$\Delta\varphi$ projection of h-h correlation function with $3<p_{\mathrm{T}}^{\mathrm{trigg}}< 4 \mathrm{GeV}/c$ and $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

$\Delta\varphi$ projection of $K_S^0$-h correlation function with $3<p_{\mathrm{T}}^{\mathrm{trigg}}< 4 \mathrm{GeV}/c$ and $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

$\Delta\varphi$ projection of $K_S^0$-h correlation function with $3<p_{\mathrm{T}}^{\mathrm{trigg}}< 4 \mathrm{GeV}/c$ and $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

$\Delta\varphi$ projection of ($\Lambda+\overline{\Lambda}$)-h correlation function with $3<p_{\mathrm{T}}^{\mathrm{trigg}}< 4 \mathrm{GeV}/c$ and $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

$\Delta\varphi$ projection of ($\Lambda+\overline{\Lambda}$)-h correlation function with $3<p_{\mathrm{T}}^{\mathrm{trigg}}< 4 \mathrm{GeV}/c$ and $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

$\Delta\varphi$ projection of h-h correlation function with $9<p_{\mathrm{T}}^{\mathrm{trigg}}< 11 \mathrm{GeV}/c$ and $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

$\Delta\varphi$ projection of h-h correlation function with $9<p_{\mathrm{T}}^{\mathrm{trigg}}< 11 \mathrm{GeV}/c$ and $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

$\Delta\varphi$ projection of $K_S^0$-h correlation function with $9<p_{\mathrm{T}}^{\mathrm{trigg}}< 11 \mathrm{GeV}/c$ and $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

$\Delta\varphi$ projection of $K_S^0$-h correlation function with $9<p_{\mathrm{T}}^{\mathrm{trigg}}< 11 \mathrm{GeV}/c$ and $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

$\Delta\varphi$ projection of ($\Lambda+\overline{\Lambda}$)-h correlation function with $9<p_{\mathrm{T}}^{\mathrm{trigg}}< 11 \mathrm{GeV}/c$ and $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

$\Delta\varphi$ projection of ($\Lambda+\overline{\Lambda}$)-h correlation function with $9<p_{\mathrm{T}}^{\mathrm{trigg}}< 11 \mathrm{GeV}/c$ and $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

Per-trigger yields of h-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side with $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

Per-trigger yields of h-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side with $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

Per-trigger yields of $K_S^0$-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side with $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

Per-trigger yields of $K_S^0$-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side with $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

Per-trigger yields of ($\Lambda+\overline{\Lambda}$)-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side with $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

Per-trigger yields of ($\Lambda+\overline{\Lambda}$)-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side with $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

Per-trigger yields of h-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side with $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

Per-trigger yields of h-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side with $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

Per-trigger yields of $K_S^0$-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side with $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

Per-trigger yields of $K_S^0$-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side with $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

Per-trigger yields of ($\Lambda+\overline{\Lambda}$)-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side with $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

Per-trigger yields of ($\Lambda+\overline{\Lambda}$)-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side with $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

Ratio of the per-trigger yields in different multiplicity classes to the corresponding minimum bias yield for h-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side

Ratio of the per-trigger yields in different multiplicity classes to the corresponding minimum bias yield for h-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side

Ratio of the per-trigger yields in different multiplicity classes to the corresponding minimum bias yield for $K_S^0$-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side

Ratio of the per-trigger yields in different multiplicity classes to the corresponding minimum bias yield for $K_S^0$-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side

Ratio of the per-trigger yields in different multiplicity classes to the corresponding minimum bias yield for ($\Lambda+\overline{\Lambda}$)-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side

Ratio of the per-trigger yields in different multiplicity classes to the corresponding minimum bias yield for ($\Lambda+\overline{\Lambda}$)-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side

Ratio of the per-trigger yields in different multiplicity classes to the corresponding minimum bias yield for h-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side

Ratio of the per-trigger yields in different multiplicity classes to the corresponding minimum bias yield for h-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side

Ratio of the per-trigger yields in different multiplicity classes to the corresponding minimum bias yield for $K_S^0$-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side

Ratio of the per-trigger yields in different multiplicity classes to the corresponding minimum bias yield for $K_S^0$-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side

Ratio of the per-trigger yields in different multiplicity classes to the corresponding minimum bias yield for ($\Lambda+\overline{\Lambda}$)-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side

Ratio of the per-trigger yields in different multiplicity classes to the corresponding minimum bias yield for ($\Lambda+\overline{\Lambda}$)-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side

Per-trigger yields of h-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side from minimum bias

Per-trigger yields of h-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side from minimum bias

Per-trigger yields of $K_S^0$-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side from minimum bias

Per-trigger yields of $K_S^0$-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side from minimum bias

Per-trigger yields of ($\Lambda+\overline{\Lambda}$)-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side from minimum bias

Per-trigger yields of ($\Lambda+\overline{\Lambda}$)-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side from minimum bias

Per-trigger yields of h-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side from minimum bias

Per-trigger yields of h-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side from minimum bias

Per-trigger yields of $K_S^0$-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side from minimum bias

Per-trigger yields of $K_S^0$-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side from minimum bias

Per-trigger yields of ($\Lambda+\overline{\Lambda}$)-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side from minimum bias

Per-trigger yields of ($\Lambda+\overline{\Lambda}$)-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side from minimum bias

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for minimum bias

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for minimum bias

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 0-1% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 0-1% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 1-3% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 1-3% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 3-7% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 3-7% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 7-15% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 7-15% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 15-50% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 15-50% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 50-100% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 50-100% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for minimum bias

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for minimum bias

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 0-1% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 0-1% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 1-3% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 1-3% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 3-7% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 3-7% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 7-15% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 7-15% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 15-50% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 15-50% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 50-100% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 50-100% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for minimum bias

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for minimum bias

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 0-1% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 0-1% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 1-3% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 1-3% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 3-7% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 3-7% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 7-15% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 7-15% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 15-50% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 15-50% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 50-100% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 50-100% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for minimum bias

