Observed (points with error bars) and expected background (solid histograms) distributions for $E_{T}^{miss}$ in the signal region (a) SRL, (b) SRM and (c) SRH after the background-only fit applied to the CRs. The predicted signal distributions for the two models with a gluino mass of 2000 GeV and neutralino mass of 250 GeV (SRL), 1050 GeV (SRM) or 1950 GeV (SRH) are also shown for comparison. The uncertainties in the SM background are only statistical.

Observed and expected exclusion limit in the gluino-neutralino mass plane at 95% CL combined using the signal region with the best expected sensitivity at each point, for the full Run-2 dataset corresponding to an integrated luminosity of $139~\mathrm{fb}^{-1}$, for $\gamma/Z$ (a) and $\gamma/h$ (b) signal models. The black solid line corresponds to the expected limits at 95% CL, with the light (yellow) bands indicating the 1$\sigma$ exclusions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves, the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties. For each point in the higgsino-bino parameter space, the labels indicate the best-expected signal region, where L, M and H mean SRL, SRM and SRH, respectively.

Observed and expected exclusion limit in the gluino-neutralino mass plane at 95% CL combined using the signal region with the best expected sensitivity at each point, for the full Run-2 dataset corresponding to an integrated luminosity of $139~\mathrm{fb}^{-1}$, for $\gamma/Z$ (a) and $\gamma/h$ (b) signal models. The black solid line corresponds to the expected limits at 95% CL, with the light (yellow) bands indicating the 1$\sigma$ exclusions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves, the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties. For each point in the higgsino-bino parameter space, the labels indicate the best-expected signal region, where L, M and H mean SRL, SRM and SRH, respectively.

Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Cutflow for the SRL selection, for two relevant signal points for both $\gamma/Z$ and $\gamma/h$ models, where the gluinos have mass of 2000 GeV and the neutralinos have a mass of 250 GeV (10000 generated events). The numbers are normalized to a luminosity of 139 $fb^{-1}$.

Cutflow for the SRM selection, for two relevant signal points for both $\gamma/Z$ and $\gamma/h$ models, where the gluinos have mass of 2000 GeV and the neutralinos have a mass of 1050 GeV (10000 generated events). The numbers are normalized to a luminosity of 139 $fb^{-1}$.

Cutflow for the SRH selection, for two relevant signal points for both $\gamma/Z$ and $\gamma/h$ models, where the gluinos have mass of 2000 GeV and the neutralinos have a mass of 1950 GeV (10000 generated events). The numbers are normalized to a luminosity of 139 $fb^{-1}$.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Measured p-p-p three-particle correlation function. The average transverse mass of the p-p pairs in the triplets at $Q_3 < 0.8$ GeV/$c$ is 1.27 GeV/$c^2$.

Measured p-p-$\Lambda$ three-particle correlation function. The average transverse mass of the p-p (p-$\Lambda$) pairs in the triplets at $Q_3 < 0.8$ GeV/$c$ is 1.30 (1.43) GeV/$c^2$.

p-p-p cumulant

p-p-$\mathrm{\overline{p}}$ cumulant

p-p-$\Lambda$ cumulant

Measured p-p-$\mathrm{\overline{p}}$ three-particle correlation function

The (p-p)-$\mathrm{\overline{p}}$ correlation function obtained using the data-driven approach

The p-(p-$\mathrm{\overline{p}}$) correlation function obtained using the data-driven approach

The per-jet charged particle yield in pPb and pp collisions for hadrons opposite to a $p_{T}^{\textrm{jet}} > 60~\textrm{GeV}$ jet ($\Delta\phi_{\textrm{ch,jet}} > 7\pi/8$).

The ratio of per-jet charged particle yields in pPb and pp collisions, $I_{pPb}$, for hadrons near a $p_{T}^{\textrm{jet}} > 30~\textrm{GeV}$ jet ($\Delta\phi_{\textrm{ch,jet}} < \pi/8$).

The ratio of per-jet charged particle yields in pPb and pp collisions, $I_{pPb}$, for hadrons opposite to a $p_{T}^{\textrm{jet}} > 30~\textrm{GeV}$ jet ($\Delta\phi_{\textrm{ch,jet}} > 7\pi/8$).

The ratio of per-jet charged particle yields in pPb and pp collisions, $I_{pPb}$, for hadrons near a $p_{T}^{\textrm{jet}} > 60~\textrm{GeV}$ jet ($\Delta\phi_{\textrm{ch,jet}} < \pi/8$).

The ratio of per-jet charged particle yields in pPb and pp collisions, $I_{pPb}$, for hadrons opposite to a $p_{T}^{\textrm{jet}} > 60~\textrm{GeV}$ jet ($\Delta\phi_{\textrm{ch,jet}} > 7\pi/8$).

K$^+$p (K$^+$p $\oplus$ K$^-\overline{\mathrm p}$) correlation function in p-Pb collisions at $\sqrt{s_{\mathrm{NN}}} = 5.02$ TeV (40-100%).

K$^+$p (K$^+$p $\oplus$ K$^-\overline{\mathrm p}$) correlation function in Pb-Pb collisions at $\sqrt{s_{\mathrm{NN}}} = 5.02$ TeV (60-70%).

K$^+$p (K$^+$p $\oplus$ K$^-\overline{\mathrm p}$) correlation function in Pb-Pb collisions at $\sqrt{s_{\mathrm{NN}}} = 5.02$ TeV (70-80%).

K$^+$p (K$^+$p $\oplus$ K$^-\overline{\mathrm p}$) correlation function in Pb-Pb collisions at $\sqrt{s_{\mathrm{NN}}} = 5.02$ TeV (80-90%).

K$^-$p (K$^-$p $\oplus$ K$^+\overline{\mathrm p}$) correlation function in pp collisions at $\sqrt{s}=13$ TeV.

K$^-$p (K$^-$p $\oplus$ K$^+\overline{\mathrm p}$) correlation function in p-Pb collisions at $\sqrt{s_{\mathrm{NN}}} = 5.02$ TeV (0-20%).

K$^-$p (K$^-$p $\oplus$ K$^+\overline{\mathrm p}$) correlation function in p-Pb collisions at $\sqrt{s_{\mathrm{NN}}} = 5.02$ TeV (20-40%).

K$^-$p (K$^-$p $\oplus$ K$^+\overline{\mathrm p}$) correlation function in p-Pb collisions at $\sqrt{s_{\mathrm{NN}}} = 5.02$ TeV (40-100%).

K$^-$p (K$^-$p $\oplus$ K$^+\overline{\mathrm p}$) correlation function in Pb-Pb collisions at $\sqrt{s_{\mathrm{NN}}} = 5.02$ TeV (60-70%).

K$^-$p (K$^-$p $\oplus$ K$^+\overline{\mathrm p}$) correlation function in Pb-Pb collisions at $\sqrt{s_{\mathrm{NN}}} = 5.02$ TeV (70-80%).

K$^-$p (K$^-$p $\oplus$ K$^+\overline{\mathrm p}$) correlation function in Pb-Pb collisions at $\sqrt{s_{\mathrm{NN}}} = 5.02$ TeV (80-90%).

