2.00 < ln(R/#DeltaR) < 2.33.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 2.33 < ln(R/#DeltaR) < 2.67.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 2.67 < ln(R/#DeltaR) < 3.00.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 3.00 < ln(R/#DeltaR) < 3.33.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 3.33 < ln(R/#DeltaR) < 3.67.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 3.67 < ln(R/#DeltaR) < 4.00.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single vertical slice of the Lund jet plane between 4.00 < ln(R/#DeltaR) < 4.33.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 0.69 < ln(1/z) < 0.97.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 0.97 < ln(1/z) < 1.25.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 1.25 < ln(1/z) < 1.52.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 1.52 < ln(1/z) < 1.80.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 1.80 < ln(1/z) < 2.08.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 2.08 < ln(1/z) < 2.36.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 2.36 < ln(1/z) < 2.63.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 2.63 < ln(1/z) < 2.91.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 2.91 < ln(1/z) < 3.19.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 3.19 < ln(1/z) < 3.47.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 3.47 < ln(1/z) < 3.74.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 3.74 < ln(1/z) < 4.02.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 4.02 < ln(1/z) < 4.30.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 4.30 < ln(1/z) < 4.57.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 4.57 < ln(1/z) < 4.85.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 4.85 < ln(1/z) < 5.13.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 5.13 < ln(1/z) < 5.41.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 5.41 < ln(1/z) < 5.68.
Normalized differential cross-section of the Lund jet plane. The first systematic uncertainty is detector systematics, the second is background systematic uncertainties. The data is presented as a 1D distribution, for a single horizontal slice of the Lund jet plane between 5.68 < ln(1/z) < 5.96.
The summed covariance matrix of all systematic and statistical uncertainties associated with the measurement in bins of $\ln{(1/z)} \times \ln{(R/\Delta R)}$.
The summed covariance matrix of all statistical uncertainties associated with the measurement in bins of $\ln{(1/z)} \times \ln{(R/\Delta R)}$.
A search for long-lived particles decaying into hadrons and at least one muon is presented. The analysis selects events that pass a muon or missing-transverse-momentum trigger and contain a displaced muon track and a displaced vertex. The analyzed dataset of proton-proton collisions at $\sqrt{s} = 13$ TeV was collected with the ATLAS detector and corresponds to 136 fb$^{-1}$. The search employs dedicated reconstruction techniques that significantly increase the sensitivity to long-lived particle decays that occur in the ATLAS inner detector. Background estimates for Standard Model processes and instrumental effects are extracted from data. The observed event yields are compatible with those expected from background processes. The results are presented as limits at 95% confidence level on model-independent cross sections for processes beyond the Standard Model, and interpreted as exclusion limits in scenarios with pair-production of long-lived top squarks that decay via a small $R$-parity-violating coupling into a quark and a muon. Top squarks with masses up to 1.7 TeV are excluded for a lifetime of 0.1 ns, and masses below 1.3 TeV are excluded for lifetimes between 0.01 ns and 30 ns.
Vertex selection acceptance for the $\tilde{t}$ $R$-hadron benchmark model as a function of the transverse decay distance $r_{DV}$.
Vertex selection acceptance for the $\tilde{t}$ $R$-hadron benchmark model as a function of the transverse decay distance $r_{DV}$.
Vertex selection efficiency for the $\tilde{t}$ $R$-hadron benchmark model as a function of the transverse decay distance $r_{DV}$.
Vertex selection efficiency for the $\tilde{t}$ $R$-hadron benchmark model as a function of the transverse decay distance $r_{DV}$.
Track multiplicity $n_{Tracks}$ for preselected DVs in MET-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.
Track multiplicity $n_{Tracks}$ for preselected DVs in MET-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.
Track multiplicity $n_{Tracks}$ for preselected DVs in muon-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.
Track multiplicity $n_{Tracks}$ for preselected DVs in muon-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.
Invariant mass $m_{DV}$ for the highest-mass preselected DV with at least three associated tracks in MET-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.
Invariant mass $m_{DV}$ for the highest-mass preselected DV with at least three associated tracks in MET-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.
Invariant mass $m_{DV}$ for the highest-mass preselected DV with at least three associated tracks in muon-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.
Invariant mass $m_{DV}$ for the highest-mass preselected DV with at least three associated tracks in muon-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.
The observed event yields in the control, validation and signal regions are shown for the MET Trigger selections, along with the predicted background yields. The bottom panel shows the ratio of observed events to the total background yields. The errors represent the total uncertainty of the backgrounds prediction, including the statistical and systematic uncertainties added in quadrature.
The observed event yields in the control, validation and signal regions are shown for the MET Trigger selections, along with the predicted background yields. The bottom panel shows the ratio of observed events to the total background yields. The errors represent the total uncertainty of the backgrounds prediction, including the statistical and systematic uncertainties added in quadrature.
The observed event yields in the control, validation and signal regions are shown for the Muon Trigger selections, along with the predicted background yields. The bottom panel shows the ratio of observed events to the total background yields. The errors represent the total uncertainty of the backgrounds prediction, including the statistical and systematic uncertainties added in quadrature.
The observed event yields in the control, validation and signal regions are shown for the Muon Trigger selections, along with the predicted background yields. The bottom panel shows the ratio of observed events to the total background yields. The errors represent the total uncertainty of the backgrounds prediction, including the statistical and systematic uncertainties added in quadrature.
Expected exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Expected exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Expected (1 sigma band) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Expected (1 sigma band) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Expected (2 sigma band) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Expected (2 sigma band) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Observed exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Observed exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Observed (+1 sigma) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Observed (+1 sigma) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Observed (-1 sigma) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Observed (-1 sigma) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Exclusion limits on the production cross section as a function of m($\tilde{t}$) are shown for several values of $\tau(\tilde{t})$ along with the nominal signal production cross section and its theoretical uncertainty.
Exclusion limits on the production cross section as a function of m($\tilde{t}$) are shown for several values of $\tau(\tilde{t})$ along with the nominal signal production cross section and its theoretical uncertainty.
Parameterized event selection efficiencies for the $E_{T}^{miss}$ Trigger SR. The event-level efficiencies for each SR are extracted for all events passing the acceptance of the corresponding SR.
Parameterized event selection efficiencies for the $E_{T}^{miss}$ Trigger SR. The event-level efficiencies for each SR are extracted for all events passing the acceptance of the corresponding SR.
Parameterized event selection efficiencies for the Muon Trigger SR. The event-level efficiencies for each SR are extracted for all events passing the acceptance of the corresponding SR.
Parameterized event selection efficiencies for the Muon Trigger SR. The event-level efficiencies for each SR are extracted for all events passing the acceptance of the corresponding SR.
Parameterized muon-level reconstruction efficiencies as a function of the muon $p_{T}$ and $d_{0}$. The muon-level efficiencies are extracted using muons passing the muon acceptance criteria.
Parameterized muon-level reconstruction efficiencies as a function of the muon $p_{T}$ and $d_{0}$. The muon-level efficiencies are extracted using muons passing the muon acceptance criteria.
Parameterized vertex-level reconstruction efficiencies as a function of the radial position of the truth vertex. The efficiency is calculated independent of the muons originating from this truth vertex.
Parameterized vertex-level reconstruction efficiencies as a function of the radial position of the truth vertex. The efficiency is calculated independent of the muons originating from this truth vertex.
Parameterized vertex-level reconstruction efficiencies as a function of the radial position of the truth vertex. The efficiency is calculated only for truth vertices which have a muon originating from them which is matched to a reconstructed muon.
Parameterized vertex-level reconstruction efficiencies as a function of the radial position of the truth vertex. The efficiency is calculated only for truth vertices which have a muon originating from them which is matched to a reconstructed muon.
The $p_{T}$ distribution of all muons originating from LLP decays in the samples used to calculate and validate the efficiencies.
The $p_{T}$ distribution of all muons originating from LLP decays in the samples used to calculate and validate the efficiencies.
The invariant mass and multiplicity of selected decay products of all truth vertices used in the calculation and validation of the reconstructed efficiencies.
The invariant mass and multiplicity of selected decay products of all truth vertices used in the calculation and validation of the reconstructed efficiencies.
Azimuthal anisotropies of muons from charm and bottom hadron decays are measured in Pb+Pb collisions at $\sqrt{s_\mathrm{NN}}= 5.02$ TeV. The data were collected with the ATLAS detector at the Large Hadron Collider in 2015 and 2018 with integrated luminosities of $0.5~\mathrm{nb}^{-1}$ and $1.4~\mathrm{nb^{-1}}$, respectively. The kinematic selection for heavy-flavor muons requires transverse momentum $4 < p_\mathrm{T} < 30$ GeV and pseudorapidity $|\eta|<2.0$. The dominant sources of muons in this $p_\mathrm{T}$ range are semi-leptonic decays of charm and bottom hadrons. These heavy-flavor muons are separated from light-hadron decay muons and punch-through hadrons using the momentum imbalance between the measurements in the tracking detector and in the muon spectrometers. Azimuthal anisotropies, quantified by flow coefficients, are measured via the event-plane method for inclusive heavy-flavor muons as a function of the muon $p_\mathrm{T}$ and in intervals of Pb+Pb collision centrality. Heavy-flavor muons are separated into contributions from charm and bottom hadron decays using the muon transverse impact parameter with respect to the event primary vertex. Non-zero elliptic ($v_{2}$) and triangular ($v_{3}$) flow coefficients are extracted for charm and bottom muons, with the charm muon coefficients larger than those for bottom muons for all Pb+Pb collision centralities. The results indicate substantial modification to the charm and bottom quark angular distributions through interactions in the quark-gluon plasma produced in these Pb+Pb collisions, with smaller modifications for the bottom quarks as expected theoretically due to their larger mass.
Summary of results for Inclusive HF muon v2 as a function of pT for different centrality. Uncertainties are statistical and systematic, respectively.
Summary of results for Inclusive HF muon v3 as a function of pT for different centrality. Uncertainties are statistical and systematic, respectively.
Summary of results for charm muon v2 as a function of pT for different centrality. Uncertainties are statistical and systematic, respectively.
Summary of results for bottom muon v2 as a function of pT for different centrality. Uncertainties are statistical and systematic, respectively.
Summary of results for charm muon v3 as a function of pT for different centrality. Uncertainties are statistical and systematic, respectively.
Summary of results for bottom muon v3 as a function of pT for different centrality. Uncertainties are statistical and systematic, respectively.
A search for dijet resonances in events with at least one isolated charged lepton is performed using $139~{\text{fb}}^{-1}$ of $\sqrt{s}=13$ TeV proton-proton collision data recorded by the ATLAS detector at the LHC. The dijet invariant-mass ($m_{jj}$) distribution constructed from events with at least one isolated electron or muon is searched in the region $0.22 < m_{jj} < 6.3$ TeV for excesses above a smoothly falling background from Standard Model processes. Triggering based on the presence of a lepton in the event reduces limitations imposed by minimum transverse momentum thresholds for triggering on jets. This approach allows smaller dijet invariant masses to be probed than in inclusive dijet searches, targeting a variety of new-physics models, for example ones in which a new state is produced in association with a leptonically decaying $W$ or $Z$ boson. No statistically significant deviation from the Standard Model background hypothesis is found. Limits on contributions from generic Gaussian signals with widths ranging from that determined by the detector resolution up to 15% of the resonance mass are obtained for dijet invariant masses ranging from 0.25 TeV to 6 TeV. Limits are set also in the context of several scenarios beyond the Standard Model, such as the Sequential Standard Model, a technicolor model, a charged Higgs boson model and a simplified Dark Matter model.