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for minimum bias

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 0-1% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 0-1% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 1-3% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 1-3% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 3-7% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 3-7% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 7-15% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 7-15% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 15-50% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 15-50% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 50-100% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 50-100% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $3 < p_{\mathrm{T}}^{\mathrm{trigg}} < 4 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $3 < p_{\mathrm{T}}^{\mathrm{trigg}} < 4 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $4 < p_{\mathrm{T}}^{\mathrm{trigg}} < 5 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $4 < p_{\mathrm{T}}^{\mathrm{trigg}} < 5 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $5 < p_{\mathrm{T}}^{\mathrm{trigg}} < 6 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $5 < p_{\mathrm{T}}^{\mathrm{trigg}} < 6 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $6 < p_{\mathrm{T}}^{\mathrm{trigg}} < 7 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $6 < p_{\mathrm{T}}^{\mathrm{trigg}} < 7 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $7 < p_{\mathrm{T}}^{\mathrm{trigg}} < 9 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $7 < p_{\mathrm{T}}^{\mathrm{trigg}} < 9 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $9 < p_{\mathrm{T}}^{\mathrm{trigg}} < 11 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $9 < p_{\mathrm{T}}^{\mathrm{trigg}} < 11 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $11 < p_{\mathrm{T}}^{\mathrm{trigg}} < 15 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $11 < p_{\mathrm{T}}^{\mathrm{trigg}} < 15 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $3 < p_{\mathrm{T}}^{\mathrm{trigg}} < 4 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $3 < p_{\mathrm{T}}^{\mathrm{trigg}} < 4 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $4 < p_{\mathrm{T}}^{\mathrm{trigg}} < 5 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $4 < p_{\mathrm{T}}^{\mathrm{trigg}} < 5 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $5 < p_{\mathrm{T}}^{\mathrm{trigg}} < 6 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $5 < p_{\mathrm{T}}^{\mathrm{trigg}} < 6 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $6 < p_{\mathrm{T}}^{\mathrm{trigg}} < 7 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $6 < p_{\mathrm{T}}^{\mathrm{trigg}} < 7 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $7 < p_{\mathrm{T}}^{\mathrm{trigg}} < 9 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $7 < p_{\mathrm{T}}^{\mathrm{trigg}} < 9 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $9 < p_{\mathrm{T}}^{\mathrm{trigg}} < 11 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $9 < p_{\mathrm{T}}^{\mathrm{trigg}} < 11 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $11 < p_{\mathrm{T}}^{\mathrm{trigg}} < 15 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $11 < p_{\mathrm{T}}^{\mathrm{trigg}} < 15 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $3 < p_{\mathrm{T}}^{\mathrm{trigg}} < 4 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $3 < p_{\mathrm{T}}^{\mathrm{trigg}} < 4 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $4 < p_{\mathrm{T}}^{\mathrm{trigg}} < 5 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $4 < p_{\mathrm{T}}^{\mathrm{trigg}} < 5 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $5 < p_{\mathrm{T}}^{\mathrm{trigg}} < 6 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $5 < p_{\mathrm{T}}^{\mathrm{trigg}} < 6 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $6 < p_{\mathrm{T}}^{\mathrm{trigg}} < 7 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $6 < p_{\mathrm{T}}^{\mathrm{trigg}} < 7 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $7 < p_{\mathrm{T}}^{\mathrm{trigg}} < 9 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $7 < p_{\mathrm{T}}^{\mathrm{trigg}} < 9 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $9 < p_{\mathrm{T}}^{\mathrm{trigg}} < 11 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $9 < p_{\mathrm{T}}^{\mathrm{trigg}} < 11 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $11 < p_{\mathrm{T}}^{\mathrm{trigg}} < 15 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $11 < p_{\mathrm{T}}^{\mathrm{trigg}} < 15 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $3 < p_{\mathrm{T}}^{\mathrm{trigg}} < 4 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $3 < p_{\mathrm{T}}^{\mathrm{trigg}} < 4 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $4 < p_{\mathrm{T}}^{\mathrm{trigg}} < 5 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $4 < p_{\mathrm{T}}^{\mathrm{trigg}} < 5 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $5 < p_{\mathrm{T}}^{\mathrm{trigg}} < 6 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $5 < p_{\mathrm{T}}^{\mathrm{trigg}} < 6 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $6 < p_{\mathrm{T}}^{\mathrm{trigg}} < 7 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $6 < p_{\mathrm{T}}^{\mathrm{trigg}} < 7 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $7 < p_{\mathrm{T}}^{\mathrm{trigg}} < 9 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $7 < p_{\mathrm{T}}^{\mathrm{trigg}} < 9 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $9 < p_{\mathrm{T}}^{\mathrm{trigg}} < 11 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $9 < p_{\mathrm{T}}^{\mathrm{trigg}} < 11 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $11 < p_{\mathrm{T}}^{\mathrm{trigg}} < 15 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $11 < p_{\mathrm{T}}^{\mathrm{trigg}} < 15 \mathrm{GeV}/c$

$\phi$ meson production cross section $\mathrm{d}^2\sigma/(\mathrm{d}y\mathrm{d}p_\mathrm{T})$ as a function of $p_\mathrm{T}$ at $\sqrt{s}=5.02$ TeV in pp collisions, in the $2.5<y<3$ rapidity interval.

$\phi$ meson production cross section $\mathrm{d}^2\sigma/(\mathrm{d}y\mathrm{d}p_\mathrm{T})$ as a function of $p_\mathrm{T}$ at $\sqrt{s}=5.02$ TeV in pp collisions, in the $3<y<3.25$ rapidity interval.

$\phi$ meson production cross section $\mathrm{d}^2\sigma/(\mathrm{d}y\mathrm{d}p_\mathrm{T})$ as a function of $p_\mathrm{T}$ at $\sqrt{s}=5.02$ TeV in pp collisions, in the $3.25<y<3.5$ rapidity interval.

$\phi$ meson production cross section $\mathrm{d}^2\sigma/(\mathrm{d}y\mathrm{d}p_\mathrm{T})$ as a function of $p_\mathrm{T}$ at $\sqrt{s}=5.02$ TeV in pp collisions, in the $3.5<y<4$ rapidity interval.

$\phi$ meson production cross section $\mathrm{d}^2\sigma/(\mathrm{d}y\mathrm{d}p_\mathrm{T})$ as a function of $p_\mathrm{T}$ at $\sqrt{s}=13$ TeV in pp collisions, in the $2.5<y<2.75$ rapidity interval.

$\phi$ meson production cross section $\mathrm{d}^2\sigma/(\mathrm{d}y\mathrm{d}p_\mathrm{T})$ as a function of $p_\mathrm{T}$ at $\sqrt{s}=13$ TeV in pp collisions, in the $2.75<y<3$ rapidity interval.

$\phi$ meson production cross section $\mathrm{d}^2\sigma/(\mathrm{d}y\mathrm{d}p_\mathrm{T})$ as a function of $p_\mathrm{T}$ at $\sqrt{s}=13$ TeV in pp collisions, in the $3<y<3.25$ rapidity interval.

$\phi$ meson production cross section $\mathrm{d}^2\sigma/(\mathrm{d}y\mathrm{d}p_\mathrm{T})$ as a function of $p_\mathrm{T}$ at $\sqrt{s}=13$ TeV in pp collisions, in the $3.25<y<3.5$ rapidity interval.

$\phi$ meson production cross section $\mathrm{d}^2\sigma/(\mathrm{d}y\mathrm{d}p_\mathrm{T})$ as a function of $p_\mathrm{T}$ at $\sqrt{s}=13$ TeV in pp collisions, in the $3.5<y<4$ rapidity interval.