Scaling factor ($\alpha_j $) for $\mathrm{\overline{K}^0 n}$ extracted from the different fits of the K$^-$ p correlation function as a function of the core radius $r_{\mathrm{core}}$.

Scaling factor ($\alpha_j $) for $\pi \Sigma$ extracted from the different fits of the K$^-$ p correlation function as a function of the core radius $r_{\mathrm{core}}$.

This table shows the correlation coefficient between the $\alpha_{\mathrm{\overline{K}^0 n}}$ and $\alpha_{\pi \Sigma}$ parameters extracted from the different fits to the K$^-$ p correlation function with free weights. The results are shown as a function of the core radius $r_{\mathrm{core}}$ shown in Table 7. The error on the correlation coefficient, shown as statistical errors in the table, are obteined by using the Pearson's formula to evaluate the probable error of correlation coefficient.

Inclusive jet asymmetries, $A_{UT}^{\sin(\phi_{S})}$, as a function of particle jet-$p_{T}$. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S})}$ (vertical) and jet-$p_{T}$ (horizontal). The top panel shows results for jets that scatter forward relative to the polarized beam ($x_{F} > 0$).

Inclusive jet asymmetries, $A_{UT}^{\sin(\phi_{S})}$, as a function of particle jet-$p_{T}$. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S})}$ (vertical) and jet-$p_{T}$ (horizontal). the bottom panel shows jets that scatter backward to the polarized beam ($x_{F} < 0$).

Inclusive jet asymmetries, $A_{UT}^{\sin(\phi_{S})}$, as a function of particle jet-$p_{T}$ for jets that contain a charged pion with $z > 0.3$. The blue circles are for jets containing a high-$z$ $\pi^{+}$, while red squares are for jets containing a high-$z$ $\pi^{-}$.

Inclusive jet asymmetries, $A_{UT}^{\sin(\phi_{S})}$, as a function of particle jet-$p_{T}$ for jets that contain a charged pion with $z > 0.3$. The blue circles are for jets containing a high-$z$ $\pi^{+}$, while red squares are for jets containing a high-$z$ $\pi^{-}$.

Collins-like asymmetries, $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$, as a function of particle jet-$p_{T}$. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$ (vertical) and jet-$p_{T}$ (horizontal). The top panel shows results for jets that scatter forward relative to the polarized beam ($x_{F} > 0$).

Collins-like asymmetries, $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$, as a function of particle jet-$p_{T}$. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$ (vertical) and jet-$p_{T}$ (horizontal). The top panel shows results for jets that scatter forward relative to the polarized beam ($x_{F} > 0$).

Collins-like asymmetries, $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$, as a function of particle jet-$p_{T}$. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$ (vertical) and jet-$p_{T}$ (horizontal). The bottom panel shows jets that scatter backward with respect to the polarized beam ($x_{F} < 0$).

Collins-like asymmetries, $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$, as a function of particle jet-$p_{T}$. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$ (vertical) and jet-$p_{T}$ (horizontal). The bottom panel shows jets that scatter backward with respect to the polarized beam ($x_{F} < 0$).

Collins-like asymmetries, $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins-like asymmetries, $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins-like asymmetries, $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins-like asymmetries, $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins-like asymmetries, $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins-like asymmetries, $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins-like asymmetries, $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins-like asymmetries, $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins-like asymmetries, $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins-like asymmetries, $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins-like asymmetries, $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins-like asymmetries, $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-2\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of particle jet-$p_{T}$ separately for the 2012 and 2015 data. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and jet-$p_{T}$ (horizontal). The top panel shows the results for jets that scatter forward relative to the polarized beam ($x_{F} > 0$), while the bottom panel shows jets that scatter backward to the polarized beam ($x_{F} < 0$).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of particle jet-$p_{T}$ separately for the 2012 and 2015 data. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and jet-$p_{T}$ (horizontal). The top panel shows the results for jets that scatter forward relative to the polarized beam ($x_{F} > 0$), while the bottom panel shows jets that scatter backward to the polarized beam ($x_{F} < 0$).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of particle jet-$p_{T}$ separately for the 2012 and 2015 data. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and jet-$p_{T}$ (horizontal). The top panel shows the results for jets that scatter forward relative to the polarized beam ($x_{F} > 0$), while the bottom panel shows jets that scatter backward to the polarized beam ($x_{F} < 0$).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of particle jet-$p_{T}$ separately for the 2012 and 2015 data. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and jet-$p_{T}$ (horizontal). The top panel shows the results for jets that scatter forward relative to the polarized beam ($x_{F} > 0$), while the bottom panel shows jets that scatter backward to the polarized beam ($x_{F} < 0$).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of particle jet-$p_{T}$ separately for the 2012 and 2015 data. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and jet-$p_{T}$ (horizontal). The top panel shows the results for jets that scatter forward relative to the polarized beam ($x_{F} > 0$), while the bottom panel shows jets that scatter backward to the polarized beam ($x_{F} < 0$).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of particle jet-$p_{T}$ separately for the 2012 and 2015 data. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and jet-$p_{T}$ (horizontal). The top panel shows the results for jets that scatter forward relative to the polarized beam ($x_{F} > 0$), while the bottom panel shows jets that scatter backward to the polarized beam ($x_{F} < 0$).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of particle jet-$p_{T}$ separately for the 2012 and 2015 data. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and jet-$p_{T}$ (horizontal). The top panel shows the results for jets that scatter forward relative to the polarized beam ($x_{F} > 0$), while the bottom panel shows jets that scatter backward to the polarized beam ($x_{F} < 0$).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of particle jet-$p_{T}$ separately for the 2012 and 2015 data. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and jet-$p_{T}$ (horizontal). The top panel shows the results for jets that scatter forward relative to the polarized beam ($x_{F} > 0$), while the bottom panel shows jets that scatter backward to the polarized beam ($x_{F} < 0$).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of particle jet-$p_{T}$. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and jet-$p_{T}$ (horizontal). The top panel shows the results for jets that scatter forward relative to the polarized beam ($x_{F} > 0$), while the bottom panel shows jets that scatter backward to the polarized beam ($x_{F} < 0$).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of particle jet-$p_{T}$. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and jet-$p_{T}$ (horizontal). The top panel shows the results for jets that scatter forward relative to the polarized beam ($x_{F} > 0$), while the bottom panel shows jets that scatter backward to the polarized beam ($x_{F} < 0$).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of particle jet-$p_{T}$. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and jet-$p_{T}$ (horizontal). The top panel shows the results for jets that scatter forward relative to the polarized beam ($x_{F} > 0$), while the bottom panel shows jets that scatter backward to the polarized beam ($x_{F} < 0$).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of particle jet-$p_{T}$. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and jet-$p_{T}$ (horizontal). The top panel shows the results for jets that scatter forward relative to the polarized beam ($x_{F} > 0$), while the bottom panel shows jets that scatter backward to the polarized beam ($x_{F} < 0$).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different hadron longitudinal momentum fraction $z$ bins, integrated over detector jet-$p_T > 9.9$ GeV/$c$. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different hadron longitudinal momentum fraction $z$ bins, integrated over detector jet-$p_T > 9.9$ GeV/$c$. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different hadron longitudinal momentum fraction $z$ bins, integrated over detector jet-$p_T > 9.9$ GeV/$c$. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different hadron longitudinal momentum fraction $z$ bins, integrated over detector jet-$p_T > 9.9$ GeV/$c$. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different hadron longitudinal momentum fraction $z$ bins, integrated over detector jet-$p_T > 9.9$ GeV/$c$. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different hadron longitudinal momentum fraction $z$ bins, integrated over detector jet-$p_T > 9.9$ GeV/$c$. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different hadron longitudinal momentum fraction $z$ bins, integrated over detector jet-$p_T > 9.9$ GeV/$c$. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different hadron longitudinal momentum fraction $z$ bins, integrated over detector jet-$p_T > 9.9$ GeV/$c$. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of particle jet $x_{T}~(= 2 p_T/\sqrt{s}$). The solid points show the results from this analysis of $\sqrt{s} = 200$ GeV $pp$ collisions, while the open points show previous STAR results for $\sqrt{s} = 500$ GeV $pp$ collisions from data recorded during 2011.