Observed and expected 95% credibility-level upper limits on the cross-section times acceptance times branching ratio for the techicolor model with production of $\rho_T$ decaying to $\pi_T W^{\pm}$. The table also shows the corresponding $1\sigma$ and $2\sigma$ bands for the expected limits. The limits are calculated using jets in events with at least one isolated lepton ($e$ or $\mu$) with $p_\text{T}^\ell \ge 60$ GeV.
Observed and expected 95% credibility-level upper limits on the cross-section times acceptance times branching ratio for $W' \to Z' W^{\pm}$ production in the Sequential Standard Model. The table also shows the corresponding $1\sigma$ and $2\sigma$ bands for the expected limits. The limits are calculated using jets in events with at least one isolated lepton ($e$ or $\mu$) with $p_\text{T}^\ell \ge 60$ GeV.
Observed and expected 95% credibility-level upper limits on the cross-section times branching ratio for the $tbH^+$ model. The table also shows the corresponding $1\sigma$ and $2\sigma$ bands for the expected limits. The limits are calculated using jets in events with at least one isolated lepton ($e$ or $\mu$) with $p_\text{T}^\ell \ge 60$ GeV.
Observed and expected 95% credibility-level upper limits on the cross-section times branching ratio for the simplified dark-matter model. The table also shows the corresponding $1\sigma$ and $2\sigma$ bands for the expected limits. The limits are calculated using jets in events with at least one isolated lepton ($e$ or $\mu$) with $p_\text{T}^\ell \ge 60$ GeV.
The 95% CL upper limits on the cross-section times acceptance times efficiency times branching ratio, as a function of the resonance mass, $m_X$. The limits are calculated using jets in events with at least one isolated lepton ($e$ or $\mu$) with $p_\text{T}^\ell \ge 60$ GeV. The limits are shown for a generic Gaussian signal with the width $\sigma_{X}/m_{X} =0$. The table also shows the expected limits and the corresponding $1\sigma$ and $2\sigma$ bands. The tabulated data has been used in Figure 04 of the publication.
The 95% CL upper limits on the cross-section times acceptance times efficiency times branching ratio, as a function of the resonance mass, $m_X$. The limits are calculated using jets in events with at least one isolated lepton ($e$ or $\mu$) with $p_\text{T}^\ell \ge 60$ GeV. The limits are shown for a generic Gaussian signal with the width $\sigma_{X}/m_{X} =0.05$. The table also shows the expected limits and the corresponding $1\sigma$ and $2\sigma$ bands. The tabulated data has been used in Figure 04 of the publication.
The 95% CL upper limits on the cross-section times acceptance times efficiency times branching ratio, as a function of the resonance mass, $m_X$. The limits are calculated using jets in events with at least one isolated lepton ($e$ or $\mu$) with $p_\text{T}^\ell \ge 60$ GeV. The limits are shown for a generic Gaussian signal with the width $\sigma_{X}/m_{X} =0.10$. The table also shows the expected limits and the corresponding $1\sigma$ and $2\sigma$ bands. The tabulated data has been used in Figure 04 of the publication.
The 95% CL upper limits on the cross-section times acceptance times efficiency times branching ratio, as a function of the resonance mass, $m_X$. The limits are calculated using jets in events with at least one isolated lepton ($e$ or $\mu$) with $p_\text{T}^\ell \ge 60$ GeV. The limits are shown for a generic Gaussian signal with the width $\sigma_{X}/m_{X} =0.15$. The table also shows the expected limits and the corresponding $1\sigma$ and $2\sigma$ bands. The tabulated data has been used in Figure 04 of the publication.
Truth-level cross-sections ($\sigma$), acceptances ($A$), detector efficiencies ($\epsilon$) and the detector-level visible cross-sections ($\sigma^{vis}$) for different masses of the $\rho_T$ model. Only statistical uncertainties on the acceptances and efficiencies are shown. The acceptance is defined by requiring jets with $m_{jj} >216$ GeV and $|\eta|<2.4$, as well as isolated leptons ($e$ or $\mu$) with $p_\text{T}^\ell \ge 60$ GeV and $|\eta^\mu|<2.5$ ($|\eta^e|<2.47$, excluding of the gap region 1.37--1.52) for muons (electrons). The tabulated data has been used in Figure 05a of the publication.
Truth-level cross-sections ($\sigma$), acceptances ($A$), detector efficiencies ($\epsilon$) and the detector-level visible cross-sections ($\sigma^{vis}$) for different masses of the $W'/Z'$ SSM model. Only statistical uncertainties on the acceptances and efficiencies are shown. The acceptance is defined by requiring jets with $m_{jj} >216$ GeV and $|\eta|<2.4$, as well as leptons with $p_\text{T}^\ell \ge 60$ GeV and $|\eta^\mu|<2.5$ ($|\eta^e|<2.47$ with exclusion of the gap region 1.37-1.52) for muons (electrons). The tabulated data has been used in Figure 05b of the publication.
Truth-level cross-sections ($\sigma$), acceptances ($A$), detector efficiencies ($\epsilon$) and the detector-level visible cross-sections ($\sigma^{vis}$) for different masses of the $H^+$ model for $\tan \beta=1$. Only statistical uncertainties on the acceptances and efficiencies are shown. The acceptance correction was calculated assuming $\tan \beta=1$ and the narrow-width approximation. The acceptance is defined by requiring jets with $m_{jj} >216$ GeV and $|\eta|<2.4$, as well as leptons with $p_\text{T}^\ell \ge 60$ GeV and $|\eta^\mu|<2.5$ ($|\eta^e|<2.47$ with exclusion of the gap region 1.37-1.52) for muons (electrons). The tabulated data has been used in Figure 05c of the publication.
Truth-level cross-sections ($\sigma$), acceptances ($A$), detector efficiencies ($\epsilon$) and the detector-level visible cross-sections ($\sigma^{vis}$) for different masses of the $Z'$ (DM) model. Only statistical uncertainties on the acceptances and efficiencies are shown. The acceptance is defined by requiring jets with $m_{jj} > 216$ GeV and $|\eta|<2.4$, as well as leptons with $p_\text{T}^\ell \ge 60$ GeV and $|\eta^\mu|<2.5$ ($|\eta^e|<2.47$ with exclusion of the gap region 1.37-1.52) for muons (electrons). The tabulated data has been used in Figure 05d of the publication.
A test of CP invariance in Higgs boson production via vector-boson fusion is performed in the $H\rightarrow\tau\tau$ decay channel. This test uses the Optimal Observable method and is carried out using 36.1 $\mathrm{fb}^{-1}$ of $\sqrt{s}$ = 13 TeV proton$-$proton collision data collected by the ATLAS experiment at the LHC. Contributions from CP-violating interactions between the Higgs boson and electroweak gauge bosons are described by an effective field theory, in which the parameter $\tilde{d}$ governs the strength of CP violation. No sign of CP violation is observed in the distributions of the Optimal Observable, and $\tilde{d}$ is constrained to the interval $[-0.090, 0.035]$ at the 68% confidence level (CL), compared to an expected interval of $\tilde{d} \in [-0.035,0.033]$ based upon the Standard Model prediction. No constraints can be set on $\tilde{d}$ at 95% CL, while an expected 95% CL interval of $\tilde{d} \in [-0.21,0.15]$ for the Standard Model hypothesis was expected.
Post-fit BDT distributions after the VBF event selection for the $\tau_{\mathrm{lep}}\tau_{\mathrm{lep}}$ SF analysis channel. The VBF signal is shown for $\mu = 0.73$ and $\tilde d = -0.01$. ''Other bkg'' denotes all background contributions not listed explicitly in the legend. The size of the combined statistical, experimental, and theoretical uncertainties is given. The exact value of the $p_{\mathrm{T}}$ cut on the leptons depends on the trigger.
Post-fit BDT distributions after the VBF event selection for the $\tau_{\mathrm{lep}}\tau_{\mathrm{lep}}$ DF analysis channel. The VBF signal is shown for $\mu = 0.73$ and $\tilde d = -0.01$. ''Other bkg'' denotes all background contributions not listed explicitly in the legend. The size of the combined statistical, experimental, and theoretical uncertainties is given.
Post-fit BDT distributions after the VBF event selection for the $\tau_{\mathrm{lep}}\tau_{\mathrm{had}}$ analysis channel. The VBF signal is shown for $\mu = 0.73$ and $\tilde d = -0.01$. ''Other bkg'' denotes all background contributions not listed explicitly in the legend. The size of the combined statistical, experimental, and theoretical uncertainties is given. The exact value of the $p_{\mathrm{T}}$ cut on the leading lepton depends on the trigger.
Post-fit BDT distributions after the VBF event selection for the $\tau_{\mathrm{had}}\tau_{\mathrm{had}}$ analysis channel. The VBF signal is shown for $\mu = 0.73$ and $\tilde d = -0.01$. ''Other bkg'' denotes all background contributions not listed explicitly in the legend. The size of the combined statistical, experimental, and theoretical uncertainties is given.
Post-fit $m_{\tau\tau}^{\mathrm{MMC}}$ distributions in the low BDT score CR for the $\tau_{\mathrm{lep}}\tau_{\mathrm{lep}}$ SF analysis channel. ''Other bkg'' denotes all background contributions not listed explicitly in the legend. The size of the combined statistical, experimental, and theoretical uncertainties is given. The exact value of the $p_{\mathrm{T}}$ cut on the leptons depends on the trigger.
Post-fit $m_{\tau\tau}^{\mathrm{MMC}}$ distributions in the low BDT score CR for the $\tau_{\mathrm{lep}}\tau_{\mathrm{lep}}$ DF analysis channel. ''Other bkg'' denotes all background contributions not listed explicitly in the legend. The size of the combined statistical, experimental, and theoretical uncertainties is given.
Post-fit $m_{\tau\tau}^{\mathrm{MMC}}$ distributions in the low BDT score CR for the $\tau_{\mathrm{lep}}\tau_{\mathrm{had}}$ analysis channel. ''Other bkg'' denotes all background contributions not listed explicitly in the legend. The size of the combined statistical, experimental, and theoretical uncertainties is given. The exact value of the $p_{\mathrm{T}}$ cut on the leading lepton depends on the trigger.
Post-fit $m_{\tau\tau}^{\mathrm{MMC}}$ distributions in the low BDT score CR for the $\tau_{\mathrm{had}}\tau_{\mathrm{had}}$ analysis channel. ''Other bkg'' denotes all background contributions not listed explicitly in the legend. The size of the combined statistical, experimental, and theoretical uncertainties is given.
