Fraction of non-prompt J/$\psi$ in p--Pb collisions at $\sqrt{s_\mathrm{NN}}$ = 8.16 TeV as a function of $p_\mathrm{T}$.

d$^2\sigma$/d$y$d$p_{\rm T}$ in bins of $p_{\mathrm{T}}^{J/\psi}$ for prompt J/$\psi$ in p--Pb collisions at $\sqrt{s_{NN}}$ = 8.16 TeV.

d$^2\sigma$/d$y$d$p_{\rm T}$ in bins of $p_{\mathrm{T}}^{J/\psi}$ for non-prompt J/$\psi$ in p--Pb collisions at $\sqrt{s_{NN}}$ = 8.16 TeV.

Nuclear modification factor ($R_{pPb}$) of prompt J/$\psi$ in p--Pb collisions at $\sqrt{s_{NN}}$ = 8.16 TeV at midrapidity.

Nuclear modification factor ($R_{pPb}$) of non-prompt J/$\psi$ in p--Pb collisions at $\sqrt{s_{NN}}$ = 8.16 TeV at midrapidity.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.2$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.2$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.2$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.2$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.2$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.2$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=0$) for jets of $R=0.2$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=1$) for jets of $R=0.2$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.2$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.2$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$Standard for jets of $R=0.2$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=0$) for jets of $R=0.2$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=1$) for jets of $R=0.2$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.2$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.2$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.2$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.2$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.2$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.2$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=0$) for jets of $R=0.2$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=1$) for jets of $R=0.2$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.2$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.2$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$Standard for jets of $R=0.2$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=0$) for jets of $R=0.2$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=1$) for jets of $R=0.2$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.2$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.2$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.2$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.2$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.2$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.2$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=0$) for jets of $R=0.2$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=1$) for jets of $R=0.2$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.2$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.2$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$Standard for jets of $R=0.2$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=0$) for jets of $R=0.2$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=1$) for jets of $R=0.2$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.2$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.2$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.2$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.2$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.2$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.2$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=0$) for jets of $R=0.2$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=1$) for jets of $R=0.2$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.2$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.2$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$Standard for jets of $R=0.4$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=0$) for jets of $R=0.4$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=1$) for jets of $R=0.4$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.4$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.4$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.4$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.4$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.4$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.4$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=0$) for jets of $R=0.4$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=1$) for jets of $R=0.4$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.4$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.4$, in the interval $20<p_{\rm T}^{\rm ch \ jet}<40 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$Standard for jets of $R=0.4$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=0$) for jets of $R=0.4$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=1$) for jets of $R=0.4$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.4$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.4$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.4$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.4$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.4$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.4$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=0$) for jets of $R=0.4$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=1$) for jets of $R=0.4$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.4$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.4$, in the interval $40<p_{\rm T}^{\rm ch \ jet}<60 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$Standard for jets of $R=0.4$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=0$) for jets of $R=0.4$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=1$) for jets of $R=0.4$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.4$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.4$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.4$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.4$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.4$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.4$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=0$) for jets of $R=0.4$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=1$) for jets of $R=0.4$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.4$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.4$, in the interval $60<p_{\rm T}^{\rm ch \ jet}<80 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$Standard for jets of $R=0.4$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=0$) for jets of $R=0.4$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=1$) for jets of $R=0.4$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.4$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.4$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.4$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for WTA$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.4$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.3,\beta=1$) for jets of $R=0.4$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.2,\beta=1$) for jets of $R=0.4$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=0$) for jets of $R=0.4$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=1$) for jets of $R=0.4$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=2$) for jets of $R=0.4$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

$\Delta R_{\rm axis}$ distribution for Standard$\textendash$SD with grooming setting ($z_{\rm cut}=0.1,\beta=3$) for jets of $R=0.4$, in the interval $80<p_{\rm T}^{\rm ch \ jet}<100 \ {\rm GeV}/c$.

Distribution of the most-probable value of the WTA$\textendash$Standard spectra as a function of $p_{\rm T}^{\rm ch \ jet}$ for $R=0.2$.

Distribution of the most-probable value of the WTA$\textendash$Standard spectra as a function of $p_{\rm T}^{\rm ch \ jet}$ for $R=0.4$.

$p_{\rm T}$-differential density of $\Xi^{\pm}$ in jets and the underlying event in pp collisions at $\sqrt{s} = 13$ TeV.

$p_{\rm T}$-differential density of inclusive $\Omega^{\pm}$ in pp collisions at $\sqrt{s} = 13$ TeV.

$p_{\rm T}$-differential density of $\Omega^{\pm}$ in jets and the underlying event in pp collisions at $\sqrt{s} = 13$ TeV.

$p_{\rm T}$-differential $(\Lambda + \overline{\Lambda})/2{\rm K}_{\rm S}^{0}$ ratio of inclusive particles in pp collisions at $\sqrt{s} = 13$ TeV.