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of particle jet $x_{T}~(= 2 p_T/\sqrt{s}$). The solid points show the results from this analysis of $\sqrt{s} = 200$ GeV $pp$ collisions, while the open points show previous STAR results for $\sqrt{s} = 500$ GeV $pp$ collisions from data recorded during 2011.

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of particle jet $x_{T}~(= 2 p_T/\sqrt{s}$). The solid points show the results from this analysis of $\sqrt{s} = 200$ GeV $pp$ collisions, while the open points show previous STAR results for $\sqrt{s} = 500$ GeV $pp$ collisions from data recorded during 2011.

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of particle jet $x_{T}~(= 2 p_T/\sqrt{s}$). The solid points show the results from this analysis of $\sqrt{s} = 200$ GeV $pp$ collisions, while the open points show previous STAR results for $\sqrt{s} = 500$ GeV $pp$ collisions from data recorded during 2011.

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion momentum transverse to the jet axis, $j_{T}$, in different hadron longitudinal momentum fraction $z$ bins. The solid points show the results from this analysis of $\sqrt{s} = 200$ GeV $pp$ collisions, while the open points show previous STAR results for $\sqrt{s} = 500$ GeV $pp$ collisions from data recorded during 2011.

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion momentum transverse to the jet axis, $j_{T}$, in different hadron longitudinal momentum fraction $z$ bins. The solid points show the results from this analysis of $\sqrt{s} = 200$ GeV $pp$ collisions, while the open points show previous STAR results for $\sqrt{s} = 500$ GeV $pp$ collisions from data recorded during 2011.

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion momentum transverse to the jet axis, $j_{T}$, in different hadron longitudinal momentum fraction $z$ bins. The solid points show the results from this analysis of $\sqrt{s} = 200$ GeV $pp$ collisions, while the open points show previous STAR results for $\sqrt{s} = 500$ GeV $pp$ collisions from data recorded during 2011.

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion momentum transverse to the jet axis, $j_{T}$, in different hadron longitudinal momentum fraction $z$ bins. The solid points show the results from this analysis of $\sqrt{s} = 200$ GeV $pp$ collisions, while the open points show previous STAR results for $\sqrt{s} = 500$ GeV $pp$ collisions from data recorded during 2011.

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion momentum transverse to the jet axis, $j_{T}$, in different hadron longitudinal momentum fraction $z$ bins. The solid points show the results from this analysis of $\sqrt{s} = 200$ GeV $pp$ collisions, while the open points show previous STAR results for $\sqrt{s} = 500$ GeV $pp$ collisions from data recorded during 2011.

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion momentum transverse to the jet axis, $j_{T}$, in different hadron longitudinal momentum fraction $z$ bins. The solid points show the results from this analysis of $\sqrt{s} = 200$ GeV $pp$ collisions, while the open points show previous STAR results for $\sqrt{s} = 500$ GeV $pp$ collisions from data recorded during 2011.

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion momentum transverse to the jet axis, $j_{T}$, in different hadron longitudinal momentum fraction $z$ bins. The solid points show the results from this analysis of $\sqrt{s} = 200$ GeV $pp$ collisions, while the open points show previous STAR results for $\sqrt{s} = 500$ GeV $pp$ collisions from data recorded during 2011.

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion momentum transverse to the jet axis, $j_{T}$, in different hadron longitudinal momentum fraction $z$ bins. The solid points show the results from this analysis of $\sqrt{s} = 200$ GeV $pp$ collisions, while the open points show previous STAR results for $\sqrt{s} = 500$ GeV $pp$ collisions from data recorded during 2011.

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion momentum transverse to the jet axis, $j_{T}$, in different hadron longitudinal momentum fraction $z$ bins. The solid points show the results from this analysis of $\sqrt{s} = 200$ GeV $pp$ collisions, while the open points show previous STAR results for $\sqrt{s} = 500$ GeV $pp$ collisions from data recorded during 2011.

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion momentum transverse to the jet axis, $j_{T}$, in different hadron longitudinal momentum fraction $z$ bins. The solid points show the results from this analysis of $\sqrt{s} = 200$ GeV $pp$ collisions, while the open points show previous STAR results for $\sqrt{s} = 500$ GeV $pp$ collisions from data recorded during 2011.

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion momentum transverse to the jet axis, $j_{T}$, in different hadron longitudinal momentum fraction $z$ bins. The solid points show the results from this analysis of $\sqrt{s} = 200$ GeV $pp$ collisions, while the open points show previous STAR results for $\sqrt{s} = 500$ GeV $pp$ collisions from data recorded during 2011.

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion momentum transverse to the jet axis, $j_{T}$, in different hadron longitudinal momentum fraction $z$ bins. The solid points show the results from this analysis of $\sqrt{s} = 200$ GeV $pp$ collisions, while the open points show previous STAR results for $\sqrt{s} = 500$ GeV $pp$ collisions from data recorded during 2011.

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of particle jet-$p_{T}$, hadron-$z$, and hadron-$j_{T}$ for charged kaons (upper panels) and protons (lower panels) inside jets. In both cases, the $p_T$ dependence is shown integrated over the full ranges of $z$ and $j_T$, while the $z$ and $j_T$ dependences are shown integrated over detector jet-$p_T > 9.9$ GeV/$c$. The bars show the statistical uncertainties, while the size of the boxes represent the systematic uncertainties.

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of particle jet-$p_{T}$, hadron-$z$, and hadron-$j_{T}$ for charged kaons (upper panels) and protons (lower panels) inside jets. In both cases, the $p_T$ dependence is shown integrated over the full ranges of $z$ and $j_T$, while the $z$ and $j_T$ dependences are shown integrated over detector jet-$p_T > 9.9$ GeV/$c$. The bars show the statistical uncertainties, while the size of the boxes represent the systematic uncertainties.

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of particle jet-$p_{T}$, hadron-$z$, and hadron-$j_{T}$ for charged kaons (upper panels) and protons (lower panels) inside jets. In both cases, the $p_T$ dependence is shown integrated over the full ranges of $z$ and $j_T$, while the $z$ and $j_T$ dependences are shown integrated over detector jet-$p_T > 9.9$ GeV/$c$. The bars show the statistical uncertainties, while the size of the boxes represent the systematic uncertainties.