Post-fit Optimal Observable distributions in the low BDT score CR for the $\tau_{\mathrm{lep}}\tau_{\mathrm{lep}}$ SF analysis channel. ''Other bkg'' denotes all background contributions not listed explicitly in the legend. The size of the combined statistical, experimental, and theoretical uncertainties is given. The exact value of the $p_{\mathrm{T}}$ cut on the leptons depends on the trigger.
Post-fit Optimal Observable distributions in the low BDT score CR for the $\tau_{\mathrm{lep}}\tau_{\mathrm{lep}}$ DF analysis channel. ''Other bkg'' denotes all background contributions not listed explicitly in the legend. The size of the combined statistical, experimental, and theoretical uncertainties is given.
Post-fit Optimal Observable distributions in the low BDT score CR for the $\tau_{\mathrm{lep}}\tau_{\mathrm{had}}$ analysis channel. ''Other bkg'' denotes all background contributions not listed explicitly in the legend. The size of the combined statistical, experimental, and theoretical uncertainties is given. The exact value of the $p_{\mathrm{T}}$ cut on the leading lepton depends on the trigger.
Post-fit Optimal Observable distributions in the low BDT score CR for the $\tau_{\mathrm{had}}\tau_{\mathrm{had}}$ analysis channel. ''Other bkg'' denotes all background contributions not listed explicitly in the legend. The size of the combined statistical, experimental, and theoretical uncertainties is given.
Post-fit distributions of the event yields as a function of the Optimal Observable in the SR for the $\tau_{\mathrm{lep}}\tau_{\mathrm{lep}}$ SF analysis channel. The values of $\tilde d$, the signal strength $\mu$, the normalization of background processes, and nuisance parameters for the event yield prediction are set to those which minimize the NLL. The size of the combined statistical, experimental and theoretical uncertainties is given.
Post-fit distributions of the event yields as a function of the Optimal Observable in the SR for the $\tau_{\mathrm{lep}}\tau_{\mathrm{lep}}$ DF analysis channel. The values of $\tilde d$, the signal strength $\mu$, the normalization of background processes, and nuisance parameters for the event yield prediction are set to those which minimize the NLL. The size of the combined statistical, experimental and theoretical uncertainties is given.
Post-fit distributions of the event yields as a function of the Optimal Observable in the SR for the $\tau_{\mathrm{lep}}\tau_{\mathrm{had}}$ analysis channel. The values of $\tilde d$, the signal strength $\mu$, the normalization of background processes, and nuisance parameters for the event yield prediction are set to those which minimize the NLL. The size of the combined statistical, experimental and theoretical uncertainties is given. The exact value of the $p_{\mathrm{T}}$ cut on the leading lepton depends on the trigger.
Post-fit distributions of the event yields as a function of the Optimal Observable in the SR for the $\tau_{\mathrm{had}}\tau_{\mathrm{had}}$ analysis channel. The values of $\tilde d$, the signal strength $\mu$, the normalization of background processes, and nuisance parameters for the event yield prediction are set to those which minimize the NLL. The size of the combined statistical, experimental and theoretical uncertainties is given.
The observed $\Delta\mathrm{NLL}$ curve as a function of $\tilde d$ values. For comparison, expected $\Delta\mathrm{NLL}$ curves are also shown. The constraints on the nuisance parameters and normalization factors are first determined in a CR-only fit, and then a fit to pseudo-data corresponding to these nuisance parameters, normalization factors, and to $\tilde d=0, \mu = 1$ or $\tilde d =0, \mu = 0.73$ is performed to obtain these $\Delta\mathrm{NLL}$ curves. Moreover, a pre-fit expected $\Delta\mathrm{NLL}$ is shown, using pseudo-data corresponding to $\tilde d =0$ and $\mu = 1$ in the signal and control regions.
The expected $\Delta\mathrm{NLL}$ curves comparing the sensitivity of the fit with and without systematic uncertainties. For comparison, other curves are shown which remove the effect of jet-based systematic uncertainties, $\tau$-based systematic uncertainties, and MC statistical uncertainties.
The observed $\Delta\mathrm{NLL}$ curves for each analysis channel as a function of $\tilde d$, compared to the combined result. For the individual analysis channel $\Delta\mathrm{NLL}$ curves, only event yield information in the other SRs is used, ensuring that the Optimal Observable distributions in the other SRs do not influence the preferred value of $\tilde d$. The signal strength is constrained to be positive in these individual channel $\Delta\mathrm{NLL}$ curves. The exact value of the $p_{\mathrm{T}}$ cut on the leading lepton depends on the trigger.
Post-fit BDT distributions in the top-quark CR for the $\tau_{\mathrm{lep}}\tau_{\mathrm{lep}}$ SF channel. The size of the combined statistical, experimental, and theoretical uncertainties is given. The exact value of the $p_{\mathrm{T}}$ cut on the leptons depends on the trigger.
Post-fit BDT distributions in the top-quark CR for the $\tau_{\mathrm{lep}}\tau_{\mathrm{lep}}$ DF channel. The size of the combined statistical, experimental, and theoretical uncertainties is given.
Post-fit BDT distributions in the $Z\to \ell\ell$ CR for the $\tau_{\mathrm{lep}}\tau_{\mathrm{lep}}$ SF analysis channel. The size of the combined statistical, experimental, and theoretical uncertainties is given. The exact value of the $p_{\mathrm{T}}$ cut on the leptons depends on the trigger.
Post-fit Optimal Observable distributions in the top-quark CR for the $\tau_{\mathrm{lep}}\tau_{\mathrm{lep}}$ SF channel. The size of the combined statistical, experimental, and theoretical uncertainties is given. The exact value of the $p_{\mathrm{T}}$ cut on the leptons depends on the trigger.
Post-fit Optimal Observable distributions in the top-quark CR for the $\tau_{\mathrm{lep}}\tau_{\mathrm{lep}}$ DF channel. The size of the combined statistical, experimental, and theoretical uncertainties is given.
Post-fit Optimal Observable distributions in the $Z\to \ell\ell$ CR for the $\tau_{\mathrm{lep}}\tau_{\mathrm{lep}}$ SF analysis channel. The size of the combined statistical, experimental, and theoretical uncertainties is given. The exact value of the $p_{\mathrm{T}}$ cut on the leptons depends on the trigger.
Post-fit distribution of weighted event yields as a function of the Optimal Observable for all four SRs combined. The contributions of the different SRs are weighted by a factor of ln(1 + S/B), where S and B are the post-fit expected numbers of signal and background events in that region, respectively. The size of the combined statistical, experimental, and theoretical uncertainties is given.
A measurement of the $B^0_s \to J/\psi\phi$ decay parameters using 80.5 $\mathrm{fb}^{-1}$ of integrated luminosity collected with the ATLAS detector from 13 TeV proton-proton collisions at the LHC is presented. The measured parameters include the $CP$-violating phase $\phi_s$, the width difference $\Delta\Gamma_{s}$ between the $B^0_s$ meson mass eigenstates and the average decay width $\Gamma_{s}$. The values measured for the physical parameters are combined with those from 19.2 $\mathrm{fb}^{-1}$ of 7 TeV and 8 TeV data, leading to the following: \begin{eqnarray*} \phi_s & = & -0.087\phantom{0} \pm 0.036\phantom{0} ~\mathrm{(stat.)} \pm 0.021\phantom{0} ~\mathrm{(syst.)~rad} \\ \Delta\Gamma_{s} & = & \phantom{-}0.0657 \pm 0.0043 ~\mathrm{(stat.)} \pm 0.0037 ~\mathrm{(syst.)~ps}^{-1} \\ \Gamma_{s} & = & \phantom{-}0.6703 \pm 0.0014 ~\mathrm{(stat.)} \pm 0.0018 ~\mathrm{(syst.)~ps}^{-1} \\ \end{eqnarray*} Results for $\phi_s$ and $\Delta\Gamma_{s}$ are also presented as 68% confidence level contours in the $\phi_s$-$\Delta\Gamma_{s}$ plane. Furthermore, the transversity amplitudes and corresponding strong phases are measured. $\phi_s$ and $\Delta\Gamma_{s}$ measurements are in agreement with the Standard Model predictions.
Fitted values for the physical parameters of interest with their statistical and systematic uncertainties, for the result of solution (a).
Fitted values for the physical parameters of interest with their statistical and systematic uncertainties, for the result of solution (b).
Fit correlations between the physical parameters of interest, obtained from the fit for solution (a).
Fit correlations between the physical parameters of interest, obtained from the fit for solution (b).
Values of the physical parameters extracted in the combination of solution (a) of 13 TeV results with those obtained from 7 TeV and 8 TeV data.
Values of the physical parameters extracted in the combination of solution (b) of 13 TeV results with those obtained from 7 TeV and 8 TeV data.
Correlation matrix of the BLUE combination of the 7 TeV and 8 TeV results and the solution (a) of the 13 TeV result.
Correlation matrix of the BLUE combination of the 7 TeV and 8 TeV results and the solution (b) of the 13 TeV result.
Summary of systematic uncertainties assigned to the physical parameters of interest.
A search for Higgs boson pair production via vector-boson fusion (VBF) in the $b\bar{b}b\bar{b}$ final state is carried out with the ATLAS experiment using 126 fb$^{-1}$ of proton-proton collision data delivered at $\sqrt{s} = 13$ TeV by the Large Hadron Collider. This search is sensitive to VBF production of additional heavy bosons that may decay into Higgs boson pairs, and in a non-resonant topology it can constrain the quartic coupling between the Higgs bosons and vector bosons. No significant excess relative to the Standard Model expectation is observed, and limits on the production cross-section are set at the 95 % confidence level for a heavy scalar resonance in the context of an extended Higgs sector, and for non-resonant Higgs boson pair production. Interpretation in terms of the coupling between a Higgs boson pair and two vector bosons is also provided: coupling values normalised to the Standard Model expectation of $\kappa_{2V} < -0.43$ and $\kappa_{2V} > 2.56$ are excluded at the 95 % confidence level in data.
Acceptance x efficiency versus $\kappa_{2V}$ for non-resonant signal of $HH$.
Acceptance x efficiency versus $\kappa_{2V}$ for non-resonant signal of $HH$.
Acceptance x efficiency versus $\kappa_{2V}$ for non-resonant signal of $HH$.
Acceptance x efficiency versus $\kappa_{2V}$ for non-resonant signal of $HH$.
Acceptance x efficiency versus resonance mass for both narrow and broad resonance $X$ to $HH$.
Acceptance x efficiency versus resonance mass for both narrow and broad resonance $X$ to $HH$.
Acceptance x efficiency versus resonance mass for both narrow and broad resonance $X$ to $HH$.
Acceptance x efficiency versus resonance mass for both narrow and broad resonance $X$ to $HH$.
Post-fit mass distribution of the $HH$ candidates in the signal region. The expected background is shown after the profile-likelihood fit to data with the background-only hypothesis; the narrow-width resonant signal at 800 GeV and the non-resonant signal at $\kappa_{2V}$ = 3 are overlaid, both normalised to the corresponding observed upper limits on the cross-section.
Post-fit mass distribution of the $HH$ candidates in the signal region. The expected background is shown after the profile-likelihood fit to data with the background-only hypothesis; the narrow-width resonant signal at 800 GeV and the non-resonant signal at $\kappa_{2V}$ = 3 are overlaid, both normalised to the corresponding observed upper limits on the cross-section.