$p_{\rm T}$-differential $(\Lambda + \overline{\Lambda})/2{\rm K}_{\rm S}^{0}$ ratio in jets and the underlying event in pp collisions at $\sqrt{s} = 13$ TeV.

$p_{\rm T}$-differential $(\Xi^{-} + \Xi^{+}) / 2{\rm K}_{\rm S}^{0}$ and $(\Xi^{-} + \Xi^{+}) / (\Lambda + \overline{\Lambda})$ ratios of inclusive particles in pp collisions at $\sqrt{s} = 13$ TeV.

$p_{\rm T}$-differential $(\Xi^{-} + \Xi^{+}) / 2{\rm K}_{\rm S}^{0}$ and $(\Xi^{-} + \Xi^{+}) / (\Lambda + \overline{\Lambda})$ ratios in jets and the underlying event in pp collisions at $\sqrt{s} = 13$ TeV.

$p_{\rm T}$-differential $(\Omega^{-} + \Omega^{+}) / 2{\rm K}_{\rm S}^{0}$, $(\Omega^{-} + \Omega^{+}) / (\Lambda + \overline{\Lambda})$ and $(\Omega^{-} + \Omega^{+}) / (\Xi^{-} + \Xi^{+})$ ratios of inclusive particles in pp collisions at $\sqrt{s} = 13$ TeV.

$p_{\rm T}$-differential $(\Omega^{-} + \Omega^{+}) / 2{\rm K}_{\rm S}^{0}$, $(\Omega^{-} + \Omega^{+}) / (\Lambda + \overline{\Lambda})$ and $(\Omega^{-} + \Omega^{+}) / (\Xi^{-} + \Xi^{+})$ ratios in jets and the underlying event in pp collisions at $\sqrt{s} = 13$ TeV.

$p_{\rm T}$-differential density of inclusive ${\rm K}_{\rm S}^{0}$ and $\Lambda$ ($\overline{\Lambda}$) in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential densities of ${\rm K}_{\rm S}^{0}$ and $\Lambda$ ($\overline{\Lambda}$) in jets and the underlying event in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential density of inclusive $\Xi^{\pm}$ in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential density of $\Xi^{\pm}$ in jets and the underlying event in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential density of inclusive $\Omega^{\pm}$ in p-Pb collisions at $\sqrt{s} = 5.02$ TeV.

$p_{\rm T}$-differential density of $\Omega^{\pm}$ in jets and the underlying event in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential $(\Lambda + \overline{\Lambda})/2{\rm K}_{\rm S}^{0}$ ratio in jets for various event activity classes in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential $(\Xi^{-} + \Xi^{+}) / 2{\rm K}_{\rm S}^{0}$ and $(\Xi^{-} + \Xi^{+}) / (\Lambda + \overline{\Lambda})$ ratios in jets for various event activity classes in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential $(\Omega^{-} + \Omega^{+}) / 2{\rm K}_{\rm S}^{0}$, $(\Omega^{-} + \Omega^{+}) / (\Lambda + \overline{\Lambda})$ and $(\Omega^{-} + \Omega^{+}) / (\Xi^{-} + \Xi^{+})$ ratios in jets in MB p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential density of inclusive ${\rm K}_{\rm S}^{0}$ and $\Lambda$ ($\overline{\Lambda}$) for $0$-$10\%$ event activity class in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential densities of ${\rm K}_{\rm S}^{0}$ and $\Lambda$ ($\overline{\Lambda}$) in jets and the underlying event for $0$-$10\%$ event activity class in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential density of inclusive $\Xi^{\pm}$ for $0$-$10\%$ event activity class in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential density of $\Xi^{\pm}$ in jets and the underlying event for $0$-$10\%$ event activity class in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential density of inclusive ${\rm K}_{\rm S}^{0}$ and $\Lambda$ ($\overline{\Lambda}$) for $10$-$40\%$ event activity class in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential densities of ${\rm K}_{\rm S}^{0}$ and $\Lambda$ ($\overline{\Lambda}$) in jets and the underlying event for $10$-$40\%$ event activity class in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential density of inclusive $\Xi^{\pm}$ for $10$-$40\%$ event activity class in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential density of $\Xi^{\pm}$ in jets and the underlying event for $10$-$40\%$ event activity class in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential density of inclusive ${\rm K}_{\rm S}^{0}$ and $\Lambda$ ($\overline{\Lambda}$) for $40$-$100\%$ event activity class in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential densities of ${\rm K}_{\rm S}^{0}$ and $\Lambda$ ($\overline{\Lambda}$) in jets and the underlying event for $40$-$100\%$ event activity class in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential density of inclusive $\Xi^{\pm}$ for $40$-$100\%$ event activity class in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential density of $\Xi^{\pm}$ in jets and the underlying event for $40$-$100\%$ event activity class in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential $(\Lambda + \overline{\Lambda})/2{\rm K}_{\rm S}^{0}$ ratio of inclusive particles for various event activity classes in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential $(\Lambda + \overline{\Lambda})/2{\rm K}_{\rm S}^{0}$ ratio in the underlying event for various event activity classes in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential $(\Lambda + \overline{\Lambda})/2{\rm K}_{\rm S}^{0}$ ratio in jets for various event activity classes in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential $(\Xi^{-} + \Xi^{+}) / 2{\rm K}_{\rm S}^{0}$ ratio of inclusive particles for various event activity classes in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential $(\Xi^{-} + \Xi^{+}) / 2{\rm K}_{\rm S}^{0}$ ratio in the underlying event for $0$-$10\%$ event activity class in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential $(\Xi^{-} + \Xi^{+}) / 2{\rm K}_{\rm S}^{0}$ ratio in the underlying event for $10$-$40\%$ and $40$-$100\%$ event activity classes in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential $(\Xi^{-} + \Xi^{+}) / 2{\rm K}_{\rm S}^{0}$ ratio in jets for various event activity classes in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential $(\Xi^{-} + \Xi^{+}) / (\Lambda + \overline{\Lambda})$ ratio of inclusive particles for various event activity classes in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential $(\Xi^{-} + \Xi^{+}) / (\Lambda + \overline{\Lambda})$ ratio in the underlying event for $0$-$10\%$ event activity class in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential $(\Xi^{-} + \Xi^{+}) / (\Lambda + \overline{\Lambda})$ ratio in the underlying event for $10$-$40\%$ and $40$-$100\%$ event activity classes in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