$\phi$ meson production cross section $\mathrm{d}^2\sigma/(\mathrm{d}y\mathrm{d}p_\mathrm{T})$ as a function of rapidity at $\sqrt{s}=5.02$ TeV in pp collisions, in the $1<p_T<2$ GeV/$c$ interval.

$\phi$ meson production cross section $\mathrm{d}^2\sigma/(\mathrm{d}y\mathrm{d}p_\mathrm{T})$ as a function of rapidity at $\sqrt{s}=5.02$ TeV in pp collisions, in the $2<p_T<5$ GeV/$c$ interval.

$\phi$ meson production cross section $\mathrm{d}^2\sigma/(\mathrm{d}y\mathrm{d}p_\mathrm{T})$ as a function of rapidity at $\sqrt{s}=5.02$ TeV in pp collisions, in the $5<p_T<8$ GeV/$c$ interval.

$\phi$ meson production cross section $\mathrm{d}^2\sigma/(\mathrm{d}y\mathrm{d}p_\mathrm{T})$ as a function of rapidity at $\sqrt{s}=13$ TeV in pp collisions, in the $1<p_T<2$ GeV/$c$ interval.

$\phi$ meson production cross section $\mathrm{d}^2\sigma/(\mathrm{d}y\mathrm{d}p_\mathrm{T})$ as a function of rapidity at $\sqrt{s}=13$ TeV in pp collisions, in the $2<p_T<5$ GeV/$c$ interval.

$\phi$ meson production cross section $\mathrm{d}^2\sigma/(\mathrm{d}y\mathrm{d}p_\mathrm{T})$ as a function of rapidity at $\sqrt{s}=13$ TeV in pp collisions, in the $5<p_T<10$ GeV/$c$ interval.

$\phi$ meson production integrated cross section as a function of $\sqrt{s}$ for $1.5 < p_\mathrm{T} <5$ GeV/$c$ at forward rapidity in pp collisions.

Distribution of the MLP W+jets score in the CRs for the $T\overline{T}$ search. The observed data, predicted $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario, and the background are all shown. Statistical and systematic uncertainties in the background prediction before performing the fit to data are also shown.

Distribution of DeepAK8 jet tags in the DeepAK8 CR of the $T\overline{T}$ search. The observed data are shown using black markers, $T\overline{T}$ signals using solid lines, and background using filled histograms. Statistical and systematic uncertainties in the background prediction before performing the fit to data are shown by the hatched region.

Distribution of HT in the W+jets CR of the $T\overline{T}$ search. The observed data are shown using black markers, $T\overline{T}$ signals using solid lines, and background using filled histograms. Statistical and systematic uncertainties in the background prediction before performing the fit to data are shown by the hatched region.

Distribution of HT in the $T\overline{T}$ CR of the $T\overline{T}$ search. The observed data are shown using black markers, $T\overline{T}$ signals using solid lines, and background using filled histograms. Statistical and systematic uncertainties in the background prediction before performing the fit to data are shown by the hatched region.

Numbers of predicted and observed CR events in 2016--2018 data for the $T\overline{T}$ signal hypotheses in the single-lepton channel, after a background-only fit to data. Predicted numbers of signal events before the fit to data are included for comparison, using the singlet branching fraction scenario. Uncertainties include statistical and systematic components, and lepton flavor categories are combined with their uncertainties added in quadrature. Values in the DeepAK8 CR represent the number of large-radius jets rather than number of events.

Numbers of predicted and observed CR events in 2016--2018 data for the $B\overline{B}$ signal hypotheses in the single-lepton channel, after a background-only fit to data. Predicted numbers of signal events before the fit to data are included for comparison, using the singlet branching fraction scenario. Uncertainties include statistical and systematic components, and lepton flavor categories are combined with their uncertainties added in quadrature. Values in the DeepAK8 CR represent the number of large-radius jets rather than number of events.

Numbers of predicted and observed CR events in 2017--2018 data in the same-sign dilepton channel, after a background-only fit to data. Predicted numbers of signal events before the fit to data are included for comparison, using the singlet branching fraction scenario. Uncertainties include statistical and systematic components. Predictions for 2017 and 2018 are combined with their uncertainties added in quadrature.

Distribution of lepton $p_T$ in 2017 in the multilepton channel nonprompt lepton control region for all flavor categories, evaluated with the best-fit nonprompt rates. The uncertainty shown is the quadratic sum of statistical and systematics uncertainties.

Distribution of lepton $p_T$ in 2018 in the multilepton channel nonprompt lepton control region for all flavor categories, evaluated with the best-fit nonprompt rates. The uncertainty shown is the quadratic sum of statistical and systematics uncertainties.

Numbers of predicted and observed CR events in 2017--2018 data in the multilepton channel, after a background-only fit to data. Predicted numbers of signal events before the fit to data are included for comparison, using the singlet branching fraction scenario. Uncertainties include statistical and systematic components. Predictions for 2017 and 2018 are combined with their uncertainties added in quadrature.

Numbers of predicted and observed $T\overline{T}$ SR events in 2016--2018 data in the single-lepton channel, after a background-only fit to data. Predicted numbers of signal events before the fit to data are included for comparison, using the singlet branching fraction scenario. Uncertainties include statistical and systematic components, and lepton flavor categories are combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 1. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 2. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 3. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 4. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 5. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 6. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 7. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 8. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 9. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 10. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 11. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 12. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of $H_T^{\mathrm{lep}}$ in the same-sign dilepton signal region for $ee$ category. Data from 2017 and 2018 is shown using black markers, $T\overline{T}$ signals with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region.

Distribution of $H_T^{\mathrm{lep}}$ in the same-sign dilepton signal region for $e\mu$ category. Data from 2017 and 2018 is shown using black markers, $T\overline{T}$ signals with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region.

Distribution of $H_T^{\mathrm{lep}}$ in the same-sign dilepton signal region for $\mu\mu$ category. Data from 2017 and 2018 is shown using black markers, $T\overline{T}$ signals with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region.

Distribution of $S_T$ in the multilepton signal region for $eee$ category. Data from 2017 and 2018 is shown using black markers, $T\overline{T}$ signals with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region.

Distribution of $S_T$ in the multilepton signal region for $ee\mu$ category. Data from 2017 and 2018 is shown using black markers, $T\overline{T}$ signals with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region.

Distribution of $S_T$ in the multilepton signal region for $e\mu\mu$ category. Data from 2017 and 2018 is shown using black markers, $T\overline{T}$ signals with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region.

Distribution of $S_T$ in the multilepton signal region for $\mu\mu\mu$ category. Data from 2017 and 2018 is shown using black markers, $T\overline{T}$ signals with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region.