Post-fit mass distribution of the $HH$ candidates in the signal region. The expected background is shown after the profile-likelihood fit to data with the background-only hypothesis; the narrow-width resonant signal at 800 GeV and the non-resonant signal at $\kappa_{2V}$ = 3 are overlaid, both normalised to the corresponding observed upper limits on the cross-section.
Post-fit mass distribution of the $HH$ candidates in the signal region. The expected background is shown after the profile-likelihood fit to data with the background-only hypothesis; the narrow-width resonant signal at 800 GeV and the non-resonant signal at $\kappa_{2V}$ = 3 are overlaid, both normalised to the corresponding observed upper limits on the cross-section.
Observed and expected limits at 95% CL on the cross-sections of narrow resonance $X$ to $HH$ as a function of the mass $m_{X}$.
Observed and expected limits at 95% CL on the cross-sections of narrow resonance $X$ to $HH$ as a function of the mass $m_{X}$.
Observed and expected limits at 95% CL on the cross-sections of narrow resonance $X$ to $HH$ as a function of the mass $m_{X}$.
Observed and expected limits at 95% CL on the cross-section of narrow resonance $X$ to $HH$ as a function of the mass $m_{X}$.
Observed and expected limits at 95% CL on the cross-sections of broad resonance $X$ to $HH$ as a function of the mass $m_{X}$.
Observed and expected limits at 95% CL on the cross-sections of broad resonance $X$ to $HH$ as a function of the mass $m_{X}$.
Observed and expected limits at 95% CL on the cross-sections of broad resonance $X$ to $HH$ as a function of the mass $m_{X}$.
Observed and expected limits at 95% CL on the cross-section of broad resonance $X$ to $HH$ as a function of the mass $m_{X}$.
Observed and expected limits at 95% CL on the cross-sections of non-resonant $HH$ production via VBF as a function of the di-vector-boson-di-Higgs-boson coupling modifier $\kappa_{2V}$. The theory prediction of the cross-section as a function of $\kappa_{2V}$ is also shown. The minimum theory cross-section is 1.37 fb at $\kappa_{2V}=1.17$.
Observed and expected limits at 95% CL on the cross-sections of non-resonant $HH$ production via VBF as a function of the di-vector-boson-di-Higgs-boson coupling modifier $\kappa_{2V}$. The theory prediction of the cross-section as a function of $\kappa_{2V}$ is also shown. The minimum theory cross-section is 1.37 fb at $\kappa_{2V}=1.17$.
Observed and expected limits at 95% CL on the cross-sections of non-resonant $HH$ production via VBF as a function of the di-vector-boson-di-Higgs-boson coupling modifier $\kappa_{2V}$. The theory prediction of the cross-section as a function of $\kappa_{2V}$ is also shown. The minimum theory cross-section is 1.37 fb at $\kappa_{2V}=1.17$.
Observed and expected limits at 95% CL on the cross-sections of non-resonant $HH$ production via VBF as a function of the di-vector-boson-di-Higgs-boson coupling modifier $\kappa_{2V}$. The theory prediction of the cross-section as a function of $\kappa_{2V}$ is also shown. The minimum theory cross-section is 1.37 fb at $\kappa_{2V}=1.17$.
The dynamics of isolated-photon plus two-jet production in $pp$ collisions at a centre-of-mass energy of 13 TeV are studied with the ATLAS detector at the LHC using a dataset corresponding to an integrated luminosity of 36.1 fb$^{-1}$. Cross sections are measured as functions of a variety of observables, including angular correlations and invariant masses of the objects in the final state, $\gamma+jet+jet$. Measurements are also performed in phase-space regions enriched in each of the two underlying physical mechanisms, namely direct and fragmentation processes. The measurements cover the range of photon (jet) transverse momenta from 150 GeV (100 GeV) to 2 TeV. The tree-level plus parton-shower predictions from SHERPA and PYTHIA as well as the next-to-leading-order QCD predictions from SHERPA are compared with the measurements. The next-to-leading-order QCD predictions describe the data adequately in shape and normalisation except for regions of phase space such as those with high values of the invariant mass or rapidity separation of the two jets, where the predictions overestimate the data.
Measured cross sections for isolated-photon plus two-jet production as functions of $E_{\mathrm{T}}^{\gamma}$ for the total phase-space. The predictions from Sherpa NLO are also included.
Measured cross sections for isolated-photon plus two-jet production as functions of $p_{\mathrm{T}}^{\textrm{jet}}$ for the total phase-space. The predictions from Sherpa NLO are also included.
Measured cross sections for isolated-photon plus two-jet production as functions of $|y^{\textrm{jet}}|$ for the total phase-space. The predictions from Sherpa NLO are also included.
Measured cross sections for isolated-photon plus two-jet production as functions of $\Delta y^{\gamma-\textrm{jet}}$ for the total phase-space. The predictions from Sherpa NLO are also included.
Measured cross sections for isolated-photon plus two-jet production as functions of $\Delta \phi^{\gamma-\textrm{jet}}$ for the total phase-space. The predictions from Sherpa NLO are also included.
Measured cross sections for isolated-photon plus two-jet production as functions of $\Delta y^{\textrm{jet}-\textrm{jet}}$ for the total phase-space. The predictions from Sherpa NLO are also included.
Measured cross sections for isolated-photon plus two-jet production as functions of $\Delta \phi^{\textrm{jet}-\textrm{jet}}$ for the total phase-space. The predictions from Sherpa NLO are also included.
Measured cross sections for isolated-photon plus two-jet production as functions of $m^{\textrm{jet}-\textrm{jet}}$ for the total phase-space. The predictions from Sherpa NLO are also included.
Measured cross sections for isolated-photon plus two-jet production as functions of $m^{\gamma-\textrm{jet}-\textrm{jet}}$ for the total phase-space. The predictions from Sherpa NLO are also included.
Measured cross sections for isolated-photon plus two-jet production as functions of $E_{\mathrm{T}}^{\gamma}$ for the fragmentation-enriched phase-space. The predictions from Sherpa NLO are also included.
Measured cross sections for isolated-photon plus two-jet production as functions of $p_{\mathrm{T}}^{\textrm{jet}}$ for the fragmentation-enriched phase-space. The predictions from Sherpa NLO are also included.
Measured cross sections for isolated-photon plus two-jet production as functions of $|y^{\textrm{jet}}|$ for the fragmentation-enriched phase-space. The predictions from Sherpa NLO are also included.
Measured cross sections for isolated-photon plus two-jet production as functions of $\Delta y^{\gamma-\textrm{jet}}$ for the fragmentation-enriched phase-space. The predictions from Sherpa NLO are also included.
Measured cross sections for isolated-photon plus two-jet production as functions of $\Delta \phi^{\gamma-\textrm{jet}}$ for the fragmentation-enriched phase-space. The predictions from Sherpa NLO are also included.
Measured cross sections for isolated-photon plus two-jet production as functions of $\Delta y^{\textrm{jet}-\textrm{jet}}$ for the fragmentation-enriched phase-space. The predictions from Sherpa NLO are also included.
Measured cross sections for isolated-photon plus two-jet production as functions of $\Delta \phi^{\textrm{jet}-\textrm{jet}}$ for the fragmentation-enriched phase-space. The predictions from Sherpa NLO are also included.
Measured cross sections for isolated-photon plus two-jet production as functions of $m^{\textrm{jet}-\textrm{jet}}$ for the fragmentation-enriched phase-space. The predictions from Sherpa NLO are also included.
Measured cross sections for isolated-photon plus two-jet production as functions of $m^{\gamma-\textrm{jet}-\textrm{jet}}$ for the fragmentation-enriched phase-space. The predictions from Sherpa NLO are also included.
Measured cross sections for isolated-photon plus two-jet production as functions of $E_{\mathrm{T}}^{\gamma}$ for the direct-enriched phase-space. The predictions from Sherpa NLO are also included.
Measured cross sections for isolated-photon plus two-jet production as functions of $p_{\mathrm{T}}^{\textrm{jet}}$ for the direct-enriched phase-space. The predictions from Sherpa NLO are also included.
Measured cross sections for isolated-photon plus two-jet production as functions of $|y^{\textrm{jet}}|$ for the direct-enriched phase-space. The predictions from Sherpa NLO are also included.
Measured cross sections for isolated-photon plus two-jet production as functions of $\Delta y^{\gamma-\textrm{jet}}$ for the direct-enriched phase-space. The predictions from Sherpa NLO are also included.
Measured cross sections for isolated-photon plus two-jet production as functions of $\Delta \phi^{\gamma-\textrm{jet}}$ for the direct-enriched phase-space. The predictions from Sherpa NLO are also included.
Measured cross sections for isolated-photon plus two-jet production as functions of $\Delta y^{\textrm{jet}-\textrm{jet}}$ for the direct-enriched phase-space. The predictions from Sherpa NLO are also included.
Measured cross sections for isolated-photon plus two-jet production as functions of $\Delta \phi^{\textrm{jet}-\textrm{jet}}$ for the direct-enriched phase-space. The predictions from Sherpa NLO are also included.
Measured cross sections for isolated-photon plus two-jet production as functions of $m^{\textrm{jet}-\textrm{jet}}$ for the direct-enriched phase-space. The predictions from Sherpa NLO are also included.
Measured cross sections for isolated-photon plus two-jet production as functions of $m^{\gamma-\textrm{jet}-\textrm{jet}}$ for the direct-enriched phase-space. The predictions from Sherpa NLO are also included.
Jet substructure quantities are measured using jets groomed with the soft-drop grooming procedure in dijet events from 32.9 fb$^{-1}$ of $pp$ collisions collected with the ATLAS detector at $\sqrt{s} = 13$ TeV. These observables are sensitive to a wide range of QCD phenomena. Some observables, such as the jet mass and opening angle between the two subjets which pass the soft-drop condition, can be described by a high-order (resummed) series in the strong coupling constant $\alpha_S$. Other observables, such as the momentum sharing between the two subjets, are nearly independent of $\alpha_S$. These observables can be constructed using all interacting particles or using only charged particles reconstructed in the inner tracking detectors. Track-based versions of these observables are not collinear safe, but are measured more precisely, and universal non-perturbative functions can absorb the collinear singularities. The unfolded data are directly compared with QCD calculations and hadron-level Monte Carlo simulations. The measurements are performed in different pseudorapidity regions, which are then used to extract quark and gluon jet shapes using the predicted quark and gluon fractions in each region. All of the parton shower and analytical calculations provide an excellent description of the data in most regions of phase space.