$p_{\rm T}$-differential $(\Xi^{-} + \Xi^{+}) / (\Lambda + \overline{\Lambda})$ ratio in jets for various event activity classes in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV.

Probability of finding at least one TAR jet, where the p_T-leading TAR jet passes the m_Wcand and D₂^&beta;=1 requirements, as a function of m_s. The probability is determined in a sample of signal events with m_Z'=2100 GeV, with the preselections applied.

Probability of finding a W_had candidate reconstructed as a pair of R=0.4 PFlow jets, as a function of m_s. The probability is determined in a sample of signal events with m_Z'=500 GeV, with the preselections applied that do not pass the requirements of the merged category.

Probability of finding a W_had candidate reconstructed as a pair of R=0.4 PFlow jets, as a function of m_s. The probability is determined in a sample of signal events with m_Z'=1000 GeV, with the preselections applied that do not pass the requirements of the merged category.

Probability of finding a W_had candidate reconstructed as a pair of R=0.4 PFlow jets, as a function of m_s. The probability is determined in a sample of signal events with m_Z'=1700 GeV, with the preselections applied that do not pass the requirements of the merged category.

Probability of finding a W_had candidate reconstructed as a pair of R=0.4 PFlow jets, as a function of m_s. The probability is determined in a sample of signal events with m_Z'=2100 GeV, with the preselections applied that do not pass the requirements of the merged category.

Observed exclusion contour at 95&#37; C.L. for the dark Higgs model in the (m_Z', m_s) plane for g_q=0.25, g_&chi;=1, m_&chi;=200 GeV, and sin&theta;=0.01.

Expected exclusion contour at 95&#37; C.L. for the dark Higgs model in the (m_Z', m_s) plane for g_q=0.25, g_&chi;=1, m_&chi;=200 GeV, and sin&theta;=0.01.

Expected+1&sigma; exclusion contour at 95&#37; C.L. for the dark Higgs model in the (m_Z', m_s) plane for g_q=0.25, g_&chi;=1, m_&chi;=200 GeV, and sin&theta;=0.01.

Expected-1&sigma; exclusion contour at 95&#37; C.L. for the dark Higgs model in the (m_Z', m_s) plane for g_q=0.25, g_&chi;=1, m_&chi;=200 GeV, and sin&theta;=0.01.

Expected+2&sigma; exclusion contour at 95&#37; C.L. for the dark Higgs model in the (m_Z', m_s) plane for g_q=0.25, g_&chi;=1, m_&chi;=200 GeV, and sin&theta;=0.01.

Expected-2&sigma; exclusion contour at 95&#37; C.L. for the dark Higgs model in the (m_Z', m_s) plane for g_q=0.25, g_&chi;=1, m_&chi;=200 GeV, and sin&theta;=0.01.

Observed upper limits at 95&#37; C.L. on &sigma;(pp &rarr; s &chi;&chi;) &times; B(s &rarr; W^&pm; W^&mp;) for m_Z'=0.5 TeV as a function of m_s. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the &sigma;(pp &rarr; s &chi;&chi;) &times; B(s &rarr; W^&pm; W^&mp;) process for m_Z'=0.5 TeV, shown in dashed blue.

Observed upper limits at 95&#37; C.L. on &sigma;(pp &rarr; s &chi;&chi;) &times; B(s &rarr; W^&pm; W^&mp;) for m_Z'=1 TeV as a function of m_s. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the &sigma;(pp &rarr; s &chi;&chi;) &times; B(s &rarr; W^&pm; W^&mp;) process for m_Z'=1 TeV, shown in dashed blue.