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of particle jet-$p_{T}$, hadron-$z$, and hadron-$j_{T}$ for charged kaons (upper panels) and protons (lower panels) inside jets. In both cases, the $p_T$ dependence is shown integrated over the full ranges of $z$ and $j_T$, while the $z$ and $j_T$ dependences are shown integrated over detector jet-$p_T > 9.9$ GeV/$c$. The bars show the statistical uncertainties, while the size of the boxes represent the systematic uncertainties.

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of particle jet-$p_{T}$, hadron-$z$, and hadron-$j_{T}$ for charged kaons (upper panels) and protons (lower panels) inside jets. In both cases, the $p_T$ dependence is shown integrated over the full ranges of $z$ and $j_T$, while the $z$ and $j_T$ dependences are shown integrated over detector jet-$p_T > 9.9$ GeV/$c$. The bars show the statistical uncertainties, while the size of the boxes represent the systematic uncertainties.

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of particle jet-$p_{T}$, hadron-$z$, and hadron-$j_{T}$ for charged kaons (upper panels) and protons (lower panels) inside jets. In both cases, the $p_T$ dependence is shown integrated over the full ranges of $z$ and $j_T$, while the $z$ and $j_T$ dependences are shown integrated over detector jet-$p_T > 9.9$ GeV/$c$. The bars show the statistical uncertainties, while the size of the boxes represent the systematic uncertainties.

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of particle jet-$p_{T}$, hadron-$z$, and hadron-$j_{T}$ for charged kaons (upper panels) and protons (lower panels) inside jets. In both cases, the $p_T$ dependence is shown integrated over the full ranges of $z$ and $j_T$, while the $z$ and $j_T$ dependences are shown integrated over detector jet-$p_T > 9.9$ GeV/$c$. The bars show the statistical uncertainties, while the size of the boxes represent the systematic uncertainties.

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of particle jet-$p_{T}$, hadron-$z$, and hadron-$j_{T}$ for charged kaons (upper panels) and protons (lower panels) inside jets. In both cases, the $p_T$ dependence is shown integrated over the full ranges of $z$ and $j_T$, while the $z$ and $j_T$ dependences are shown integrated over detector jet-$p_T > 9.9$ GeV/$c$. The bars show the statistical uncertainties, while the size of the boxes represent the systematic uncertainties.

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of particle jet-$p_{T}$, hadron-$z$, and hadron-$j_{T}$ for charged kaons (upper panels) and protons (lower panels) inside jets. In both cases, the $p_T$ dependence is shown integrated over the full ranges of $z$ and $j_T$, while the $z$ and $j_T$ dependences are shown integrated over detector jet-$p_T > 9.9$ GeV/$c$. The bars show the statistical uncertainties, while the size of the boxes represent the systematic uncertainties.

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of particle jet-$p_{T}$, hadron-$z$, and hadron-$j_{T}$ for charged kaons (upper panels) and protons (lower panels) inside jets. In both cases, the $p_T$ dependence is shown integrated over the full ranges of $z$ and $j_T$, while the $z$ and $j_T$ dependences are shown integrated over detector jet-$p_T > 9.9$ GeV/$c$. The bars show the statistical uncertainties, while the size of the boxes represent the systematic uncertainties.

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of particle jet-$p_{T}$, hadron-$z$, and hadron-$j_{T}$ for charged kaons (upper panels) and protons (lower panels) inside jets. In both cases, the $p_T$ dependence is shown integrated over the full ranges of $z$ and $j_T$, while the $z$ and $j_T$ dependences are shown integrated over detector jet-$p_T > 9.9$ GeV/$c$. The bars show the statistical uncertainties, while the size of the boxes represent the systematic uncertainties.

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of particle jet-$p_{T}$, hadron-$z$, and hadron-$j_{T}$ for charged kaons (upper panels) and protons (lower panels) inside jets. In both cases, the $p_T$ dependence is shown integrated over the full ranges of $z$ and $j_T$, while the $z$ and $j_T$ dependences are shown integrated over detector jet-$p_T > 9.9$ GeV/$c$. The bars show the statistical uncertainties, while the size of the boxes represent the systematic uncertainties.

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's longitudinal momentum fraction, $z$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$z$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different jet-$p_{T}$ bins. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different hadron longitudinal momentum fraction $z$ bins, integrated over detector jet-$p_T > 9.9$ GeV/$c$. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different hadron longitudinal momentum fraction $z$ bins, integrated over detector jet-$p_T > 9.9$ GeV/$c$. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different hadron longitudinal momentum fraction $z$ bins, integrated over detector jet-$p_T > 9.9$ GeV/$c$. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different hadron longitudinal momentum fraction $z$ bins, integrated over detector jet-$p_T > 9.9$ GeV/$c$. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different hadron longitudinal momentum fraction $z$ bins, integrated over detector jet-$p_T > 9.9$ GeV/$c$. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different hadron longitudinal momentum fraction $z$ bins, integrated over detector jet-$p_T > 9.9$ GeV/$c$. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different hadron longitudinal momentum fraction $z$ bins, integrated over detector jet-$p_T > 9.9$ GeV/$c$. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

Collins asymmetries, $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$, as a function of the charged pion's momentum transverse to the jet axis, $j_{T}$, in different hadron longitudinal momentum fraction $z$ bins, integrated over detector jet-$p_T > 9.9$ GeV/$c$. The bars show the statistical uncertainties, while the size of the boxes represents the systematic uncertainties on $A_{UT}^{\sin(\phi_{S}-\phi_{H})}$ (vertical) and hadron-$j_{T}$ (horizontal).

$v_{2}(p_{T})$ for $K_{S}^{0}$ (Centrality:0-80%)

$v_{3}(p_{T})$ for $K_{S}^{0}$ (Centrality:0-10%)

$v_{3}(p_{T})$ for $K_{S}^{0}$ (Centrality:10-40%)

$v_{3}(p_{T})$ for $K_{S}^{0}$ (Centrality:40-80%)

$v_{3}(p_{T})$ for $K_{S}^{0}$ (Centrality:0-80%)

$v_{2}(p_{T})$ for $\Lambda$ (Centrality:0-10%)

$v_{2}(p_{T})$ for $\Lambda$ (Centrality:10-40%)

$v_{2}(p_{T})$ for $\Lambda$ (Centrality:40-80%)

$v_{2}(p_{T})$ for $\Lambda$ (Centrality:0-80%)

$v_{3}(p_{T})$ for $\Lambda$ (Centrality:0-10%)

$v_{3}(p_{T})$ for $\Lambda$ (Centrality:10-40%)

$v_{3}(p_{T})$ for $\Lambda$ (Centrality:40-80%)

$v_{3}(p_{T})$ for $\Lambda$ (Centrality:0-80%)

$v_{2}(p_{T})$ for $\bar{\Lambda}$ (Centrality:0-10%)

$v_{2}(p_{T})$ for $\bar{\Lambda}$ (Centrality:10-40%)

$v_{2}(p_{T})$ for $\bar{\Lambda}$ (Centrality:40-80%)