Data from Fig 6a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 6a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 6b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 6b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 6c. The unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 6c. The unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 6d. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 6d. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 6e. The unfolded $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 6e. The unfolded $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 6f. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 6f. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 7a. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 7a. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 7b. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 7b. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 7c. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 7c. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 7d. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 7d. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 7e. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 7e. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 7f. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 7f. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 8a. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 8a. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 8b. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 8b. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 8c. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 8c. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 8d. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 8d. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 8e. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 8e. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 8f. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 8f. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 14a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 14b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 14b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 4b. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 4b. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 21b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 21b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 5a. The unfolded $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 5a. The unfolded $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 5b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 5b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 14c. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14c. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14d. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14d. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4c. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4c. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4d. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4d. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5c. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5c. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5d. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5d. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14e. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14e. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14f. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14f. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4e. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4e. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4f. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4f. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5e. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5e. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5f. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5f. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 14a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 14b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 14b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 4a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 4a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 4b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 4b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 5a. The unfolded $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 5a. The unfolded $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 5b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 5b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 14c. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14c. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14d. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14d. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4c. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4c. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4d. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4d. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5c. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5c. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5d. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5d. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14e. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14e. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14f. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14f. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4e. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4e. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4f. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4f. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5e. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5e. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5f. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5f. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 36-40a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 36-40a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 81-85a. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 81-85a. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 36-40b. The unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 36-40b. The unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 81-85b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 81-85b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 36-40c. The unfolded $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 36-40c. The unfolded $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 81-85c. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 81-85c. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 51-55a. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 51-55a. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 101-105a. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 101-105a. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 51-55b. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 51-55b. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 101-105b. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 101-105b. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 51-55c. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 51-55c. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 101-105c. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 101-105c. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 66-70a. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 66-70a. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 106-110a. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 106-110a. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 66-70b. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 66-70b. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 106-110b. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 106-110b. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 66-70c. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 66-70c. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 106-110c. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 106-110c. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 26-30a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 26-30a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 71-75a. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 71-75a. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 26-30b. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 26-30b. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 71-75b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 71-75b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 26-30c. The unfolded $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 26-30c. The unfolded $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 71-75c. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 71-75c. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 41-45a. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 41-45a. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 86-90a. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 86-90a. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 41-45b. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 41-45b. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 86-90b. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 86-90b. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 41-45c. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 41-45c. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 86-90c. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 86-90c. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 56-60a. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 56-60a. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 101-105a. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 101-105a. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 56-60b. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 56-60b. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 101-105b. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 101-105b. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 56-60c. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 56-60c. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 101-105c. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 101-105c. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 31-35a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 31-35a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 76-80a. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 76-80a. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 31-35b. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 31-35b. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 76-80b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 76-80b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 31-35c. The unfolded $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 31-35c. The unfolded $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 76-80c. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 76-80c. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 46-50a. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 46-50a. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 91-95a. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 91-95a. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 46-50b. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 46-50b. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 91-95b. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 91-95b. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 46-50c. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 46-50c. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 91-95c. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 91-95c. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 61-65a. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 61-65a. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 106-110a. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 106-110a. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 61-65b. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 61-65b. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 106-110b. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 106-110b. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 61-65c. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 61-65c. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 106-110c. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 106-110c. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 6a. The extracted quark-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 6a. The extracted quark-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 15a. Theextracted quark-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 15a. Theextracted quark-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 6b. The extracted quark-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 6b. The extracted quark-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 15b. The extracted quark-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 15b. The extracted quark-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 6c. The extracted quark-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 6c. The extracted quark-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 15c. The extracted quark-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 15c. The extracted quark-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 7a. The extracted quark-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 7a. The extracted quark-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 16a. The extracted quark-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 16a. The extracted quark-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 7b. The extracted quark-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 7b. The extracted quark-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 16b. The extracted quark-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 16b. The extracted quark-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 7c. The extracted quark-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 7c. The extracted quark-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 16c. The extracted quark-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 16c. The extracted quark-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 8a. The extracted quark-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 8a. The extracted quark-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 17a. The extracted quark-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 17a. The extracted quark-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 8b. The extracted quark-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 8b. The extracted quark-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 17b. The extracted quark-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 17b. The extracted quark-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 8c. The extracted quark-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 8c. The extracted quark-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 17c. The extracted quark-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 17c. The extracted quark-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 6a. The extracted gluon-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 6a. The extracted gluon-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 15a. Theextracted gluon-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 15a. Theextracted gluon-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 6b. The extracted gluon-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 6b. The extracted gluon-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 15b. The extracted gluon-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 15b. The extracted gluon-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 6c. The extracted gluon-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 6c. The extracted gluon-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 15c. The extracted gluon-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 15c. The extracted gluon-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 7a. The extracted gluon-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 7a. The extracted gluon-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 16a. The extracted gluon-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 16a. The extracted gluon-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 7b. The extracted gluon-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 7b. The extracted gluon-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 16b. The extracted gluon-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 16b. The extracted gluon-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 7c. The extracted gluon-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 7c. The extracted gluon-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 16c. The extracted gluon-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 16c. The extracted gluon-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 8a. The extracted gluon-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 8a. The extracted gluon-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 17a. The extracted gluon-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 17a. The extracted gluon-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 8b. The extracted gluon-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 8b. The extracted gluon-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 17b. The extracted gluon-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 17b. The extracted gluon-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 8c. The extracted gluon-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 8c. The extracted gluon-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 17c. The extracted gluon-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 17c. The extracted gluon-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 99a. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 99a. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 100a. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 100a. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 99b. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 99b. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 100b. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 100b. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 99c. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 99c. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 100c. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 100c. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 101a. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 101a. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 102a. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 102a. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 101b. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 101b. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 102b. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 102b. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 101c. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 101c. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 102c. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 102c. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 103a. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 103a. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 104a. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 104a. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 103b. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 103b. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 104b. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 104b. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 103c. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 103c. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 104c. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 104c. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 105a. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 105a. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 106a. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 106a. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 105b. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 105b. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 106b. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 106b. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 105c. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 105c. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 106c. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 106c. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 107a. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 107a. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 108a. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 108a. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 107b. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 107b. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 108b. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 108b. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 107c. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 107c. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 108c. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 108c. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 109a. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 109a. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 110a. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 110a. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 109b. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 109b. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 110b. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 110b. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 109c. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 109c. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 110c. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 110c. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 111a. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 111a. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 112a. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 112a. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 111b. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 111b. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 112b. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 112b. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 111c. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 111c. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 112c. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 112c. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 113a. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 113a. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 114a. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 114a. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 113b. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 113b. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 114b. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 114b. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 113c. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 113c. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 114c. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 114c. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 115a. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 115a. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 116a. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 116a. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 115b. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 115b. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 116b. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 116b. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 115c. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 115c. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 116c. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 116c. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 99d. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 99d. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 100d. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 100d. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 99e. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 99e. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 100e. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 100e. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 99f. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 99f. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 100f. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 100f. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 101d. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 101d. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 102d. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 102d. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 101e. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 101e. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 102e. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 102e. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 101f. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 101f. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 102f. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 102f. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 103d. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 103d. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 104d. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 104d. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 103e. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 103e. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 104e. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 104e. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 103f. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 103f. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 104f. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 104f. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 105d. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 105d. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 106d. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 106d. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 105e. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 105e. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 106e. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 106e. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 105f. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 105f. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 106f. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 106f. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 107d. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 107d. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 108d. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 108d. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 107e. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 107e. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 108e. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 108e. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 107f. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 107f. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 108f. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 108f. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 109d. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 109d. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 110d. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 110d. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 109e. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 109e. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 110e. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 110e. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 109f. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 109f. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 110f. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 110f. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 111d. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 111d. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 112d. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 112d. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 111e. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 111e. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 112e. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 112e. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 111f. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 111f. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 112f. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 112f. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 113d. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 113d. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 114d. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 114d. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 113e. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 113e. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 114e. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 114e. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 113f. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 113f. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 114f. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 114f. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 115d. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 115d. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 116d. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 116d. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 115e. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 115e. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 116e. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 116e. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 115f. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 115f. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 116f. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 116f. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
A search for supersymmetry through the pair production of electroweakinos with mass splittings near the electroweak scale and decaying via on-shell $W$ and $Z$ bosons is presented for a three-lepton final state. The analyzed proton-proton collision data taken at a center-of-mass energy of $\sqrt{s}$ = 13 TeV were collected between 2015 and 2018 by the ATLAS experiment at the Large Hadron Collider, corresponding to an integrated luminosity of 139 fb$^{-1}$. A search, emulating the recursive jigsaw reconstruction technique with easily reproducible laboratory-frame variables, is performed. The two excesses observed in the 2015-2016 data recursive jigsaw analysis in the low-mass three-lepton phase space are reproduced. Results with the full dataset are in agreement with the Standard Model expectations. They are interpreted to set exclusion limits at 95% confidence level on simplified models of chargino-neutralino pair production for masses up to 345 GeV.
Distributions in SR-low of the data and post-fit background prediction for m<sub>T</sub>. The SR-low event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-low of the data and post-fit background prediction for m<sub>T</sub>. The SR-low event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-low of the data and post-fit background prediction for H<sup>boost</sup>. The SR-low event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-low of the data and post-fit background prediction for H<sup>boost</sup>. The SR-low event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-low of the data and post-fit background prediction for m<sub>eff</sub><sup>3ℓ</sup>/H<sup>boost</sup>. The SR-low event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-low of the data and post-fit background prediction for m<sub>eff</sub><sup>3ℓ</sup>/H<sup>boost</sup>. The SR-low event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-low of the data and post-fit background prediction for p<sub>T</sub><sup>soft</sup>/(p<sub>T</sub><sup>soft</sup> + m<sub>eff</sub><sup>3ℓ</sup>). The SR-low event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-low of the data and post-fit background prediction for p<sub>T</sub><sup>soft</sup>/(p<sub>T</sub><sup>soft</sup> + m<sub>eff</sub><sup>3ℓ</sup>). The SR-low event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-ISR of the data and post-fit background prediction for m<sub>T</sub>. The SR-ISR event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-ISR of the data and post-fit background prediction for m<sub>T</sub>. The SR-ISR event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-ISR of the data and post-fit background prediction for R(E<sub>T</sub><sup>miss</sup>,jets). The SR-ISR event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-ISR of the data and post-fit background prediction for R(E<sub>T</sub><sup>miss</sup>,jets). The SR-ISR event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-ISR of the data and post-fit background prediction for p<sub>T</sub><sup>soft</sup>. The SR-ISR event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-ISR of the data and post-fit background prediction for p<sub>T</sub><sup>soft</sup>. The SR-ISR event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-ISR of the data and post-fit background prediction for p<sub>T</sub><sup>jets</sup>. The SR-ISR event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-ISR of the data and post-fit background prediction for p<sub>T</sub><sup>jets</sup>. The SR-ISR event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Observed exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Observed exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Expected exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Expected exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Plus 1$\sigma$ uncertainty, varying the signal cross section within its uncertainty, on the observed exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Plus 1$\sigma$ uncertainty, varying the signal cross section within its uncertainty, on the observed exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Minus 1$\sigma$ uncertainty, varying the signal cross section within its uncertainty, on the observed exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Minus 1$\sigma$ uncertainty, varying the signal cross section within its uncertainty, on the observed exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Plus 1$\sigma$ uncertainty, due to uncertainties in the background prediction and experimental uncertainties affecting the signal, on the expected exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Plus 1$\sigma$ uncertainty, due to uncertainties in the background prediction and experimental uncertainties affecting the signal, on the expected exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Minus 1$\sigma$ uncertainty, due to uncertainties in the background prediction and experimental uncertainties affecting the signal, on the expected exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Minus 1$\sigma$ uncertainty, due to uncertainties in the background prediction and experimental uncertainties affecting the signal, on the expected exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Upper limits on observed wino-bino simplified model signal cross section $\sigma_\text{obs}^\text{95}$.