Observed upper limits at 95&#37; C.L. on &sigma;(pp &rarr; s &chi;&chi;) &times; B(s &rarr; W^&pm; W^&mp;) for m_Z'=1.7 TeV as a function of m_s. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the &sigma;(pp &rarr; s &chi;&chi;) &times; B(s &rarr; W^&pm; W^&mp;) process for m_Z'=1.7 TeV, shown in dashed blue.

Observed upper limits at 95&#37; C.L. on &sigma;(pp &rarr; s &chi;&chi;) &times; B(s &rarr; W^&pm; W^&mp;) for m_Z'=2.1 TeV as a function of m_s. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the &sigma;(pp &rarr; s &chi;&chi;) &times; B(s &rarr; W^&pm; W^&mp;) process for m_Z'=2.1 TeV, shown in dashed blue.

Data overlaid on SM background yields stacked in each SR and CR category after the fit to data ('Post-fit'). The yields in the SR are broken down into their contributions to the individual bins. The maximum-likelihood estimators are set to the conditional values of the CR-only fit, and propagated to SR and CRs.

Dominant sources of uncertainty for three dark Higgs scenarios after the fit to data. The uncertainties are quantified in terms of their contribution to the fitted signal uncertainty that is expressed relative to the theory prediction. Three representative dark Higgs signal scenarios with g_q=0.25, g_&chi;=1.0, sin&theta;=0.01 and m_&chi;=200 GeV are considered, which are indicated using the (m_Z', m_s) format in units of GeV in the table columns.

Cumulative efficiencies in the merged category for three representative dark Higgs signal scenarios with g_q=0.25, g_&chi;=1.0, sin&theta;=0.01, m_Z' = 1 TeV, and m_&chi;=200 GeV considering s&rarr;W(&ell;&nu;)W(qq) decays only.

Cumulative efficiencies in the resolved category for three representative dark Higgs signal scenarios with g_q=0.25, g_&chi;=1.0, sin&theta;=0.01, m_Z' = 1 TeV, and m_&chi;=200 GeV considering s&rarr;W(&ell;&nu;)W(qq) decays only.

Theoretical cross section for &sigma;(pp &rarr; s&chi;&chi;) &times; B(s &rarr; W^&plusmn;W^&#8723;) for each of the dark Higgs signal points at m_Z′ ={300, 350, 400, 500, 750} GeV, with g_q = 0.25, g<sub>&chi; = 1.0, sin&theta; = 0.01, m_Z′ = 1 TeV , and m_&chi; = 200 GeV. Also shown are experimentally excluded cross sections of &sigma;(pp &rarr; s&chi;&chi;) &times; B(s &rarr; W^&plusmn;W^&#8723;) (Obs.) together with the expectations (Exp.) varied up and down by one standard deviation (&plusmn;1&sigma;).

Theoretical cross section for &sigma;(pp &rarr; s&chi;&chi;) &times; B(s &rarr; W^&plusmn;W^&#8723;) for each of the dark Higgs signal points at m_Z′ ={1000, 1700} GeV, with g_q = 0.25, g<sub>&chi; = 1.0, sin&theta; = 0.01, m_Z′ = 1 TeV , and m_&chi; = 200 GeV. Also shown are experimentally excluded cross sections of &sigma;(pp &rarr; s&chi;&chi;) &times; B(s &rarr; W^&plusmn;W^&#8723;) (Obs.) together with the expectations (Exp.) varied up and down by one standard deviation (&plusmn;1&sigma;).

Theoretical cross section for &sigma;(pp &rarr; s&chi;&chi;) &times; B(s &rarr; W^&plusmn;W^&#8723;) for each of the dark Higgs signal points at m_Z′ ={2100, 2500, 2900, 3300} GeV, with g_q = 0.25, g<sub>&chi; = 1.0, sin&theta; = 0.01, m_Z′ = 1 TeV , and m_&chi; = 200 GeV. Also shown are experimentally excluded cross sections of &sigma;(pp &rarr; s&chi;&chi;) &times; B(s &rarr; W^&plusmn;W^&#8723;) (Obs.) together with the expectations (Exp.) varied up and down by one standard deviation (&plusmn;1&sigma;).

Parametrization of the $A_{X}$ factor, defined as the fraction of diphoton resonances satisfying the fiducial acceptance at the particle level, as function of $m_{X}$ obtained from the narrow width simulated signal samples produced in gluon fusion.

The correction factor, $C_{X}$, defined as the ratio between the number of reconstructed signal events passing the analysis cuts and the number of signal events at the particle level generated within the fiducial volume, and acceptance correction factor, $A_{X}$, defined as the fraction of diphoton resonances satisfying the fiducial acceptance at the particle level. Both are computed for NWA spin-0 models as a function of $m_{X}$.