Numbers of predicted and observed $B\overline{B}$ SR events in 2016--2018 data in the single-lepton channel, after a background-only fit to data. Predicted numbers of signal events before the fit to data are included for comparison, using the singlet branching fraction scenario. Uncertainties include statistical and systematic components, and lepton flavor categories are combined with their uncertainties added in quadrature.

Numbers of predicted and observed SR events in 2017--2018 data in the same-sign dilepton channel, after a background-only fit to data. Predicted numbers of signal events before the fit to data are included for comparison, using the singlet branching fraction scenario. Uncertainties include statistical and systematic components. Predictions for 2017 and 2018 are combined with their uncertainties added in quadrature.

Numbers of predicted and observed SR events in 2017--2018 data in the multilepton channel, after a background-only fit to data. Predicted numbers of signal events before the fit to data are included for comparison, using the singlet branching fraction scenario. Uncertainties include statistical and systematic components. Predictions for 2017 and 2018 are combined with their uncertainties added in quadrature.

Expected and observed lower limits on the VLT quark masses.

Expected and observed lower limits on the VLB quark masses.

Expected 95% CL upper limits on $T\overline{T}$ production cross sections for the singlet combination.

Expected 95% CL upper limits on $T\overline{T}$ production cross sections for the doublet combination.

Expected 95% CL upper limits on $B\overline{B}$ production cross sections for the singlet combination.

Expected 95% CL upper limits on $B\overline{B}$ production cross sections for the doublet combination.

The 95% CL expected lower mass limits on pair-produced T quark masses as functions of their branching ratios to W and H bosons.

The 95% CL observed lower mass limits on pair-produced T quark masses as functions of their branching ratios to W and H bosons.

The 95% CL expected lower mass limits on pair-produced B quark masses as functions of their branching ratios to W and H bosons.

The 95% CL observed lower mass limits on pair-produced B quark masses as functions of their branching ratios to W and H bosons.

Final state radiation correction used in the $\phi_{\eta}^{*}$ cross-section measurement. The first uncertainty is statistical and the second is systematic.

Final state radiation correction used in the $y^{Z}-p_{T}^{Z}$ cross-section measurement. The first uncertainty is statistical and the second is systematic.

Final state radiation correction used in the $y^{Z}-\phi_{\eta}^{*}$ cross-section measurement. The first uncertainty is statistical and the second is systematic.

Correlation matrix of statistical uncertainty for one-dimensional $y^Z$ measurement.

Correlation matrix of statistical uncertainty for one-dimensional $p_{T}^{Z}$ measurement.

Correlation matrix of statistical uncertainty for one-dimensional $\phi_{\eta}^{*}$ measurement.

Correlation matrix of statistical uncertainty for two-dimensional $y^Z-p_{T}^{Z}$ measurement.

Correlation matrix of statistical uncertainty for two-dimensional $y^Z-\phi_{\eta}^{*}$ measurement.

Correlation matrix of efficiency uncertainty for one-dimensional $y^Z$ measurement.

Correlation matrix of efficiency uncertainty for one-dimensional $p_{T}^{Z}$ measurement.

Correlation matrix of efficiency uncertainty for one-dimensional $\phi_{\eta}^{*}$ measurement.

Correlation matrix of efficiency uncertainty for two-dimensional $y^Z-p_{T}^{Z}$ measurement.

Correlation matrix of efficiency uncertainty for two-dimensional $y^Z-\phi_{\eta}^{*}$ measurement.

Measured total $Z$-boson cross-section for different datasets. The first uncertainty is statistical, the second systematic, and the third is due to the luminosity.

Measured single differential cross-sections in interval regions of $y^{Z}$. The first uncertainty is statistical, the second systematic, and the third is due to the luminosity.

Measured single differential cross-sections in interval regions of $p_{T}^{Z}$. The first uncertainty is statistical, the second systematic, and the third is due to the luminosity.

Measured single differential cross-sections in interval regions of $\phi_{\eta}^{*}$. The first uncertainty is statistical, the second systematic, and the third is due to the luminosity.

Measured double differential cross-sections in interval regions of $y^{Z}$ and $p_{T}^{Z}$. The first uncertainty is statistical, the second systematic, and the third is due to the luminosity.

Measured double differential cross-sections in interval regions of $y^{Z}$ and $\phi_{\eta}^{*}$. The first uncertainty is statistical, the second systematic, and the third is due to the luminosity.

Systematic uncertainties in the single differential cross-sections in interval regions of $y^{Z}$, presented in percentage. The contributions from efficiency (Eff), background (BKG), final state radiation (FSR), closure test (Closure), and alignment and calibration (Alignment) are shown.

Systematic uncertainties in the single differential cross-sections in interval regions of $p_{T}^{Z}$, presented in percentage. The contributions from efficiency (Eff), background (BKG), final state radiation (FSR), closure test (Closure), and alignment and calibration (Alignment) are shown.

Systematic uncertainties in the single differential cross-sections in interval regions of $\phi_{\eta}^{*}$, presented in percentage. The contributions from efficiency (Eff), background (BKG), final state radiation (FSR), closure test (Closure), and alignment and calibration (Alignment) are shown.

Systematic uncertainties in the double differential cross-sections in interval regions of $y^{Z}$ and $p_{T}^{Z}$, presented in percentage. The contributions from efficiency (Eff), background (BKG), final state radiation (FSR), closure test (Closure), and alignment and calibration (Alignment) are shown.

Systematic uncertainties in the double differential cross-sections in interval regions of $y^{Z}$ and $\phi_{\eta}^{*}$, presented in percentage. The contributions from efficiency (Eff), background (BKG), final state radiation (FSR), closure test (Closure), and alignment and calibration (Alignment) are shown.

Bayesian upper exclusion limits on the ratio $g_{W'}/g_{W}$ for an SSM-like W$\prime$ boson are shown. The unity coupling ratio (blue dotted curve) corresponds to the SSM common benchmark. The 68 and 95% quantiles of the limits are represented by the green and yellow bands, respectively.

Bayesian lower exclusion limits on the NUGIM G(221) mixing angle $\cot(\theta_{E})$ are shown as a function of the W$\prime$ boson mass. The theoretically excluded region is shaded in grey. The 68 and 95% quantiles of the limits are represented by the green and yellow bands, respectively.

Bayesian upper exclusion limits at 95% CL on the product of the production cross section and branching fraction of a QBH in an associated $ au$ lepton and neutrino final state. Minimum threshold masses $m_{th}$ of up to 6.6 TeV are excluded at 95% CL. The observed limit (solid line) is obtained from the intersection with the LO QBH cross section (blue dotted curve). The 68 and 95% quantiles of the limits are represented by the green and yellow bands, respectively.