$v_{2}(p_{T})$ for $\bar{\Lambda}$ (Centrality:0-80%)

$v_{3}(p_{T})$ for $\bar{\Lambda}$ (Centrality:0-10%)

$v_{3}(p_{T})$ for $\bar{\Lambda}$ (Centrality:10-40%)

$v_{3}(p_{T})$ for $\bar{\Lambda}$ (Centrality:40-80%)

$v_{3}(p_{T})$ for $\bar{\Lambda}$ (Centrality:0-80%)

$v_{2}(p_{T})$ for $\phi$ (Centrality:0-10%)

$v_{2}(p_{T})$ for $\phi$ (Centrality:10-40%)

$v_{2}(p_{T})$ for $\phi$ (Centrality:40-80%)

$v_{2}(p_{T})$ for $\phi$ (Centrality:0-80%)

$v_{3}(p_{T})$ for $\phi$ (Centrality:0-10%)

$v_{3}(p_{T})$ for $\phi$ (Centrality:10-40%)

$v_{3}(p_{T})$ for $\phi$ (Centrality:0-80%)

$v_{2}(p_{T})$ for $\Xi^{-}$ (Centrality:0-10%)

$v_{2}(p_{T})$ for $\Xi^{-}$ (Centrality:10-40%)

$v_{2}(p_{T})$ for $\Xi^{-}$ (Centrality:40-80%)

$v_{2}(p_{T})$ for $\Xi^{-}$ (Centrality:0-80%)

$v_{3}(p_{T})$ for $\Xi^{-}$ (Centrality:0-10%)

$v_{3}(p_{T})$ for $\Xi^{-}$ (Centrality:10-40%)

$v_{3}(p_{T})$ for $\Xi^{-}$ (Centrality:0-80%)

$v_{2}(p_{T})$ for $\bar{\Xi^{+}}$ (Centrality:0-10%)

$v_{2}(p_{T})$ for $\bar{\Xi^{+}}$ (Centrality:10-40%)

$v_{2}(p_{T})$ for $\bar{\Xi^{+}}$ (Centrality:40-80%)

$v_{2}(p_{T})$ for $\bar{\Xi^{+}}$ (Centrality:0-80%)

$v_{3}(p_{T})$ for $\bar{\Xi^{+}}$ (Centrality:0-10%)

$v_{3}(p_{T})$ for $\bar{\Xi^{+}}$ (Centrality:10-40%)

$v_{3}(p_{T})$ for $\bar{\Xi^{+}}$ (Centrality:0-80%)

$v_{2}(p_{T})$ for $\Omega^{-}$ (Centrality:0-10%)

$v_{2}(p_{T})$ for $\Omega^{-}$ (Centrality:10-40%)

$v_{2}(p_{T})$ for $\Omega^{-}$ (Centrality:40-80%)

$v_{2}(p_{T})$ for $\Omega^{-}$ (Centrality:0-80%)

$v_{3}(p_{T})$ for $\Omega^{-}$ (Centrality:0-10%)

$v_{3}(p_{T})$ for $\Omega^{-}$ (Centrality:10-40%)

$v_{3}(p_{T})$ for $\Omega^{-}$ (Centrality:0-80%)

$v_{2}(p_{T})$ for $\bar{\Omega^{+}}$ (Centrality:0-10%)

$v_{2}(p_{T})$ for $\bar{\Omega^{+}}$ (Centrality:10-40%)

$v_{2}(p_{T})$ for $\bar{\Omega^{+}}$ (Centrality:40-80%)

$v_{2}(p_{T})$ for $\bar{\Omega^{+}}$ (Centrality:0-80%)

$v_{3}(p_{T})$ for $\bar{\Omega^{+}}$ (Centrality:0-10%)

$v_{3}(p_{T})$ for $\bar{\Omega^{+}}$ (Centrality:10-40%)

$v_{3}(p_{T})$ for $\bar{\Omega^{+}}$ (Centrality:0-80%)

$v_{2}$ of $\phi$ to $\bar{p}$ ratio

Difference of $v_{2}$ between particle and anti-particle

Difference of $v_{3}$ between particle and anti-particle

Level-1 muon trigger efficiency in cosmic-ray muon data (blue) and signal simulation (red) as a function of $d_0$, for the Level-1 trigger $p_T$ threshold used in the 2018 analysis triggers. The denominator in the efficiency calculation is the number of STA muons with $|\eta| < 1.2$ and $p_T > 28$ GeV.

Fractions of signal events with zero (green), one (blue), and two (red) STA muons matched to TMS muons by the STA-to-TMS muon association procedure, as a function of true $L_{xy}$, in all simulated $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal samples combined. The fractions are computed relative to the number of signal events passing the trigger and containing two STA muons with more than 12 muon detector hits and $p_T > 10$ GeV matched to generated muons from $X \rightarrow \mu \mu$ decays.

Fractions of signal events with zero (green), one (blue), and two (red) STA muons matched to TMS muons by the STA-to-TMS muon association procedure, as a function of true $L_{xy}$, in all simulated $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal samples combined. The fractions are computed relative to the number of signal events passing the trigger and containing two STA muons with more than 12 muon detector hits and $p_T > 10$ GeV matched to generated muons from $X \rightarrow \mu \mu$ decays.

Comparison of the number of events observed in 2016 data in the STA-STA dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legends also include the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{\mu \mu}$ intervals combined.

Comparison of the number of events observed in 2016 data in the STA-STA dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legends also include the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{\mu \mu}$ intervals combined.

Comparison of the number of events observed in 2018 data in the STA-STA dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legends also include the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{\mu \mu}$ intervals combined.

Comparison of the number of events observed in 2018 data in the STA-STA dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legends also include the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{\mu \mu}$ intervals combined.

Comparison of the number of events observed in 2016 data in the STA-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 30 and 60 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legends also include the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{\mu \mu}$ intervals combined.

Comparison of the number of events observed in 2016 data in the STA-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 30 and 60 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legends also include the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{\mu \mu}$ intervals combined.

Comparison of the number of events observed in 2018 data in the STA-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 30 and 60 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legends also include the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{\mu \mu}$ intervals combined.

Comparison of the number of events observed in 2018 data in the STA-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 30 and 60 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legends also include the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{\mu \mu}$ intervals combined.

Comparison of the number of events observed in 2016 data in the TMS-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals in the $6 < min(d_0 / \sigma_{d_0}) \leq 10$ bin. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legend also includes the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{Z_D}$ and min($d_0 / \sigma_{d_0}$) intervals combined.

Comparison of the number of events observed in 2016 data in the TMS-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals in the $6 < min(d_0 / \sigma_{d_0}) \leq 10$ bin. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legend also includes the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{Z_D}$ and min($d_0 / \sigma_{d_0}$) intervals combined.

Comparison of the number of events observed in 2016 data in the TMS-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals in the $10 < min(d_0 / \sigma_{d_0}) \leq 20$ bin. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legend also includes the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{Z_D}$ and min($d_0 / \sigma_{d_0}$) intervals combined.