Effect of event selections on a scalar MC signal sample generated for $m_{X}$ = 15 GeV and on the data. For the MC sample, the efficiencies are shown after applying event weights and a truth level filter that requires two photons with $p^{\gamma\gamma}_{T}>40$ GeV; for the data, the absolute yields are shown. The initial yields for data include a trigger preselection that is the OR of a list of single photon and diphoton triggers. The "2 $loose$ photons" step includes the kinematic acceptance cuts.

Parameterization of the Double Sided Crystal Ball function parameters describing the scalar mass resolution model as a function of $m_{X}$ [GeV].

Expected 95% CL upper limits with 1-sigma uncertainty on the production of a heavy Higgs boson as functions of fw and fww with mass equal to 300 GeV.

Expected 95% CL upper limits with 2-sigma uncertainty on the production of a heavy Higgs boson as functions of fw and fww with mass equal to 300 GeV.

Observed 95% CL upper limits on the production of a heavy Higgs boson as functions of fw and fww with mass equal to 300 GeV.

Expected 95% CL upper limits on the production of a heavy Higgs boson as functions of fw and fww with mass equal to 600 GeV.

Expected 95% CL upper limits with 1-sigma uncertainty on the production of a heavy Higgs boson as functions of fw and fww with mass equal to 600 GeV.

Expected 95% CL upper limits with 2-sigma uncertainty on the production of a heavy Higgs boson as functions of fw and fww with mass equal to 600 GeV.

Observed 95% CL upper limits on the production of a heavy Higgs boson as functions of fw and fww with mass equal to 600 GeV.

Expected 95% CL upper limits on the production of a heavy Higgs boson as functions of fw and fww with mass equal to 900 GeV.

Expected 95% CL upper limits with 1-sigma uncertainty on the production of a heavy Higgs boson as functions of fw and fww with mass equal to 900 GeV.

Expected 95% CL upper limits with 2-sigma uncertainty on the production of a heavy Higgs boson as functions of fw and fww with mass equal to 900 GeV.

Observed 95% CL upper limits on the production of a heavy Higgs boson as functions of fw and fww with mass equal to 900 GeV.

Observed (black solid curve) and expected (black dashed curve) 95% CL upper limits on the production of a heavy Higgs boson as functions of its mass with ( fW, fWW) fixed at (0, 6200). The green (inner) and yellow (outer) bands represent 1 and 2 sigma uncertainty in the expected limits. Theoretical predictions (red solid curve) as functions of the heavy Higgs boson mass are overlaid.

Observed (black solid curve) and expected (black dashed curve) 95% CL upper limits on the production of a heavy Higgs boson as functions of its mass with ( fW, fWW) fixed at (1350, 0). The green (inner) and yellow (outer) bands represent 1 and 2 sigma uncertainty in the expected limits. Theoretical predictions (red solid curve) as functions of the heavy Higgs boson mass are overlaid.

Near-side ratios of V^{0}-triggered yields to charged-hadron triggered (h$-$h) ones, ${{Y}^{K^{0}_{S}-\mathrm{h}}_{\Delta\varphi}}/{{Y}^{\mathrm{h-h}}_{\Delta\varphi}}$ and ${{Y}^{(\Lambda+\overline{\Lambda})-\mathrm{h}}_{\Delta\varphi}}/{{Y}^{\mathrm{h-h}}_{\Delta\varphi}}$ in Pb-Pb collisions.

Away-side ratios of V^{0}-triggered yields to charged-hadron triggered (h$-$h) ones, ${{Y}^{K^{0}_{S}-\mathrm{h}}_{\Delta\varphi}}/{{Y}^{\mathrm{h-h}}_{\Delta\varphi}}$ and ${{Y}^{(\Lambda+\overline{\Lambda})-\mathrm{h}}_{\Delta\varphi}}/{{Y}^{\mathrm{h-h}}_{\Delta\varphi}}$ in Pb-Pb collisions.

Near-side ratios of V^{0}-triggered yields to charged-hadron triggered (h--h) ones, ${{Y}^{K^{0}_{S}-\mathrm{h}}_{\Delta\varphi}}/{{Y}^{\mathrm{h-h}}_{\Delta\varphi}}$ and ${{Y}^{(\Lambda+\overline{\Lambda})-\mathrm{h}}_{\Delta\varphi}}/{{Y}^{\mathrm{h-h}}_{\Delta\varphi}}$ in pp collisions.

Away-side ratios of V^{0}-triggered yields to charged-hadron triggered (h--h) ones, ${{Y}^{K^{0}_{S}-\mathrm{h}}_{\Delta\varphi}}/{{Y}^{\mathrm{h-h}}_{\Delta\varphi}}$ and ${{Y}^{(\Lambda+\overline{\Lambda})-\mathrm{h}}_{\Delta\varphi}}/{{Y}^{\mathrm{h-h}}_{\Delta\varphi}}$ in Pb-Pb collisions.

Pre-fit comparison between data and background in the baseline SR for two of the variables used as input for the BSM pBDT: HT.

Data and post-fit background comparison for the distributions of the discriminant variables fitted in the control regions obtained with the background-only fit: CR HF e.