Bayesian upper limits at 95% CL on the cross section of the process $pp\rightarrow\tau\nu$ mediated via LQ exchange in the t-channel. The inner (green) band and the outer (yellow) band indicate the regions containing 68 and 95%, respectively, of the distribution of limits expected under the background-only hypothesis. The predicted LQ cross section at LO in the three coupling benchmark scenarios is depicted in different colors for $g_{U}=1$. The uncertainty bandy correspond to the sum in quadrature of PDF and scale variations. The first benchmark scenario considers only couplings to left-handed SM fermions (i.e. $\beta_{\text{R}}^{ij}=0$) and is referred to as "best fit LH". The second benchmark, referred to as "best fit LH+RH", considers $|\beta_{\text{R}}^{\text{b}\tau}|=1$ and all other $\beta_{\text{R}}^{ij}=0$. In the third "democratic" benchmark, equal couplings only to LH fermions are assumed, i.e. $\beta_{\text{L}}^{ij}=1$ and $\beta_{\text{R}}^{ij}=0$ for all $i$ and $j$.

Expected and observed lower limits of the LQ mass as a function of the coupling $g_{U}$ in the LH scenario. The blue band shows the 68% and 95% regions of $g_{U}$ preferred by the fit to the b anomalies data.

Expected and observed lower limits of the LQ mass as a function of the coupling $g_{U}$ in the LH+RH scenario. The blue band shows the 68% and 95% regions of $g_{U}$ preferred by the fit to the b anomalies data.

Expected and observed lower limits of the LQ mass as a function of the coupling $g_{U}$ in the democratic scenario. The blue band shows the 68% and 95% regions of $g_{U}$ preferred by the fit to the b anomalies data.

Bayesian upper exclusion limits at 95% CL on each of the Wilson coefficients described by the EFT model based on 2016-2018 data. The three different coupling types represent a left-handed vector coupling ($\epsilon^{cb}_{L}$), tensor-like coupling ($\epsilon^{cb}_{T}$), and scalar-tensor-like coupling ($\epsilon^{cb}_{S_{L}}$). The 68 and 95% quantiles of the limits are represented by the green and yellow bands, respectively.

Summary of exclusion limits (expected and observed) calculated at 95% CL for full Run-2 CMS data.

Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit and serve as input to the simplified likelihood reinterpretation scheme. The naming of the bins is "year_binnumber", following the binning from Figure 4.

Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit and serve as input to the simplified likelihood reinterpretation scheme. The naming of the bins is "year_binnumber", following the binning used in Figure 4.

Predicted signal yields for the 2017 data-taking period, corresponding to 41.3 fb$^{-1}$, after the application of each search requirement (cumulative) for various signal hypothesis. The requirements listed are presented as total efficiencies w.r.t. the previous selection step.

Upper limits on the production cross section times branching fraction of the b* RH hypothesis at a 95% CL. Dashed colored lines show the expected limits from the l+jets and all-hadronic channels, where the latter start at resonance masses of 1.4 TeV. The observed and expected limits from the combination are shown as solid and dashed black lines, respectively. The green and yellow bands show the 68 and 95% confidence intervals on the combined expected limits.

Upper limits on the production cross section times branching fraction of the b* VL hypothesis at a 95% CL. Dashed colored lines show the expected limits from the l+jets and all-hadronic channels, where the latter start at resonance masses of 1.4 TeV. The observed and expected limits from the combination are shown as solid and dashed black lines, respectively. The green and yellow bands show the 68 and 95% confidence intervals on the combined expected limits.

Upper limits on the production cross section times branching fraction of the B+b hypothesis at a 95% CL. Dashed colored lines show the expected limits from the l+jets and all-hadronic channels, where the latter start at resonance masses of 1.4 TeV. The observed and expected limits from the combination are shown as solid and dashed black lines, respectively. The green and yellow bands show the 68 and 95% confidence intervals on the combined expected limits.

Upper limits on the production cross section times branching fraction of the B+t hypothesis at a 95% CL. Dashed colored lines show the expected limits from the l+jets and all-hadronic channels, where the latter start at resonance masses of 1.4 TeV. The observed and expected limits from the combination are shown as solid and dashed black lines, respectively. The green and yellow bands show the 68 and 95% confidence intervals on the combined expected limits.

The observed and expected (in parentheses) 95% CL lower mass limits on RPV SUSY, Z′ ($\mathcal{B}=0.1$) , and QBH signals for the e$\mu$, e$\tau$, and $\mu\tau$ channels.

Expected and observed 95% CL upper limits on the product of cross section times branching fraction as a function of the $ au$ sneutrino mass in an RPV SUSY model for the e$\mu$ channel. The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits. The red and blue solid lines show the product of cross section times branching fraction as a function of the tau sneutrino mass for two different values of couplings.

Expected and observed 95% CL upper limits on the product of cross section times branching fraction as a function of the $ au$ sneutrino mass in an RPV SUSY model for the e$\tau$ channel. The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits. The red and blue solid lines show the product of cross section times branching fraction as a function of the tau sneutrino mass for two different values of couplings.

Expected and observed 95% CL upper limits on the product of cross section times branching fraction as a function of the $ au$ sneutrino mass in an RPV SUSY model for the $\mu\tau$ channel. The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits. The red and blue solid lines show the product of cross section times branching fraction as a function of the tau sneutrino mass for two different values of couplings.

Expected (black dashed line) and observed (black solid line) 95% CL upper limits on the product of cross section and branching fraction for a Z′ ($\mathcal{B}=0.1$) boson with LFV decays, in the e$\mu$ channel.The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits. The red solid lines show the product of cross section times branching fraction as a function of the Z′ mass.

Expected (black dashed line) and observed (black solid line) 95% CL upper limits on the product of cross section and branching fraction for a Z′ ($\mathcal{B}=0.1$) boson with LFV decays, in the e$\tau$ channel.The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits. The red solid lines show the product of cross section times branching fraction as a function of the Z′ mass.

Expected (black dashed line) and observed (black solid line) 95% CL upper limits on the product of cross section and branching fraction for a Z′ ($\mathcal{B}=0.1$) boson with LFV decays, in the $\mu\tau$ channel.The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits. The red solid lines show the product of cross section times branching fraction as a function of the Z′ mass.

Expected (black dashed line) and observed (black solid line) 95% CL upper limits on the product of cross section and branching fraction for quantum black hole production in an ADD model with $n=4$ extra dimensions, in the e$\mu$ channel. The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits. The red solid lines show the product of cross section times branching fraction as a function of the QBH threshold mass.

Expected (black dashed line) and observed (black solid line) 95% CL upper limits on the product of cross section and branching fraction for quantum black hole production in an ADD model with $n=4$ extra dimensions, in the e$\tau$ channel. The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits. The red solid lines show the product of cross section times branching fraction as a function of the QBH threshold mass.