Upper limits on observed wino-bino simplified model signal cross section $\sigma_\text{obs}^\text{95}$.
Upper limits on expected wino-bino simplified model signal cross section $\sigma_\text{exp}^\text{95}$.
Upper limits on expected wino-bino simplified model signal cross section $\sigma_\text{exp}^\text{95}$.
Signal acceptance in SR-low, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} \geq 100$ GeV.
Signal acceptance in SR-low, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} \geq 100$ GeV.
Signal efficiency in SR-low, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} \geq 100$ GeV.
Signal efficiency in SR-low, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} \geq 100$ GeV.
Signal acceptance in SR-ISR, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} \geq 100$ GeV.
Signal acceptance in SR-ISR, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} \geq 100$ GeV.
Signal efficiency in SR-ISR, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} \geq 100$ GeV.
Signal efficiency in SR-ISR, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} \geq 100$ GeV.
Signal acceptance in SR-low, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} < 100$ GeV.
Signal acceptance in SR-low, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} < 100$ GeV.
Signal efficiency in SR-low, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} < 100$ GeV.
Signal efficiency in SR-low, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} < 100$ GeV.
Signal acceptance in SR-ISR, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} < 100$ GeV.
Signal acceptance in SR-ISR, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} < 100$ GeV.
Signal efficiency in SR-ISR, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} < 100$ GeV.
Signal efficiency in SR-ISR, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} < 100$ GeV.
The observed and expected yields after the background-only fit in the SRs. The normalization factors of the $WZ$ sample for the low-mass and ISR regions are different and are treated separately in the combined fit. \The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. Combined statistical and systematic uncertainties are presented. The individual uncertainties can be correlated and do not necessarily add in quadrature to equal the total background uncertainty.
The observed and expected yields after the background-only fit in the SRs. The normalization factors of the $WZ$ sample for the low-mass and ISR regions are different and are treated separately in the combined fit. \The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. Combined statistical and systematic uncertainties are presented. The individual uncertainties can be correlated and do not necessarily add in quadrature to equal the total background uncertainty.
Summary of the expected background and data yields in $\text{SR-low}$ and $\text{SR-ISR}$. The second and third columns show the data and total expected background with systematic uncertainties. The fourth column gives the model-independent upper limits at 95\% CL on the visible cross section ($\sigma_\text{vis}$). The fifth and sixth columns give the visible number of observed ($S^{95}_\text{obs}$) and expected ($S^{95}_\text{exp}$) events of a generic beyond-the-SM process, where uncertainties on $S^{95}_\text{exp}$ reflect the $\pm 1 \sigma$ uncertainties on the background estimation. The last column shows the discovery $p$-value and Gaussian significance $Z$ assuming no signal.
Summary of the expected background and data yields in $\text{SR-low}$ and $\text{SR-ISR}$. The second and third columns show the data and total expected background with systematic uncertainties. The fourth column gives the model-independent upper limits at 95\% CL on the visible cross section ($\sigma_\text{vis}$). The fifth and sixth columns give the visible number of observed ($S^{95}_\text{obs}$) and expected ($S^{95}_\text{exp}$) events of a generic beyond-the-SM process, where uncertainties on $S^{95}_\text{exp}$ reflect the $\pm 1 \sigma$ uncertainties on the background estimation. The last column shows the discovery $p$-value and Gaussian significance $Z$ assuming no signal.
Upper limits on observed (expected) wino-bino simplified model signal cross section $\sigma_\text{obs(exp)}^\text{95}$.
Upper limits on observed (expected) wino-bino simplified model signal cross section $\sigma_\text{obs(exp)}^\text{95}$.
Full list of event selections and MC generator-weighted yields and in $\text{SR-ISR}$ for the main $WZ$ background and a representative $\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2}$ signal point of mass 200 GeV and mass splitting $\Delta m = 100$ GeV normalized to 139 fb$^{-1}$. 40000 events were generated.
Full list of event selections and MC generator-weighted yields and in $\text{SR-ISR}$ for the main $WZ$ background and a representative $\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2}$ signal point of mass 200 GeV and mass splitting $\Delta m = 100$ GeV normalized to 139 fb$^{-1}$. 40000 events were generated.
Full list of event selections and MC generator-weighted yields and in $\text{SR-low}$ for the main $WZ$ background and a representative $\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2}$ signal point of mass 200 GeV and mass splitting $\Delta m = 100$ GeV normalized to 139 fb$^{-1}$. 40000 events were generated.
Full list of event selections and MC generator-weighted yields and in $\text{SR-low}$ for the main $WZ$ background and a representative $\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2}$ signal point of mass 200 GeV and mass splitting $\Delta m = 100$ GeV normalized to 139 fb$^{-1}$. 40000 events were generated.
This paper describes precision measurements of the transverse momentum $p_\mathrm{T}^{\ell\ell}$ ($\ell=e,\mu$) and of the angular variable $\phi^{*}_{\eta}$ distributions of Drell-Yan lepton pairs in a mass range of 66-116 GeV. The analysis uses data from 36.1 fb$^{-1}$ of proton-proton collisions at a centre-of-mass energy of $\sqrt{s}=13$ TeV collected by the ATLAS experiment at the LHC in 2015 and 2016. Measurements in electron-pair and muon-pair final states are performed in the same fiducial volumes, corrected for detector effects, and combined. Compared to previous measurements in proton-proton collisions at $\sqrt{s}=$7 and 8 TeV, these new measurements probe perturbative QCD at a higher centre-of-mass energy with a different composition of initial states. They reach a precision of 0.2% for the normalized spectra at low values of $p_\mathrm{T}^{\ell\ell}$. The data are compared with different QCD predictions, where it is found that predictions based on resummation approaches can describe the full spectrum within uncertainties.
Selected signal candidate events in data for both decay channels as well as the expected background contributions including their total uncertainties.
Selected signal candidate events in data for both decay channels as well as the expected background contributions including their total uncertainties.
Selected signal candidate events in data for both decay channels as well as the expected background contributions including their total uncertainties.
Overview of the detector efficiency correction factors, $C_{Z}$ , for the electron and muon channels and their systematic uncertainty contributions.
Overview of the detector efficiency correction factors, $C_{Z}$ , for the electron and muon channels and their systematic uncertainty contributions.
Overview of the detector efficiency correction factors, $C_{Z}$ , for the electron and muon channels and their systematic uncertainty contributions.
Measured inclusive cross-section in the fiducial volume in the electron and muon decay channels at Born level and their combination as well as the theory prediction at NNLO in $\alpha_{s}$ using the CT14 PDF set.
Measured inclusive cross-section in the fiducial volume in the electron and muon decay channels at Born level and their combination as well as the theory prediction at NNLO in $\alpha_{s}$ using the CT14 PDF set.
Measured inclusive cross-section in the fiducial volume in the electron and muon decay channels at Born level and their combination as well as the theory prediction at NNLO in $\alpha_{s}$ using the CT14 PDF set.
The measured combined normalized differential cross-sections, divided by the bin-width, in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle level.
The measured combined normalized differential cross-sections, divided by the bin-width, in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle level.
The measured combined normalized differential cross-sections, divided by the bin-width, in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle level.
The measured combined normalized differential cross-sections, divided by the bin-width, in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle level.
The measured combined normalized differential cross-sections, divided by the bin-width, in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle level.
The measured combined normalized differential cross-sections, divided by the bin-width, in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle level.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid}\times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}p_{T}^{ll}$ measured on born level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid}\times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}p_{T}^{ll}$ measured on born level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid}\times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}p_{T}^{ll}$ measured on born level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid}\times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}\phi_{\eta}^{*}$ measured on born level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid}\times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}\phi_{\eta}^{*}$ measured on born level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid}\times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}\phi_{\eta}^{*}$ measured on born level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid}\times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}p_{T}^{ll}$ measured on born level for the $Z\rightarrow ee$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) and Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. for the electron momentum scale and resolution uncertainties; Elec. (Reco), Elec. (ID), Isolation, Trigger and Charge-ID denote the correlated uncertainties of the data/MC scale-factors for the electron reconstruction, identification, isolation, trigger and charge-identification efficiencies; The uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid}\times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}p_{T}^{ll}$ measured on born level for the $Z\rightarrow ee$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) and Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. for the electron momentum scale and resolution uncertainties; Elec. (Reco), Elec. (ID), Isolation, Trigger and Charge-ID denote the correlated uncertainties of the data/MC scale-factors for the electron reconstruction, identification, isolation, trigger and charge-identification efficiencies; The uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid}\times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}p_{T}^{ll}$ measured on born level for the $Z\rightarrow ee$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) and Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. for the electron momentum scale and resolution uncertainties; Elec. (Reco), Elec. (ID), Isolation, Trigger and Charge-ID denote the correlated uncertainties of the data/MC scale-factors for the electron reconstruction, identification, isolation, trigger and charge-identification efficiencies; The uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid} \times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}\phi_{\eta}^{*}$ measured on born level for the $Z\rightarrow ee$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) and Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. for the electron momentum scale and resolution uncertainties; Elec. (Reco), Elec. (ID), Isolation, Trigger and Charge-ID denote the correlated uncertainties of the data/MC scale-factors for the electron reconstruction, identification, isolation, trigger and charge-identification efficiencies; The uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid} \times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}\phi_{\eta}^{*}$ measured on born level for the $Z\rightarrow ee$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) and Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. for the electron momentum scale and resolution uncertainties; Elec. (Reco), Elec. (ID), Isolation, Trigger and Charge-ID denote the correlated uncertainties of the data/MC scale-factors for the electron reconstruction, identification, isolation, trigger and charge-identification efficiencies; The uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid} \times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}\phi_{\eta}^{*}$ measured on born level for the $Z\rightarrow ee$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) and Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. for the electron momentum scale and resolution uncertainties; Elec. (Reco), Elec. (ID), Isolation, Trigger and Charge-ID denote the correlated uncertainties of the data/MC scale-factors for the electron reconstruction, identification, isolation, trigger and charge-identification efficiencies; The uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid} \times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}p_{T}^{ll}$ measured on bare level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid} \times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}p_{T}^{ll}$ measured on bare level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid} \times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}p_{T}^{ll}$ measured on bare level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid} \times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}\phi_{\eta}^{*}$ measured on bare level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid} \times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}\phi_{\eta}^{*}$ measured on bare level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Results of the normalized differential cross-section $1/\sigma_\mathrm{fid} \times \mathrm{d}\sigma_\mathrm{fid}/\mathrm{d}\phi_{\eta}^{*}$ measured on bare level for the $Z\rightarrow\mu\mu$ decay channel. The following naming convention is used: Stat.(Data), Stat.(MC) an Eff.(Uncor.), denote the statistical uncertainties due limited data and MC as well as the uncorrelated lepton efficiency uncertainties; Scale and Res. denote the muon momentum scale and resolution uncertainties; Muon Sag. denotes the uncertainty due to the muon sagitta bias; Eff. (Cor.), Isolation, Trigger and TTVA denote the uncertainties of the data/MC scale-factors for the correlated muon reconstruction, isolation, trigger and track-to-vertex matching efficiencies; the uncertainties due to the primary vertex z-distribution and pile-up reweighting are denoted as Z-Pos and Pile-Up, while the model and background uncertainties are summarized under Model and Bkg.. The sign-information is kept to track bin-to-bin changes.