Data and post-fit background comparison for the distributions of the discriminant variables fitted in the control regions obtained with the background-only fit: CR HF mu.

Data and post-fit background comparison for the distributions of the discriminant variables fitted in the control regions obtained with the background-only fit: CR Conv.

Data and post-fit background comparison for the distributions of the discriminant variables fitted in the control regions obtained with the background-only fit: CR ttW.

Data and post-fit background comparison for the distributions of the discriminant variables fitted in the control regions obtained with the background-only fit: CR lowBDT.

Data and post-fit background comparison obtained with the background-only fit in the validation region defined for ttW+jets events: number of jets.

Data and post-fit background comparison obtained with the background-only fit in the validation region defined for ttW+jets events: SM BDT.

Data and post-fit background comparison obtained with the background-only fit to the BSM SR for the BSM pBDT distribution used for mH = 400 GeV.

Data and post-fit background comparison obtained with the background-only fit to the BSM SR for the BSM pBDT distribution used for mH = 1000 GeV.

Observed (black solid line) and expected (black dashed line) 95% CL upper limits on the ttH/A cross-section times branching fraction of H/A->tt as a function of mH/A.

Observed (red line) and expected (black dashed line) exclusion regions at 95% CL in the tan(beta) versus mass plane assuming that both, a heavy scalar H and pseudo-scalar A, contribute to the tttt final state and have the same mass mH=mA.

Observed (red line) and expected (black dashed line) exclusion regions at 95% CL in the tan(beta) versus mass plane assuming that only the scalar H contributes to the tttt final state.

Data and post-fit background comparison obtained with the background-only fit to the BSM SR for the BSM pBDT distribution used for mH = 500 GeV.

Data and post-fit background comparison obtained with the background-only fit to the BSM SR for the BSM pBDT distribution used for mH = 600 GeV.

Data and post-fit background comparison obtained with the background-only fit to the BSM SR for the BSM pBDT distribution used for mH = 700 GeV.

Data and post-fit background comparison obtained with the background-only fit to the BSM SR for the BSM pBDT distribution used for mH = 800 GeV.

Data and post-fit background comparison obtained with the background-only fit to the BSM SR for the BSM pBDT distribution used for mH = 900 GeV.

Observed (red line) and expected (black dashed line) exclusion regions at 95% CL in the tan(beta) versus mass plane assuming that only the pseudo-scalar A contributes to the tttt final state.

The product of acceptance and efficiency (A×ε), defined as the number of signal events satisfying the full set of selection criteria of the BSM SR, divided by the total number of generated signal events, for the tt̄H(→ tt̄ ) process in a type-II 2HDM for tanβ = 1 for the different heavy Higgs mass hypotheses.

Observed 95% CL limits on the production cross-section for scalar up-type LQs decaying into a top quark and a neutrino or a bottom quark and an electron.

Expected 95% CL limits on the production cross-section for scalar up-type LQs decaying into a top quark and a neutrino or a bottom quark and an electron.

Observed 95% CL limits on the production cross-section for scalar down-type LQs decaying into a bottom quark and a neutrino or a top quark and a muon.

Expected 95% CL limits on the production cross-section for scalar down-type LQs decaying into a bottom quark and a neutrino or a top quark and a muon.

Observed 95% CL limits on the production cross-section for scalar down-type LQs decaying into a bottom quark and a neutrino or a top quark and an electron.

Expected 95% CL limits on the production cross-section for scalar down-type LQs decaying into a bottom quark and a neutrino or a top quark and an electron.

Observed 95% CL limits on the production cross-section for vector up-type LQs in the Yang-Mills coupling scenario decaying into a top quark and a neutrino or a bottom quark and a muon.

Expected 95% CL limits on the production cross-section for vector up-type LQs in the Yang-Mills coupling scenario decaying into a top quark and a neutrino or a bottom quark and a muon.

Observed 95% CL limits on the production cross-section for vector up-type LQs in the Yang-Mills coupling scenario decaying into a top quark and a neutrino or a bottom quark and an electron.

Expected 95% CL limits on the production cross-section for vector up-type LQs in the Yang-Mills coupling scenario decaying into a top quark and a neutrino or a bottom quark and an electron.

Observed 95% CL limits on the production cross-section for vector up-type LQs in the minimal coupling scenario decaying into a top quark and a neutrino or a bottom quark and a muon.

Expected 95% CL limits on the production cross-section for vector up-type LQs in the minimal coupling scenario decaying into a top quark and a neutrino or a bottom quark and a muon.

Observed 95% CL limits on the production cross-section for vector up-type LQs in the minimal coupling scenario decaying into a top quark and a neutrino or a bottom quark and an electron.

Expected 95% CL limits on the production cross-section for vector up-type LQs in the minimal coupling scenario decaying into a top quark and a neutrino or a bottom quark and an electron.