Expected (black dashed line) and observed (black solid line) 95% CL upper limits on the product of cross section and branching fraction for quantum black hole production in an ADD model with $n=4$ extra dimensions, in the $\mu\tau$ channel. The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits. The red solid lines show the product of cross section times branching fraction as a function of the QBH threshold mass.

Upper limits at 95% CL on the RPV SUSY model in the plane of $\tau$ sneutrino mass and $\lambda'$ coupling, for four values of $\lambda$ couplings for the e$\mu$ channel. The regions to the left of and above the curves are excluded.

Upper limits at 95% CL on the RPV SUSY model in the plane of $\tau$ sneutrino mass and $\lambda'$ coupling, for four values of $\lambda$ couplings for the e$\tau$ channel. The regions to the left of and above the curves are excluded.

Upper limits at 95% CL on the RPV SUSY model in the plane of $\tau$ sneutrino mass and $\lambda'$ coupling, for four values of $\lambda$ couplings for the $\mu\tau$ channel. The regions to the left of and above the curves are excluded.

Model-independent upper limits at 95% CL on the product of cross section, branching fraction, and acceptance are shown. Observed (expected) limits are shown in black solid (dashed) lines for the e$\mu$ channel. The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits.

Model-independent upper limits at 95% CL on the product of cross section, branching fraction, and acceptance are shown. Observed (expected) limits are shown in black solid (dashed) lines for the e$\tau$ channel. The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits.

Model-independent upper limits at 95% CL on the product of cross section, branching fraction, and acceptance are shown. Observed (expected) limits are shown in black solid (dashed) lines for the $\mu\tau$ channel. The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits.

Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit and serve as input to the simplified likelihood reinterpretation scheme. The naming of the bins is "channel_year_binnumber", following the binning from Figure 2.

Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit and serve as input to the simplified likelihood reinterpretation scheme. The naming of the bins is "channel_year_binnumber", following the binning from Figure 2.

Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit and serve as input to the simplified likelihood reinterpretation scheme. The naming of the bins is "channel_year_binnumber", following the binning from Figure 2.

Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit and serve as input to the simplified likelihood reinterpretation scheme. The naming of the bins is "channel_year_binnumber", following the binning used in Figure 2.

Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit and serve as input to the simplified likelihood reinterpretation scheme. The naming of the bins is "channel_year_binnumber", following the binning used in Figure 2.

Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit and serve as input to the simplified likelihood reinterpretation scheme. The naming of the bins is "channel_year_binnumber", following the binning used in Figure 2.

Electron $p_{T}$ distribution using 2016-2018 data sets. The complete set of selection criteria were applied. Two examples of SSM WPRIME boson signal samples with masses of 3.8 and 5.6 TeV are shown. The lower panel shows the ratio of data to SM prediction, and the shaded band represents the systematic uncertainties.

$p_{T}^{miss}$ distribution in the electron channel using 2016-2018 data sets. The complete set of selection criteria were applied. Two examples of SSM WPRIME boson signal samples with masses of 3.8 and 5.6 TeV are shown. The lower panel shows the ratio of data to SM prediction, and the shaded band represents the systematic uncertainties.

Muon $p_T$ distribution using 2016-2018 data sets. The complete set of selection criteria were applied. Two examples of SSM WPRIME boson signal samples with masses of 3.8 and 5.6 TeV are shown. The lower panel shows the ratio of data to SM prediction, and the shaded band represents the systematic uncertainties.

$p_T^{miss}$ distribution in the muon channel using 2016-2018 data sets. The complete set of selection criteria were applied. Two examples of SSM WPRIME boson signal samples with masses of 3.8 and 5.6 TeV are shown. The lower panel shows the ratio of data to SM prediction, and the shaded band represents the systematic uncertainties.

$M_T$ distribution for the E+INVISIBLE system using 2016-2018 data sets. The complete set of selection criteria were applied. Two examples of SSM WPRIME boson signal samples with masses of 3.8 and 5.6 TeV are shown. The lower panel shows the ratio of data to SM prediction, and the shaded band represents the systematic uncertainties.

$M_T$ distribution for the MU+INVISIBLE system using 2016-2018 data sets. The complete set of selection criteria were applied. Two examples of SSM WPRIME boson signal samples with masses of 3.8 and 5.6 TeV are shown. The lower panel shows the ratio of data to SM prediction, and the shaded band represents the systematic uncertainties.

Theoretical prediction for the production and decay cross-section of SSM WPRIME bosons (W --> LEPTON + NU) as a function of the WPRIME mass, for the range 200-6400 GeV and inclusive in phase-space (no cuts). The uncertainty shown covers PDF and ALPHAS uncertainties. These theoretical predictions are obtained with PYTHIA (LO) and corrected to NNLO in QCD using FEWZ program.

Observed (solid line) and expected (dashed line) upper limits at 95% CL on the product of WPRIME cross-section production and BF(WPRIME --> LEPTON + NU) for an SSM WPRIME boson, as a function of the boson mass, for the electron decay channel. The shaded bands represent the one (green) and two (yellow) standard deviation uncertainty bands for the expected limits. The theoretical predictions for the SSM at NNLO precision in QCD are shown with narrow gray bands corresponding to the PDF and ALPHAS uncertainties.

Observed (solid line) and expected (dashed line) upper limits at 95% CL on the product of WPRIME cross-section production and BF(WPRIME --> LEPTON + NU) for an SSM WPRIME boson, as a function of the boson mass, for the muon decay channel. The shaded bands represent the one (green) and two (yellow) standard deviation uncertainty bands for the expected limits. The theoretical predictions for the SSM at NNLO precision in QCD are shown with narrow gray bands corresponding to the PDF and ALPHAS uncertainties.

Observed (solid line) and expected (dashed line) upper limits at 95% CL on the product of WPRIME cross-section production and BF(WPRIME --> LEPTON + NU) for an SSM WPRIME boson, as a function of the boson mass, for the combined electron and muon decay channels. The shaded bands represent the one (green) and two (yellow) standard deviation uncertainty bands for the expected limits. The theoretical predictions for the SSM at NNLO precision in QCD are shown with narrow gray bands corresponding to the PDF and ALPHAS uncertainties.

The 95% CL observed (solid line) and expected (dashed line) model independent cross section upper limits as function of the $MT_{min}$ threshold, for the electron decay channel. The shaded bands represent the one (green) and two (yellow) standard deviation uncertainty bands for the expected limits.

The 95% CL observed (solid line) and expected (dashed line) model independent cross section upper limits as function of the $MT_{min}$ threshold, for the muon decay channel. The shaded bands represent the one (green) and two (yellow) standard deviation uncertainty bands for the expected limits.