Comparison of the number of events observed in 2016 data in the TMS-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals in the $10 < min(d_0 / \sigma_{d_0}) \leq 20$ bin. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legend also includes the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{Z_D}$ and min($d_0 / \sigma_{d_0}$) intervals combined.

Comparison of the number of events observed in 2016 data in the TMS-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals in the $min(d_0 / \sigma_{d_0}) > 20$ bin. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legend also includes the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{Z_D}$ and min($d_0 / \sigma_{d_0}$) intervals combined.

Comparison of the number of events observed in 2016 data in the TMS-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals in the $min(d_0 / \sigma_{d_0}) > 20$ bin. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legend also includes the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{Z_D}$ and min($d_0 / \sigma_{d_0}$) intervals combined.

Comparison of the number of events observed in 2018 data in the TMS-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals in the $6 < min(d_0 / \sigma_{d_0}) \leq 10$ bin. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legend also includes the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{Z_D}$ and min($d_0 / \sigma_{d_0}$) intervals combined.

Comparison of the number of events observed in 2018 data in the TMS-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals in the $6 < min(d_0 / \sigma_{d_0}) \leq 10$ bin. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legend also includes the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{Z_D}$ and min($d_0 / \sigma_{d_0}$) intervals combined.

Comparison of the number of events observed in 2018 data in the TMS-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals in the $10 < min(d_0 / \sigma_{d_0}) \leq 20$ bin. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legend also includes the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{Z_D}$ and min($d_0 / \sigma_{d_0}$) intervals combined.

Comparison of the number of events observed in 2018 data in the TMS-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals in the $10 < min(d_0 / \sigma_{d_0}) \leq 20$ bin. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legend also includes the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{Z_D}$ and min($d_0 / \sigma_{d_0}$) intervals combined.

Comparison of the number of events observed in 2018 data in the TMS-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals in the $min(d_0 / \sigma_{d_0}) > 20$ bin. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legend also includes the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{Z_D}$ and min($d_0 / \sigma_{d_0}$) intervals combined.

Comparison of the number of events observed in 2018 data in the TMS-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals in the $min(d_0 / \sigma_{d_0}) > 20$ bin. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legend also includes the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{Z_D}$ and min($d_0 / \sigma_{d_0}$) intervals combined.

Comparison of the number of events observed in 2016 data in the TMS-TMS dimuon category with the expected number of background events, as a function of the smaller of the two $d_0 / \sigma_{d_0}$ values in the TMS-TMS dimuon. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility.

Comparison of the number of events observed in 2016 data in the TMS-TMS dimuon category with the expected number of background events, as a function of the smaller of the two $d_0 / \sigma_{d_0}$ values in the TMS-TMS dimuon. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility.

Comparison of the number of events observed in 2018 data in the TMS-TMS dimuon category with the expected number of background events, as a function of the smaller of the two $d_0 / \sigma_{d_0}$ values in the TMS-TMS dimuon. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility.

Comparison of the number of events observed in 2018 data in the TMS-TMS dimuon category with the expected number of background events, as a function of the smaller of the two $d_0 / \sigma_{d_0}$ values in the TMS-TMS dimuon. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility.

The 95% CL upper limits on $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 125\ GeV$ and $m(X) = 20\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 125\ GeV$ and $m(X) = 20\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 125\ GeV$ and $m(X) = 50\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 125\ GeV$ and $m(X) = 50\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 200\ GeV$ and $m(X) = 20\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 200\ GeV$ and $m(X) = 20\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 200\ GeV$ and $m(X) = 50\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 200\ GeV$ and $m(X) = 50\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 400\ GeV$ and $m(X) = 20\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 400\ GeV$ and $m(X) = 20\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 400\ GeV$ and $m(X) = 50\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 400\ GeV$ and $m(X) = 50\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 400\ GeV$ and $m(X) = 150\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 400\ GeV$ and $m(X) = 150\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 1000\ GeV$ and $m(X) = 20\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 1000\ GeV$ and $m(X) = 20\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 1000\ GeV$ and $m(X) = 50\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 1000\ GeV$ and $m(X) = 50\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 1000\ GeV$ and $m(X) = 150\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 1000\ GeV$ and $m(X) = 150\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 1000\ GeV$ and $m(X) = 350\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 1000\ GeV$ and $m(X) = 350\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $\sigma(H \rightarrow Z_DZ_D)B(Z_D \rightarrow \mu \mu)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 10\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits. The horizontal lines in gray correspond to the theoretical predictions for values of $B(H \rightarrow Z_DZ_D)$ indicated next to the lines.

The 95% CL upper limits on $\sigma(H \rightarrow Z_DZ_D)B(Z_D \rightarrow \mu \mu)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 10\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits. The horizontal lines in gray correspond to the theoretical predictions for values of $B(H \rightarrow Z_DZ_D)$ indicated next to the lines.

The 95% CL upper limits on $\sigma(H \rightarrow Z_DZ_D)B(Z_D \rightarrow \mu \mu)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 20\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits. The horizontal lines in gray correspond to the theoretical predictions for values of $B(H \rightarrow Z_DZ_D)$ indicated next to the lines.

The 95% CL upper limits on $\sigma(H \rightarrow Z_DZ_D)B(Z_D \rightarrow \mu \mu)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 20\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits. The horizontal lines in gray correspond to the theoretical predictions for values of $B(H \rightarrow Z_DZ_D)$ indicated next to the lines.

The 95% CL upper limits on $\sigma(H \rightarrow Z_DZ_D)B(Z_D \rightarrow \mu \mu)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 30\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits. The horizontal lines in gray correspond to the theoretical predictions for values of $B(H \rightarrow Z_DZ_D)$ indicated next to the lines.

The 95% CL upper limits on $\sigma(H \rightarrow Z_DZ_D)B(Z_D \rightarrow \mu \mu)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 30\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits. The horizontal lines in gray correspond to the theoretical predictions for values of $B(H \rightarrow Z_DZ_D)$ indicated next to the lines.

The 95% CL upper limits on $\sigma(H \rightarrow Z_DZ_D)B(Z_D \rightarrow \mu \mu)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 40\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits. The horizontal lines in gray correspond to the theoretical predictions for values of $B(H \rightarrow Z_DZ_D)$ indicated next to the lines.

The 95% CL upper limits on $\sigma(H \rightarrow Z_DZ_D)B(Z_D \rightarrow \mu \mu)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 40\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits. The horizontal lines in gray correspond to the theoretical predictions for values of $B(H \rightarrow Z_DZ_D)$ indicated next to the lines.

The 95% CL upper limits on $\sigma(H \rightarrow Z_DZ_D)B(Z_D \rightarrow \mu \mu)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 50\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits. The horizontal lines in gray correspond to the theoretical predictions for values of $B(H \rightarrow Z_DZ_D)$ indicated next to the lines.

The 95% CL upper limits on $\sigma(H \rightarrow Z_DZ_D)B(Z_D \rightarrow \mu \mu)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 50\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits. The horizontal lines in gray correspond to the theoretical predictions for values of $B(H \rightarrow Z_DZ_D)$ indicated next to the lines.

The 95% CL upper limits on $\sigma(H \rightarrow Z_DZ_D)B(Z_D \rightarrow \mu \mu)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 60\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits. The horizontal lines in gray correspond to the theoretical predictions for values of $B(H \rightarrow Z_DZ_D)$ indicated next to the lines.