Product of signal acceptance and efficiency in the training region for scalar up-type LQs decaying into top quarks and neutrinos or bottom quarks and muons depending on the signal mass, $m_{LQ}$, and $\mathcal{B}(LQ_{mix}^u\rightarrow b\mu)$.

Product of signal acceptance and efficiency in the training region for scalar up-type LQs decaying into top quarks and neutrinos or bottom quarks and electrons depending on the signal mass, $m_{LQ}$, and $\mathcal{B}(LQ_{mix}^u\rightarrow be)$.

Product of signal acceptance and efficiency in the training region for scalar down-type LQs decaying into top quarks and muons or bottom quarks and neutrinos depending on the signal mass, $m_{LQ}$, and $\mathcal{B}(LQ_{mix}^d\rightarrow t\mu)$.

Product of signal acceptance and efficiency in the training region for scalar down-type LQs decaying into top quarks and electrons or bottom quarks and neutrinos depending on the signal mass, $m_{LQ}$, and $\mathcal{B}(LQ_{mix}^d\rightarrow te)$.

Product of signal acceptance and efficiency in the training region for vector LQs in the Yang-Mills coupling scenario decaying into top quarks and neutrinos or bottom quarks and muons depending on the signal mass, $m_{LQ}$, and $\mathcal{B}(vLQ_{mix}^{YM}\rightarrow b\mu)$.

Product of signal acceptance and efficiency in the training region for vector LQs in the Yang-Mills coupling scenario decaying into top quarks and neutrinos or bottom quarks and electrons depending on the signal mass, $m_{LQ}$, and $\mathcal{B}(vLQ_{mix}^{YM}\rightarrow be)$.

Product of signal acceptance and efficiency in the training region for vector LQs in the minimal coupling scenario decaying into top quarks and neutrinos or bottom quarks and muons depending on the signal mass, $m_{LQ}$, and $\mathcal{B}(vLQ_{mix}^{min}\rightarrow b\mu)$.

Product of signal acceptance and efficiency in the training region for vector LQs in the minimal coupling scenario decaying into top quarks and neutrinos or bottom quarks and electrons depending on the signal mass, $m_{LQ}$, and $\mathcal{B}(vLQ_{mix}^{min}\rightarrow be)$.

Cut-flow for the four models containing scalar LQs at a mass of $m_{LQ}=1300$ GeV and $\mathcal{B}(LQ_{mix}\rightarrow q_3\ell)=0.5$.

Cut-flow for the four models containing vector LQs at a mass of $m_{LQ}=1300$ GeV and $\mathcal{B}(LQ_{mix}\rightarrow q_3\ell)=0.5$.

Results of applying the BH algorithm to the mass spectra in the leading photon category, using the fitted background estimations from the initial step

Results of applying the BH algorithm to the mass spectra in the leading electron category, using the fitted background estimations from the initial step

Results of applying the BH algorithm to the mass spectra in the leading muon category, using the fitted background estimations from the initial step

Results of applying the BH algorithm to the mass spectra in the leading small-R jet category, using the fitted background estimations from the initial step

Results of applying the BH algorithm to the mass spectra in the leading bjet category, using the fitted background estimations from the initial step

Results of applying the BH algorithm to the mass spectra in the leading large-R jet category, using the fitted background estimations from the initial step

Results of applying the BH algorithm to the mass spectra in the leading photon category, using the fitted background estimations from the initial step

Results of applying the BH algorithm to the mass spectra in the leading electron category, using the fitted background estimations from the initial step

Results of applying the BH algorithm to the mass spectra in the leading muon category, using the fitted background estimations from the initial step

Results of applying the BH algorithm to the mass spectra in the inclusive category, using the fitted background estimations from the initial step

Results of applying the BH algorithm to the mass spectra in the inclusive category, using the fitted background estimations from the initial step

Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading small-R jet category

Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading bjet category

Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading large-R jet category

Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading photon category

Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading electron category

Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading muon category

Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading small-R jet category

Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading bjet category

Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading large-R jet category

Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading photon category

Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading electron category

Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the leading muon category

Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the inclusive category

Upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signal with a relative width value of 3% as a function of mass in the inclusive category

Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading small-R jet category

Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading bjet category

Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading large-R jet category

Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading photon category

Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading electron category

Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading muon category

Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading small-R jet category

Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading bjet category

Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading large-R jet category

Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading photon category

Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading electron category

Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the leading muon category

Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the inclusive category

Comparison of observed upper limits at 95% CL on the cross section times branching fraction times acceptance for a Gaussian-shaped signals with relative width values as a function of mass in the inclusive category

Acceptance times efficiency in an HVT model as a function of mass in the leading large-R jet category

Upper limits at 95% CL on the cross section times the branching fraction($W^{\prime} \to ZW$) for the HVT signal as functions of mass($m_{ZX}$) in the leading large-R jet category.The full(dashed) red curves correspond to the theoretical predictions of HVT model A(B)

Comparison of the identification efficiencies using standard and merged-ee reconstruction as a function of true PT(Z)

Background rejection factor as a function of signal efficiency. The red curve shows the BDT performance whereas the blue curve corresponds to that of a cut-based analysis relying only on the jet energyfraction deposited in the EM calorimeter

BH p-values of the 100 pseudo-experiments as a function of in the leading small-R jet category for an injected Gaussian-shaped signal with a relative width value of 3%. The fractions of the pseudo-experiments that have the correctly identified interval and BH p-values below the threshold of 0.01 are indicated. The background is derived by the background-only fit in the full fitting range.