The 95% CL observed (solid line) and expected (dashed line) model independent cross section upper limits as function of the $MT_{min}$ threshold, for the combined electron and muon decay channels. The shaded bands represent the one (green) and two (yellow) standard deviation uncertainty bands for the expected limits.

Observed (solid line) and expected (dashed line) upper limits at 95% CL on the coupling strength ratio, gWprime/gW as a function of the mass of the WPRIME boson, for the electron channel. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The area above the limit curve is excluded. The dotted line represents the case of SSM coupling, gWprime, being equal to gW, the SM coupling.

Observed (solid line) and expected (dashed line) upper limits at 95% CL on the coupling strength ratio, gWprime/gW, as a function of the mass of the WPRIME boson, for the muon channel. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The area above the limit curve is excluded. The dotted line represents the case of SSM coupling, gWprime , being equal to gW, the SM coupling.

Exclusion limits in the 2D plane (1/R, $\mu$) for the split-UED interpretation for the n = 2 case, for the electron channel for the 2016-2018 data sets. R is the radius of the additional spatial dimension and $\mu$ the bulk mass for the fermion field in five dimensions. The expected limit is depicted as a black dashed line. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The experimentally excluded region is the entire area to the left of the solid black line.

Exclusion limits in the 2D plane (1/R, $\mu$) for the split-UED interpretation for the n = 2 case, for the muon channel for the 2016-2018 data sets. R is the radius of the additional spatial dimension and $\mu$ the bulk mass for the fermion field in five dimensions. The expected limit is depicted as a black dashed line. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The experimentally excluded region is the entire area to the left of the solid black line.

Exclusion limits in the 2D plane (1/R, $\mu$) for the split-UED interpretation for the n = 2 case, for the combined electron and muon channels for the 2016-2018 data sets. R is the radius of the additional spatial dimension and $\mu$ the bulk mass for the fermion field in five dimensions. The expected limit is depicted as a black dashed line. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The experimentally excluded region is the entire area to the left of the solid black line.

Observed (solid line) and expected (dashed line) upper limits at 95% CL on the ${\lambda}_{231}$ coupling in the RPV SUSY model with a STAU mediator, as a function of the mass of STAU, for the electron channel and for the production coupling, ${\lambda}^{'}_{3ij}$=0.5 . The couplings ${\lambda}^{'}_{3ij}$, ${\lambda}_{231}$, and ${\lambda}_{132}$ are defined in Fig. 1. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The area above the limit curve is excluded. Limits for other values of ${\lambda}^{'}_{3ij}$ are obtained multiplying the ones shown by the ratio ${\lambda}^{'}_{3ij}$/0.5

Observed (solid line) and expected (dashed line) upper limits at 95% CL on the ${\lambda}_{132}$ coupling in the RPV SUSY model with a stau mediator, as a function of the mass of the stau, for the muon channel and for the production coupling, ${\lambda}^{'}_{3ij}$ = 0.5 . The couplings ${\lambda}^{'}_{3ij}$, ${\lambda}_{231}$, and ${\lambda}_{132}$ are defined in Fig. 1. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The area above the limit curve is excluded. Limits for other values of ${\lambda}^{'}_{3ij}$ are obtained multiplying these ones by the ratio ${\lambda}^{'}_{3ij}$/0.5

Region in the oblique (W,Y) parameter phase space allowed by the current analysis at 95% CL. The combination of the electron and muon channel distributions from the 2017 and 2018 data sets at sqrt(s) = 13 TeV is used, having 101 fb-1 of luminosity.

Negative Log-Likelihood for the determination of the oblique W parameter, for the combination of the electron and muon channel and for 2017 and 2018 data sets (L=101 fb-1) at sqrt(s) = 13 TeV.

Total background estimate and observed data in all bins used in the limit calculation for the SSM WPRIME limits. The total event sample is split into the three years of data taking and the two lepton flavors.The distributions being shown are $M_T$ ones. The associated integrated luminosities for each year are of 35.9, 41.5, and 59.4 fb$̣^{-1}. The mass bins are numbered in ascending order.

Differential signal yields for various signal hypotheses.

Differential signal yields for various signal hypotheses.

Differential signal yields for various signal hypotheses.

Differential signal yields for various signal hypotheses.

Differential signal yields for various signal hypotheses.

Differential signal yields for various signal hypotheses.

Differential signal yields for various signal hypotheses.

Differential signal yields for various signal hypotheses.

Differential signal yields for various signal hypotheses.

Differential signal yields for various signal hypotheses.

Differential signal yields for various signal hypotheses.

Differential signal yields for various signal hypotheses.

Differential signal yields for various signal hypotheses.

Background and data yields in the control and signal region bins. The prediction before ("prefit") and after the background only fit ("b-only") are given separately.

Background and data yields in the control and signal region bins. The prediction before ("prefit") and after the background only fit ("b-only") are given separately.

Background and data yields in the control and signal region bins. The prediction before ("prefit") and after the background only fit ("b-only") are given separately.

Background and data yields in the control and signal region bins. The prediction before ("prefit") and after the background only fit ("b-only") are given separately.

Background and data yields in the control and signal region bins. The prediction before ("prefit") and after the background only fit ("b-only") are given separately.

Background and data yields in the control and signal region bins. The prediction before ("prefit") and after the background only fit ("b-only") are given separately.

Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit to the control regions, and serve as input to the simplified likelihood reinterpretation scheme.

Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit to the control regions, and serve as input to the simplified likelihood reinterpretation scheme.

Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit to the corresponding control regions, and serve as input to the simplified likelihood reinterpretation scheme.

Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit to the corresponding control regions, and serve as input to the simplified likelihood reinterpretation scheme.

Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit to the control regions, and serve as input to the simplified likelihood reinterpretation scheme.

Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit to the control regions, and serve as input to the simplified likelihood reinterpretation scheme.

Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit to the corresponding control regions, and serve as input to the simplified likelihood reinterpretation scheme.

Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit to the corresponding control regions, and serve as input to the simplified likelihood reinterpretation scheme.

Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit to the control regions, and serve as input to the simplified likelihood reinterpretation scheme.

Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit to the control regions, and serve as input to the simplified likelihood reinterpretation scheme.

Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit to the corresponding control regions, and serve as input to the simplified likelihood reinterpretation scheme.

Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit to the corresponding control regions, and serve as input to the simplified likelihood reinterpretation scheme.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Median Expected exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.

Median Expected exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.

Observed exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.

Observed exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.

Expected plus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.

Expected plus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.

Expected minus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.

Expected minus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.

Median Expected exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.

Median Expected exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.

Observed exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.

Observed exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.

Expected plus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.

Expected plus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.

Expected minus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.

Expected minus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.

Upper limits on the coupling $g_{\chi}$ in the simplified model with a axial mediator.

Upper limits on the coupling $g_{\chi}$ in the simplified model with a axial mediator.