Measured combined normalized differential cross-section in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle.
Measured combined normalized differential cross-section in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle.
Measured combined normalized differential cross-section in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle.
Measured combined normalized differential cross-section in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle.
Measured combined normalized differential cross-section in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle.
Measured combined normalized differential cross-section in the fiducial volume at Born level as well as a factor $k_{dressed}$ to translate from the Born particle level to the dressed particle.
The distribution of events passing the selection requirements in the electron channel as a function of dilepton invariant mass $m_{ll}$ , the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the electron channel as a function of dilepton invariant mass $m_{ll}$ , the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the electron channel as a function of dilepton invariant mass $m_{ll}$ , the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of dilepton invariant mass $m_{ll}$, the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of dilepton invariant mass $m_{ll}$, the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of dilepton invariant mass $m_{ll}$, the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the electron channel as a function of lepton pseudorapidity $\eta$, the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the electron channel as a function of lepton pseudorapidity $\eta$, the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the electron channel as a function of lepton pseudorapidity $\eta$, the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of lepton pseudorapidity $\eta$, the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of lepton pseudorapidity $\eta$, the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of lepton pseudorapidity $\eta$, the latter with one entry for each lepton per event. The MC signal sample is simulated using Powheg+Pythia8. The predictions of the MC signal sample together with the MC background samples are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the electron channel as a function of dilepton transverse momentum. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the electron channel as a function of dilepton transverse momentum. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the electron channel as a function of dilepton transverse momentum. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of dilepton transverse momentum. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of dilepton transverse momentum. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of dilepton transverse momentum. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the electron channel as a function of $\phi_{\eta}^{*}$. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the electron channel as a function of $\phi_{\eta}^{*}$. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the electron channel as a function of $\phi_{\eta}^{*}$. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of $\phi_{\eta}^{*}$. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of $\phi_{\eta}^{*}$. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The distribution of events passing the selection requirements in the muon channel as a function of $\phi_{\eta}^{*}$. The MC signal sample is simulated using Powheg+Pythia8. The predictions are normalized to the integral of the data and the total experimental uncertainty of the predicted values is shown as a grey band in the ratio of the prediction to data.
The measured normalized cross section as a function of $p_{ll}$ for the electron and muon channels and the combined result as well as their ratio together with the total uncertainties, shown as a blue band. The pull distribution between the electron and muon channels, defined as the difference between the two channels divided by the combined uncorrelated uncertainty, is also shown. The $p_{ll}$ distribution is split into linear and logarithmic scales at 30 GeV.
The measured normalized cross section as a function of $p_{ll}$ for the electron and muon channels and the combined result as well as their ratio together with the total uncertainties, shown as a blue band. The pull distribution between the electron and muon channels, defined as the difference between the two channels divided by the combined uncorrelated uncertainty, is also shown. The $p_{ll}$ distribution is split into linear and logarithmic scales at 30 GeV.
The measured normalized cross section as a function of $p_{ll}$ for the electron and muon channels and the combined result as well as their ratio together with the total uncertainties, shown as a blue band. The pull distribution between the electron and muon channels, defined as the difference between the two channels divided by the combined uncorrelated uncertainty, is also shown. The $p_{ll}$ distribution is split into linear and logarithmic scales at 30 GeV.
The measured normalized cross section as a function of $\phi_{\eta}^{*}$ for the electron and muon channels and the combined result as well as their ratio together with the total uncertainties, shown as a blue band. The pull distribution between the electron and muon channels, defined as the difference between the two channels divided by the combined uncorrelated uncertainty, is also shown.
The measured normalized cross section as a function of $\phi_{\eta}^{*}$ for the electron and muon channels and the combined result as well as their ratio together with the total uncertainties, shown as a blue band. The pull distribution between the electron and muon channels, defined as the difference between the two channels divided by the combined uncorrelated uncertainty, is also shown.
The measured normalized cross section as a function of $\phi_{\eta}^{*}$ for the electron and muon channels and the combined result as well as their ratio together with the total uncertainties, shown as a blue band. The pull distribution between the electron and muon channels, defined as the difference between the two channels divided by the combined uncorrelated uncertainty, is also shown.
Comparison of the normalized $p_{ll}$ distributions predicted by different computations: Pythia8 with the AZ tune, Powheg+Pythia8 with the AZNLO tune, Sherpa v2.2.1 and RadISH with the Born level combined measurement. The uncertainties of the measurement are shown as vertical bars and uncertainties of the Sherpa and RadISH predictions are indicated by the coloured bands.
Comparison of the normalized $p_{ll}$ distributions predicted by different computations: Pythia8 with the AZ tune, Powheg+Pythia8 with the AZNLO tune, Sherpa v2.2.1 and RadISH with the Born level combined measurement. The uncertainties of the measurement are shown as vertical bars and uncertainties of the Sherpa and RadISH predictions are indicated by the coloured bands.
Comparison of the normalized $p_{ll}$ distributions predicted by different computations: Pythia8 with the AZ tune, Powheg+Pythia8 with the AZNLO tune, Sherpa v2.2.1 and RadISH with the Born level combined measurement. The uncertainties of the measurement are shown as vertical bars and uncertainties of the Sherpa and RadISH predictions are indicated by the coloured bands.
Comparison of the normalized $\phi_{\eta}^{*}$ distributions predicted by different computations: Pythia8 with the AZ tune, Powheg+Pythia8 with the AZNLO tune, Sherpa v2.2.1 and RadISH with the Born level combined measurement. The uncertainties of the measurement are shown as vertical bars and uncertainties of the Sherpa and RadISH predictions are indicated by the coloured bands.
Comparison of the normalized $\phi_{\eta}^{*}$ distributions predicted by different computations: Pythia8 with the AZ tune, Powheg+Pythia8 with the AZNLO tune, Sherpa v2.2.1 and RadISH with the Born level combined measurement. The uncertainties of the measurement are shown as vertical bars and uncertainties of the Sherpa and RadISH predictions are indicated by the coloured bands.
Comparison of the normalized $\phi_{\eta}^{*}$ distributions predicted by different computations: Pythia8 with the AZ tune, Powheg+Pythia8 with the AZNLO tune, Sherpa v2.2.1 and RadISH with the Born level combined measurement. The uncertainties of the measurement are shown as vertical bars and uncertainties of the Sherpa and RadISH predictions are indicated by the coloured bands.
Comparison of the normalized $p_{ll}$ distribution in the range $p_{ll}$ > 10 GeV. The Born level combined measurement is compared with predictions by Sherpa v2.2.1, fixed-order NNLOjet and NNLOjet supplied with NLO electroweak corrections. The uncertainties in the measurement are shown as vertical bars and the uncertainties in the predictions are indicated by the coloured bands.
Comparison of the normalized $p_{ll}$ distribution in the range $p_{ll}$ > 10 GeV. The Born level combined measurement is compared with predictions by Sherpa v2.2.1, fixed-order NNLOjet and NNLOjet supplied with NLO electroweak corrections. The uncertainties in the measurement are shown as vertical bars and the uncertainties in the predictions are indicated by the coloured bands.
Comparison of the normalized $p_{ll}$ distribution in the range $p_{ll}$ > 10 GeV. The Born level combined measurement is compared with predictions by Sherpa v2.2.1, fixed-order NNLOjet and NNLOjet supplied with NLO electroweak corrections. The uncertainties in the measurement are shown as vertical bars and the uncertainties in the predictions are indicated by the coloured bands.
The measured combined normalized differential cross-sections, divided by the bin-width, in the fiducial volume at dressed level.
The measured combined normalized differential cross-sections, divided by the bin-width, in the fiducial volume at dressed level.
A search is presented for pair-production of long-lived neutral particles using 33 fb$^{-1}$ of $\sqrt{s} = 13$ TeV proton-proton collision data, collected during 2016 by the ATLAS detector at the LHC. This search focuses on a topology in which one long-lived particle decays in the ATLAS inner detector and the other decays in the muon spectrometer. Special techniques are employed to reconstruct the displaced tracks and vertices in the inner detector and in the muon spectrometer. One event is observed that passes the full event selection, which is consistent with the estimated background. Limits are placed on scalar boson propagators with masses from 125 GeV to 1000 GeV decaying into pairs of long-lived hidden-sector scalars with masses from 8 GeV to 400 GeV. The limits placed on several low-mass scalars extend previous exclusion limits in the range of proper lifetimes $c \tau$ from 5 cm to 1 m.
IDVx selection efficiency as a function of the radial decay position for $m_H = 125$ GeV.
IDVx selection efficiency as a function of the radial decay position for $m_s = 50$ GeV.
Observed $CL_S$ limits on $BR$ for $m_H = 125$ GeV.
Observed $CL_S$ limits on $\sigma \times BR$ for $m_{\Phi} = 200-400$ GeV.
Observed $CL_S$ limits on $\sigma \times BR$ for $m_{\Phi} = 600-1000$ GeV.
Combined limits from this analysis (ID) and the CR and MS analyses for $m_{H} = 125$ GeV, $m_s = 15$ GeV.
Combined limits from this analysis (ID) and the CR and MS analyses for $m_{H} = 125$ GeV, $m_s = 25$ GeV.
Combined limits from this analysis (ID) and the CR and MS analyses for $m_{H} = 125$ GeV, $m_s = 40$ GeV.
Combined limits from this analysis (ID) and the CR and MS analyses for $m_{H} = 125$ GeV, $m_s = 55$ GeV.
Combined limits from this analysis (ID) and the CR and MS analyses for $m_{\Phi} = 200$ GeV, $m_s = 25$ GeV.
Combined limits from this analysis (ID) and the CR and MS analyses for $m_{\Phi} = 200$ GeV, $m_s = 50$ GeV.
Comparison of the IDVx reconstruction and selection efficiency for a Higgs with a mass of 125 GeV decaying to an LLP with a mass of 8 GeV, using only standard tracking versus using standard and large radius tracking for all ID vertices in the signal MC sample.
Comparison of the IDVx reconstruction and selection efficiency for a Higgs with a mass of 125 GeV decaying to an LLP with a mass of 8 GeV, using only standard tracking versus using standard and large radius tracking for ID vertices passing the full IDVx selection criteria.
Comparison of the IDVx reconstruction and selection efficiency for a $\Phi$ with a mass of 1000 GeV decaying to an LLP with a mass of 150 GeV, using only standard tracking versus using standard and large radius tracking for all ID vertices in the signal MC sample.
Comparison of the IDVx reconstruction and selection efficiency for a $\Phi$ with a mass of 1000 GeV decaying to an LLP with a mass of 150 GeV, using only standard tracking versus using standard and large radius tracking for ID vertices passing the full IDVx selection criteria.
The IDVx selection efficiency as a function of long-lived particle decay $z$ position for MC signal samples with a 125 GeV Higgs boson decaying to LLPs with masses of 8, 25, and 55 GeV. The efficiency for the 55 GeV LLP sample is shown both with and without the material veto applied.