BH p-values of the 100 pseudo-experiments as a function of in the leading small-R jet category for an injected Gaussian-shaped signal with a relative width value of 3%. The fractions of the pseudo-experiments that have the correctly identified interval and BH p-values below the threshold of 0.01 are indicated. The background is derived by the background-only fit in the range excluding the BH interval.

Fractions of pseudo-experiments in which the detected BH interval agrees with the injected mass point and the BH p-value is below 0.01 as a function of mass in the leading small-R jet category for Gaussian-shaped signal with a relative width of 3%.

Fractions of pseudo-experiments in which the detected BH interval agrees with the injected mass point and the BH p-value is below 0.01 as a function of mass in the leading small-R jet category for Gaussian-shaped signal with a relative width of 3%.

Distribution of exclusion upper limits on signal event yields at 95% CL from 1000 pseudo-experiments for Gaussian-shaped signals with relative width values of 3% at the low boundary of the limit-sensitive mass range for the ZX spectrum of the leading small-R jet category. The vertical line corresponds to the expected nominal exclusion limit at 95% CL.

Distribution of exclusion upper limits on signal event yields at 95% CL from 1000 pseudo-experiments for Gaussian-shaped signals with relative width values of 3% at the high boundary of the limit-sensitive mass range for the ZX spectrum of the leading small-R jet category. The vertical line corresponds to the expected nominal exclusion limit at 95% CL.

Distribution of exclusion upper limits on signal event yields at 95% CL from 1000 pseudo-experiments for Gaussian-shaped signals with relative width values of 5% at the low boundary of the limit-sensitive mass range for the ZX spectrum of the leading small-R jet category. The vertical line corresponds to the expected nominal exclusion limit at 95% CL.

Distribution of exclusion upper limits on signal event yields at 95% CL from 1000 pseudo-experiments for Gaussian-shaped signals with relative width values of 5% at the high boundary of the limit-sensitive mass range for the ZX spectrum of the leading small-R jet category. The vertical line corresponds to the expected nominal exclusion limit at 95% CL.

Distribution of exclusion upper limits on signal event yields at 95% CL from 1000 pseudo-experiments for Gaussian-shaped signals with relative width values of 10% at the low boundary of the limit-sensitive mass range for the ZX spectrum of the leading small-R jet category. The vertical line corresponds to the expected nominal exclusion limit at 95% CL.

Distribution of exclusion upper limits on signal event yields at 95% CL from 1000 pseudo-experiments for Gaussian-shaped signals with relative width values of 10% at the high boundary of the limit-sensitive mass range for the ZX spectrum of the leading small-R jet category. The vertical line corresponds to the expected nominal exclusion limit at 95% CL.

Data yields of the six event categories in the $Z\to e^+e^-$ and $\mu^+\mu^-$ decay channels. The merged-$e^+e^-$ events are included in the $e^+e^-$ channel, increasing the event yield, mainly in the leading large-$R$-jet category, by 0.6 %.

A list of mass spectra, event categories and their corresponding fit ranges, functional forms, numbers of free parameters and global $\chi^2$ $p$-values from background-only fits. The fit range values are rounded to the nearest 5 GeV. Here $f_1(x)=p_0\left(\mathrm{e}^{-p_1x}+p_2\mathrm{e}^{-(p_1+p_3)x}+p_4\mathrm{e}^{-(p_1+p_3+p_5)x}+\cdots\right)$ and $f_2(x)=p_0(1-x)^{p_1}x^{p_2+p_3\ln\!x+p_4\ln^2\!x+\cdots}$

A list of mass spectra, event categories and their corresponding signal-sensitive mass ranges. The initial BH $p$-value is obtained by using the background derived from the background-only fit in the full fit range, whereas the new BH $p$-value uses the background derived from the background-only fit in the range excluding the initial BH interval.

A list of mass spectra, event categories, relative width values of Gaussian-shaped signals and limit-sensitive mass ranges and fractions, corresponding to the mass values in the previous column, of pseudo-experiments having exclusion upper limits higher than the nominal exclusion limit at 95% CL

Cutflow of HVT model $A$ signals ($W^\prime \to ZW \to \ell\ell qq$) with $m_{W^\prime} = 1$ TeV and $m_{W^\prime} = 4$ TeV based on MC simulations.

Acceptance times efficiency ($\mathcal{A} \times \epsilon$) values in % in the dominant event category for $p^Z_{\mathrm{T}} > 100$ GeV in the $Z \to \ell^{+}\ell^{-}$ decay channel.