The 95% CL upper limits on $\sigma(H \rightarrow Z_DZ_D)B(Z_D \rightarrow \mu \mu)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 60\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits. The horizontal lines in gray correspond to the theoretical predictions for values of $B(H \rightarrow Z_DZ_D)$ indicated next to the lines.

Observed 95% CL exclusion contours in the HAHM model, in the ($m(Z_D)$, $c\tau(Z_D)$) plane. The contours correspond to several representative values of $B(H \rightarrow Z_DZ_D$) ranging from 0.005 to 1%.

Observed 95% CL exclusion contours in the HAHM model, in the ($m(Z_D)$, $c\tau(Z_D)$) plane. The contours correspond to several representative values of $B(H \rightarrow Z_DZ_D$) ranging from 0.005 to 1%.

Observed 95% CL exclusion contours in the HAHM model, in the ($m(Z_D)$, $\epsilon$) plane. The contours correspond to several representative values of $B(H \rightarrow Z_DZ_D$) ranging from 0.005 to 1%.

Observed 95% CL exclusion contours in the HAHM model, in the ($m(Z_D)$, $\epsilon$) plane. The contours correspond to several representative values of $B(H \rightarrow Z_DZ_D$) ranging from 0.005 to 1%.

Background estimation and observed number of events in the STA-STA dimuon category in 2016 and 2018 data. For each probed LLP mass, the chosen mass interval is shown. The mass interval is followed by the estimated and observed counts for the given year. The quoted uncertainties are statistical only.

Background estimations and observed numbers of events in the STA-STA dimuon category in 2016 and 2018 data. For each probed LLP mass, the chosen mass interval is shown, followed by the predicted background yield $N^\text{est}_\text{bkg}$ and the observed number of events $N^\text{obs}$ for the given year. The quoted uncertainties are statistical only.

Background estimation and observed number of events in the TMS-TMS dimuon category in 2016 data. The mass interval is followed by the estimated and observed counts within each $min(d_0 / \sigma_{d_0})$ bin in this mass interval. The quoted uncertainties are statistical only.

Background estimations and observed numbers of events in the TMS-TMS dimuon category in 2016 data. For each mass interval, the table shows the predicted background yield $N^\text{est}_\text{bkg}$ and the observed number of events $N^\text{obs}$ in each of the three $\text{min}(d_0 / \sigma_{d_0})$ bins. The quoted uncertainties are statistical only

Background estimation and observed number of events in the TMS-TMS dimuon category in 2018 data. The mass interval is followed by the estimated and observed counts within each $min(d_0 / \sigma_{d_0})$ bin in this mass interval. The quoted uncertainties are statistical only.

Background estimations and observed numbers of events in the TMS-TMS dimuon category in 2016 data. For each mass interval, the table shows the predicted background yield $N^\text{est}_\text{bkg}$ and the observed number of events $N^\text{obs}$ in each of the three $\text{min}(d_0 / \sigma_{d_0})$ bins. The quoted uncertainties are statistical only

Correspondence between the mass intervals in the TMS-TMS category and the parameters of the simulated signal samples.

Correspondence between the probed LLP masses and the chosen mass intervals in the TMS-TMS category.

Background estimation and observed number of events in the STA-TMS dimuon category in 2016 and 2018 data. For each probed LLP mass, the chosen mass interval is shown. The mass interval is followed by the estimated and observed counts for the given year. The quoted uncertainties are statistical only.

Background estimations and observed numbers of events in the STA-TMS dimuon category in 2016 and 2018 data. For each probed LLP mass, the chosen mass interval is shown, followed by the predicted background yield $N^\text{est}_\text{bkg}$ and the observed number of events $N^\text{obs}$ for the given year. The quoted uncertainties are statistical only.

Number of events passing consecutive sets of selection criteria for 2018 collision data and the signal process $\Phi(125) \rightarrow XX(20\ GeV, c\tau = 13\ cm) \rightarrow \mu\mu$. Each row introduces a new criterion that is applied in addition to the selection of the previous row. In addition to the total number of events, N(events), the event yields of the individual dimuon vertex categories, STA-STA, TMS-TMS, and STA-TMS, are shown in separate columns for each data set. In these columns, events containing selected dimuons of different categories are independently counted for each category.

Number of events passing consecutive sets of selection criteria, in 2018 data and in a sample of simulated $\Phi \rightarrow XX \rightarrow \mu\mu$ signal events with $m(H) = 125\ GeV$, $m(X) = 20\ GeV$, and $c\tau = 13\ cm$. Each row introduces a new criterion that is applied in addition to the selection of the previous row. In addition to the total number of events $N(\text{total})$, the event yields in the individual dimuon categories, STA-STA, TMS-TMS, and STA-TMS, are shown in separate columns for each data set. In these columns, events containing selected dimuons of different categories are counted independently for each category.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 125\ GeV$ and $m(X) = 20\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 125\ GeV$ and $m(X) = 20\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 125\ GeV$ and $m(X) = 50\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 125\ GeV$ and $m(X) = 50\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 200\ GeV$ and $m(X) = 20\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 200\ GeV$ and $m(X) = 20\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 200\ GeV$ and $m(X) = 50\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 200\ GeV$ and $m(X) = 50\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 400\ GeV$ and $m(X) = 20\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 400\ GeV$ and $m(X) = 20\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 400\ GeV$ and $m(X) = 50\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 400\ GeV$ and $m(X) = 50\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 400\ GeV$ and $m(X) = 150\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 400\ GeV$ and $m(X) = 150\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 1000\ GeV$ and $m(X) = 20\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 1\ TeV$ and $m(X) = 20\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 1000\ GeV$ and $m(X) = 50\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 1\ TeV$ and $m(X) = 50\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 1000\ GeV$ and $m(X) = 150\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 1\ TeV$ and $m(X) = 150\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 1000\ GeV$ and $m(X) = 350\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 1\ TeV$ and $m(X) = 350\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 125\ GeV$ and $m(X) = 20\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 125\ GeV$ and $m(X) = 20\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 125\ GeV$ and $m(X) = 50\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 125\ GeV$ and $m(X) = 50\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 200\ GeV$ and $m(X) = 20\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 200\ GeV$ and $m(X) = 20\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 200\ GeV$ and $m(X) = 50\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 200\ GeV$ and $m(X) = 50\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 400\ GeV$ and $m(X) = 20\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 400\ GeV$ and $m(X) = 20\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 400\ GeV$ and $m(X) = 50\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 400\ GeV$ and $m(X) = 50\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 400\ GeV$ and $m(X) = 150\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 400\ GeV$ and $m(X) = 150\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 1000\ GeV$ and $m(X) = 20\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 1\ TeV$ and $m(X) = 20\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 1000\ GeV$ and $m(X) = 50\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 1\ TeV$ and $m(X) = 50\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 1000\ GeV$ and $m(X) = 150\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 1\ TeV$ and $m(X) = 150\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 1000\ GeV$ and $m(X) = 350\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 1\ TeV$ and $m(X) = 350\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $H \rightarrow Z_DZ_D \rightarrow \mu\mu + anything$ signal process with $m(H) = 125\ GeV$ and $m(Z_D) = 10\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $H \rightarrow Z_DZ_D \rightarrow \mu\mu + anything$ signal process with $m(H) = 125\ GeV$ and $m(Z_D) = 10\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well the combined efficiency (black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $H \rightarrow Z_DZ_D \rightarrow \mu\mu + anything$ signal process with $m(H) = 125\ GeV$ and $m(Z_D) = 20\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $H \rightarrow Z_DZ_D \rightarrow \mu\mu + anything$ signal process with $m(H) = 125\ GeV$ and $m(Z_D) = 20\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well the combined efficiency (black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $H \rightarrow Z_DZ_D \rightarrow \mu\mu + anything$ signal process with $m(H) = 125\ GeV$ and $m(Z_D) = 30\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $H \rightarrow Z_DZ_D \rightarrow \mu\mu + anything$ signal process with $m(H) = 125\ GeV$ and $m(Z_D) = 30\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well the combined efficiency (black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $H \rightarrow Z_DZ_D \rightarrow \mu\mu + anything$ signal process with $m(H) = 125\ GeV$ and $m(Z_D) = 40\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $H \rightarrow Z_DZ_D \rightarrow \mu\mu + anything$ signal process with $m(H) = 125\ GeV$ and $m(Z_D) = 40\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well the combined efficiency (black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $H \rightarrow Z_DZ_D \rightarrow \mu\mu + anything$ signal process with $m(H) = 125\ GeV$ and $m(Z_D) = 50\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $H \rightarrow Z_DZ_D \rightarrow \mu\mu + anything$ signal process with $m(H) = 125\ GeV$ and $m(Z_D) = 50\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well the combined efficiency (black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $H \rightarrow Z_DZ_D \rightarrow \mu\mu + anything$ signal process with $m(H) = 125\ GeV$ and $m(Z_D) = 60\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $H \rightarrow Z_DZ_D \rightarrow \mu\mu + anything$ signal process with $m(H) = 125\ GeV$ and $m(Z_D) = 60\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well the combined efficiency (black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Signal efficiencies as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true} < 20\ cm$ in the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal model, in 2016 samples. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria applied in the STA-STA dimuon category to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.