Upper limits on the coupling $g_{q}$ in the simplified model with a axial mediator.

Upper limits on the coupling $g_{q}$ in the simplified model with a axial mediator.

Upper limits on the coupling $g_{\chi}$ in the simplified model with a vector mediator.

Upper limits on the coupling $g_{\chi}$ in the simplified model with a vector mediator.

Upper limits on the coupling $g_{q}$ in the simplified model with a vector mediator.

Upper limits on the coupling $g_{q}$ in the simplified model with a vector mediator.

Exclusion limits on the signal strength in the simplified model with scalar couplings.

Exclusion limits on the signal strength in the simplified model with scalar couplings.

Exclusion limits on the signal strength in the simplified model with pseudoscalar couplings.

Exclusion limits on the signal strength in the simplified model with pseudoscalar couplings.

Exclusion limits on the fundamental Planck scale $M_{D}$ as a function of the number of extra dimensions $d$.

Exclusion limits on the fundamental Planck scale $M_{D}$ as a function of the number of extra dimensions $d$.

Median Expected exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.

Median Expected exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.

Observed exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.

Observed exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.

Expected plus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.

Expected plus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.

Expected minus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.

Expected minus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.

Tagging efficiency for AK8 jets. The efficiency includes the effect of the machine-learning based DeepAK8 tagger, as well as the application of the mass window requirement on the jet. The efficiency is split depending on the matching generator-level object. For reinterpretation purposes, this efficiency can directly be applied to any AK8 jet that is matched to a given type of generator-level object, with no prior selection on the jet mass. Other acceptance requirements on jet $\p_{T}$ and $\eta$ should still be applied.

Tagging efficiency for AK8 jets. The efficiency includes the effect of the machine-learning based DeepAK8 tagger, as well as the application of the mass window requirement on the jet. The efficiency is split depending on the matching generator-level object. For reinterpretation purposes, this efficiency can directly be applied to any AK8 jet that is matched to a given type of generator-level object, with no prior selection on the jet mass. Other acceptance requirements on jet $\p_{T}$ and $\eta$ should still be applied.

Measured cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $1.56<|\eta^{\gamma}|<1.81$ and photon isolation cone radius $R=0.4$.

Measured cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $1.81<|\eta^{\gamma}|<2.01$ and photon isolation cone radius $R=0.4$.

Measured cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $2.01<|\eta^{\gamma}|<2.37$ and photon isolation cone radius $R=0.4$.

Measured cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $|\eta^{\gamma}|<0.6$ and photon isolation cone radius $R=0.2$.

Measured cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $0.6<|\eta^{\gamma}|<0.8$ and photon isolation cone radius $R=0.2$.

Measured cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $0.8<|\eta^{\gamma}|<1.37$ and photon isolation cone radius $R=0.2$.

Measured cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $1.56<|\eta^{\gamma}|<1.81$ and photon isolation cone radius $R=0.2$.

Measured cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $1.81<|\eta^{\gamma}|<2.01$ and photon isolation cone radius $R=0.2$.

Measured cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $2.01<|\eta^{\gamma}|<2.37$ and photon isolation cone radius $R=0.2$.

Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $|\eta^{\gamma}|<0.6$ and isolation cone radius $0.4$ at NNLO QCD.

Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $0.6<|\eta^{\gamma}|<0.8$ and isolation cone radius $0.4$ at NNLO QCD.

Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $0.8<|\eta^{\gamma}|<1.37$ and isolation cone radius $0.4$ at NNLO QCD.

Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $1.56<|\eta^{\gamma}|<1.81$ and isolation cone radius $0.4$ at NNLO QCD.

Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $1.81<|\eta^{\gamma}|<2.01$ and isolation cone radius $0.4$ at NNLO QCD.

Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $2.01<|\eta^{\gamma}|<2.37$ and isolation cone radius $0.4$ at NNLO QCD.

Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $|\eta^{\gamma}|<0.6$ and isolation cone radius $0.2$ at NNLO QCD.

Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $0.6<|\eta^{\gamma}|<0.8$ and isolation cone radius $0.2$ at NNLO QCD.

Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $0.8<|\eta^{\gamma}|<1.37$ and isolation cone radius $0.2$ at NNLO QCD.

Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $1.56<|\eta^{\gamma}|<1.81$ and isolation cone radius $0.2$ at NNLO QCD.

Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $1.81<|\eta^{\gamma}|<2.01$ and isolation cone radius $0.2$ at NNLO QCD.

Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $2.01<|\eta^{\gamma}|<2.37$ and isolation cone radius $0.2$ at NNLO QCD.

Measured ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $|\eta^{\gamma}|<0.6$.

Measured ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $0.6<|\eta^{\gamma}|<0.8$.

Measured ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $0.8<|\eta^{\gamma}|<1.37$.

Measured ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $1.56<|\eta^{\gamma}|<1.81$.

Measured ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $1.81<|\eta^{\gamma}|<2.01$.

Measured ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $2.01<|\eta^{\gamma}|<2.37$.

Predicted ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $|\eta^{\gamma}|<0.6$ at NNLO QCD.

Predicted ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $0.6<|\eta^{\gamma}|<0.8$ at NNLO QCD.

Predicted ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $0.8<|\eta^{\gamma}|<1.37$ at NNLO QCD.

Predicted ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $1.56<|\eta^{\gamma}|<1.81$ at NNLO QCD.

Predicted ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $1.81<|\eta^{\gamma}|<2.01$ at NNLO QCD.

Predicted ratio of the differential cross sections for inclusive isolated-photon production for $R=0.2$ and $R=0.4$ as a function of $E_{\rm T}^{\gamma}$ for $2.01<|\eta^{\gamma}|<2.37$ at NNLO QCD.

Measured fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $|\eta^{\gamma}|<0.6$.

Measured fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $0.6<|\eta^{\gamma}|<0.8$.

Measured fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $0.8<|\eta^{\gamma}|<1.37$.

Measured fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $1.56<|\eta^{\gamma}|<1.81$.

Measured fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $1.81<|\eta^{\gamma}|<2.01$.

Measured fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $2.01<|\eta^{\gamma}|<2.37$.

Predicted fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $|\eta^{\gamma}|<0.6$ at NNLO QCD.

Predicted fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $0.6<|\eta^{\gamma}|<0.8$ at NNLO QCD.

Predicted fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $0.8<|\eta^{\gamma}|<1.37$ at NNLO QCD.

Predicted fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $1.56<|\eta^{\gamma}|<1.81$ at NNLO QCD.

Predicted fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $1.81<|\eta^{\gamma}|<2.01$ at NNLO QCD.

Predicted fiducial integrated cross section for inclusive isolated-photon production as a function of $R$ for $2.01<|\eta^{\gamma}|<2.37$ at NNLO QCD.