The IDVx selection efficiency as a function of long-lived particle decay $z$ position for MC signal samples with mediators of masses 200, 400, and 600 GeV decaying to LLPs with a mass of 50 GeV. The efficiency for the 200 GeV mediator sample is shown both with and without the material veto applied.
The impact of the IDVx selections on the selection efficiency for the MC signal sample with a Higgs with a mass of 125 GeV decaying to an LLP with a mass of 8 GeV.
The impact of the IDVx selections on the selection efficiency for the MC signal sample with a Higgs with a mass of 125 GeV decaying to an LLP with a mass of 8 GeV.
The impact of the IDVx selections on the selection efficiency for the MC signal sample with a Higgs with a mass of 125 GeV decaying to an LLP with a mass of 8 GeV.
The impact of the IDVx selections on the selection efficiency for the MC signal sample with a $\Phi$ with a mass of 400 GeV decaying to an LLP with a mass of 50 GeV.
The impact of the IDVx selections on the selection efficiency for the MC signal sample with a $\Phi$ with a mass of 400 GeV decaying to an LLP with a mass of 50 GeV.
The impact of the IDVx selections on the selection efficiency for the MC signal sample with a $\Phi$ with a mass of 400 GeV decaying to an LLP with a mass of 50 GeV.
The impact of the IDVx selections on the selection efficiency for the MC signal sample with a $\Phi$ with a mass of 1000 GeV decaying to an LLP with a mass of 150 GeV.
The impact of the IDVx selections on the selection efficiency for the MC signal sample with a $\Phi$ with a mass of 1000 GeV decaying to an LLP with a mass of 150 GeV.
The impact of the IDVx selections on the selection efficiency for the MC signal sample with a $\Phi$ with a mass of 1000 GeV decaying to an LLP with a mass of 150 GeV.
$CL_S$ limits on $B_{H\rightarrow ss}$ for $m_{H} = 125$ GeV, $m_s = 8$ GeV.
$CL_S$ limits on $B_{H\rightarrow ss}$ for $m_{H} = 125$ GeV, $m_s = 15$ GeV.
$CL_S$ limits on $B_{H\rightarrow ss}$ for $m_{H} = 125$ GeV, $m_s = 25$ GeV.
$CL_S$ limits on $B_{H\rightarrow ss}$ for $m_{H} = 125$ GeV, $m_s = 40$ GeV.
$CL_S$ limits on $B_{H\rightarrow ss}$ for $m_{H} = 125$ GeV, $m_s = 55$ GeV.
$CL_S$ limits on $\sigma \times B_{\Phi\rightarrow ss}$ for $m_{\Phi} = 200$ GeV, $m_s = 8$ GeV.
$CL_S$ limits on $\sigma \times B_{\Phi\rightarrow ss}$ for $m_{\Phi} = 200$ GeV, $m_s = 25$ GeV.
$CL_S$ limits on $\sigma \times B_{\Phi\rightarrow ss}$ for $m_{\Phi} = 200$ GeV, $m_s = 50$ GeV.
$CL_S$ limits on $\sigma \times B_{\Phi\rightarrow ss}$ for $m_{\Phi} = 400$ GeV, $m_s = 50$ GeV.
$CL_S$ limits on $\sigma \times B_{\Phi\rightarrow ss}$ for $m_{\Phi} = 400$ GeV, $m_s = 100$ GeV.
$CL_S$ limits on $\sigma \times B_{\Phi\rightarrow ss}$ for $m_{\Phi} = 600$ GeV, $m_s = 50$ GeV.
$CL_S$ limits on $\sigma \times B_{\Phi\rightarrow ss}$ for $m_{\Phi} = 600$ GeV, $m_s = 150$ GeV.
$CL_S$ limits on $\sigma \times B_{\Phi\rightarrow ss}$ for $m_{\Phi} = 1000$ GeV, $m_s = 50$ GeV.
$CL_S$ limits on $\sigma \times B_{\Phi\rightarrow ss}$ for $m_{\Phi} = 1000$ GeV, $m_s = 150$ GeV.
$CL_S$ limits on $\sigma \times B_{\Phi\rightarrow ss}$ for $m_{\Phi} = 1000$ GeV, $m_s = 400$ GeV.
This paper presents results of searches for electroweak production of supersymmetric particles in models with compressed mass spectra. The searches use 139 fb$^{-1}$ of $\sqrt{s}=13$ TeV proton-proton collision data collected by the ATLAS experiment at the Large Hadron Collider. Events with missing transverse momentum and two same-flavor, oppositely charged, low transverse momentum leptons are selected, and are further categorized by the presence of hadronic activity from initial-state radiation or a topology compatible with vector-boson fusion processes. The data are found to be consistent with predictions from the Standard Model. The results are interpreted using simplified models of $R$-parity-conserving supersymmetry in which the lightest supersymmetric partner is a neutralino with a mass similar to the lightest chargino, the second-to-lightest neutralino or the slepton. Lower limits on the masses of charginos in different simplified models range from 193 GeV to 240 GeV for moderate mass splittings, and extend down to mass splittings of 1.5 GeV to 2.4 GeV at the LEP chargino bounds (92.4 GeV). Similar lower limits on degenerate light-flavor sleptons extend up to masses of 251 GeV and down to mass splittings of 550 MeV. Constraints on vector-boson fusion production of electroweak SUSY states are also presented.
Expected 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Expected 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Expected 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Expected 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Expected 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Observed 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Observed 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Observed 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Observed 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Observed 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Expected 95% CL exclusion sensitivity for simplified models of VBF wino-bino production.
Expected 95% CL exclusion sensitivity for simplified models of VBF wino-bino production.
Expected 95% CL exclusion sensitivity for simplified models of VBF wino-bino production.
Expected 95% CL exclusion sensitivity for simplified models of VBF wino-bino production.
Expected 95% CL exclusion sensitivity for simplified models of VBF wino-bino production.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production.
Expected 95% CL exclusion sensitivity for simplified models of direct slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH slepton production.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Expected 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Efficiency for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Observed 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Expected 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Efficiency for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Observed 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Expected 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Efficiency for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Observed 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Expected 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Efficiency for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Observed 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for higgsino scenarios.
Observed and Expected upper cross-section limits for higgsino scenarios.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for higgsino scenarios, assuming VBF production..
Observed and Expected upper cross-section limits for higgsino scenarios, assuming VBF production..
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for direct slepton scenarios.
Observed and Expected upper cross-section limits for direct slepton scenarios.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for direct LH slepton scenarios.
Observed and Expected upper cross-section limits for direct LH slepton scenarios.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for direct RH slepton scenarios.
Observed and Expected upper cross-section limits for direct RH slepton scenarios.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for direct smuon scenarios.
Observed and Expected upper cross-section limits for direct smuon scenarios.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for direct LH smuon scenarios.
Observed and Expected upper cross-section limits for direct LH smuon scenarios.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed and Expected upper cross-section limits for direct RH smuon scenarios.
Observed and Expected upper cross-section limits for direct RH smuon scenarios.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed and Expected upper cross-section limits for direct selectron scenarios.
Observed and Expected upper cross-section limits for direct selectron scenarios.
Observed and Expected upper cross-section limits for higgsino scenarios.
Observed and Expected upper cross-section limits for higgsino scenarios.
Observed and Expected upper cross-section limits for higgsino scenarios.
Observed and Expected upper cross-section limits for direct LH selectron scenarios.
Observed and Expected upper cross-section limits for direct LH selectron scenarios.
Observed and Expected upper cross-section limits for higgsino scenarios, assuming VBF production..
Observed and Expected upper cross-section limits for higgsino scenarios, assuming VBF production..
Observed and Expected upper cross-section limits for higgsino scenarios, assuming VBF production..
Observed and Expected upper cross-section limits for direct RH selectron scenarios.
Observed and Expected upper cross-section limits for direct RH selectron scenarios.
Observed and Expected upper cross-section limits for direct slepton scenarios.
Observed and Expected upper cross-section limits for direct slepton scenarios.
Observed and Expected upper cross-section limits for direct slepton scenarios.
Number of signal events in SR-E-1L1T for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-1L1T for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Observed and Expected upper cross-section limits for direct LH slepton scenarios.
Observed and Expected upper cross-section limits for direct LH slepton scenarios.
Observed and Expected upper cross-section limits for direct LH slepton scenarios.
Number of signal events in SR-E-high for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-high for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Observed and Expected upper cross-section limits for direct RH slepton scenarios.
Observed and Expected upper cross-section limits for direct RH slepton scenarios.
Observed and Expected upper cross-section limits for direct RH slepton scenarios.
Number of signal events in SR-E-low for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-low for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Observed and Expected upper cross-section limits for direct smuon scenarios.
Observed and Expected upper cross-section limits for direct smuon scenarios.
Observed and Expected upper cross-section limits for direct smuon scenarios.
Number of signal events in SR-E-med for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-med for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Observed and Expected upper cross-section limits for direct LH smuon scenarios.
Observed and Expected upper cross-section limits for direct LH smuon scenarios.
Observed and Expected upper cross-section limits for direct LH smuon scenarios.
Number of signal events in SR-S-high for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-S-high for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Observed and Expected upper cross-section limits for direct RH smuon scenarios.
Observed and Expected upper cross-section limits for direct RH smuon scenarios.
Observed and Expected upper cross-section limits for direct RH smuon scenarios.
Number of signal events in SR-S-low for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-S-low for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Observed and Expected upper cross-section limits for direct selectron scenarios.
Observed and Expected upper cross-section limits for direct selectron scenarios.
Observed and Expected upper cross-section limits for direct selectron scenarios.
Number of signal events in SR-VBF for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (100 GeV, 95 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-VBF for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (100 GeV, 95 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Observed and Expected upper cross-section limits for direct LH selectron scenarios.
Observed and Expected upper cross-section limits for direct LH selectron scenarios.
Observed and Expected upper cross-section limits for direct LH selectron scenarios.
Observed and Expected upper cross-section limits for direct RH selectron scenarios.
Observed and Expected upper cross-section limits for direct RH selectron scenarios.
Observed and Expected upper cross-section limits for direct RH selectron scenarios.
Number of signal events in SR-E-1L1T for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-1L1T for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-1L1T for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-high for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-high for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-high for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-low for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-low for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-low for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-med for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-med for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-med for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-S-high for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-S-high for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-S-high for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-S-low for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-S-low for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-S-low for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-VBF for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (100 GeV, 95 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-VBF for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (100 GeV, 95 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-VBF for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (100 GeV, 95 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
When you search on a word, e.g. 'collisions', we will automatically search across everything we store about a record. But, sometimes you may wish to be more specific. Here we show you how.
Guidance and examples on the query string syntax can be found in the Elasticsearch documentation.
About HEPData Submitting to HEPData HEPData File Formats HEPData Coordinators HEPData Terms of Use HEPData Cookie Policy
Status Email Forum Twitter GitHub
Copyright ~1975-Present, HEPData | Powered by Invenio, funded by STFC, hosted and originally developed at CERN, supported and further developed at IPPP Durham.