Signal efficiencies as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true} < 20\ cm$ in the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal model, in 2018 samples. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria applied in the STA-STA dimuon category to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.

Signal efficiencies as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true} < 20\ cm$ in the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal model, in 2016 samples. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria applied in the STA-TMS dimuon category to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.

Signal efficiencies as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true} < 20\ cm$ in the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal model, in 2018 samples. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria applied in the STA-TMS dimuon category to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.

Signal efficiencies as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true} < 20\ cm$ in the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal model, in 2016 samples. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria applied in the TMS-TMS dimuon category to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.

Signal efficiencies as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true} < 20\ cm$ in the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal model, in 2018 samples. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria applied in the TMS-TMS dimuon category to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.

Signal efficiencies as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $20\ cm < L_{xy}^\mathrm{true} < 70\ cm$ in the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal model, in 2016 samples. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria applied in the STA-STA dimuon category to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.

Signal efficiencies as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $20\ cm < L_{xy}^\mathrm{true} < 70\ cm$ in the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal model, in 2018 samples. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria applied in the STA-STA dimuon category to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.

Signal efficiencies as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $20\ cm < L_{xy}^\mathrm{true} < 70\ cm$ in the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal model, in 2016 samples. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria applied in the STA-TMS dimuon category to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.

Signal efficiencies as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $20\ cm < L_{xy}^\mathrm{true} < 70\ cm$ in the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal model, in 2018 samples. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria applied in the STA-TMS dimuon category to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.

Signal efficiencies as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $20\ cm < L_{xy}^\mathrm{true} < 70\ cm$ in the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal model, in 2016 samples. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria applied in the TMS-TMS dimuon category to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.

Signal efficiencies as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $20\ cm < L_{xy}^\mathrm{true} < 70\ cm$ in the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal model, in 2018 samples. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria applied in the TMS-TMS dimuon category to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.

Signal efficiencies as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $70\ cm < L_{xy}^\mathrm{true} < 320\ cm$ in the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal model, in 2016 samples. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria applied in the STA-STA dimuon category to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper. Efficiencies for dimuons with $70\ cm < L_{xy}^\mathrm{true} < 320\ cm$ in the STA-TMS and TMS-TMS dimuon categories are equal to zero.

Signal efficiencies as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $70\ cm < L_{xy}^\mathrm{true} < 320\ cm$ in the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal model, in 2018 samples. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria applied in the STA-STA dimuon category to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper. Efficiencies for dimuons with $70\ cm < L_{xy}^\mathrm{true} < 320\ cm$ in the STA-TMS and TMS-TMS dimuon categories are equal to zero.

The observed mass distribution in the SR-Inclusive_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed mass distribution in the SR-Inclusive_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

List of expected and observed events, $p_{0}$-value and the corresponding $Z$ local significance, as well as the 95% CLs upper limit of the expected and observed signal events ($S^{95}_ ext{exp} and $S^{95}_ ext{obs}$ ) in each mass window for SR-Inclusive bins of the short lifetime regime.

List of expected and observed events, $p_{0}$-value and the corresponding $Z$ local significance, as well as the 95% CLs upper limit of the expected and observed signal events ($S^{95}_ ext{exp} and $S^{95}_ ext{obs}$ ) in each mass window for SR-Inclusive bins of the long lifetime regime.

The observed $p_{\rm T$ distribution in the SR-Inclusive_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed $p_{\rm T$ distribution in the SR-Inclusive_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed $|\eta|$ distribution in the SR-Inclusive_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed $|\eta|$ distribution in the SR-Inclusive_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed dE/dx distribution in the SR-Inclusive_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed dE/dx distribution in the SR-Inclusive_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed mass distribution in the SR-Trk-IBL0_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed mass distribution in the SR-Mu-IBL0_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed mass distribution in the SR-Trk-IBL0_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed mass distribution in the SR-Mu-IBL0_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed mass distribution in the SR-Trk-IBL1 signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed mass distribution in the SR-Mu-IBL1 signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

Lower limits on the gluino mass, from gluino $R$-hadron pair production, as a function of gluino lifetime for two neutralino mass assumptions of (a) $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$ and (b) $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$. The upper $1 \sigma_\text{exp}$ expected bound is very close to the expected limit for some lifetime values due to the expected background getting very close to 0 events.

Lower limits on the gluino mass, from gluino $R$-hadron pair production, as a function of gluino lifetime for two neutralino mass assumptions of (a) $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$ and (b) $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$. The upper $1 \sigma_\text{exp}$ expected bound is very close to the expected limit for some lifetime values due to the expected background getting very close to 0 events.

Lower limits on the gluino mass, from gluino $R$-hadron pair production, as a function of gluino lifetime for two neutralino mass assumptions of (a) $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$ and (b) $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$. The upper $1 \sigma_\text{exp}$ expected bound is very close to the expected limit for some lifetime values due to the expected background getting very close to 0 events.

Lower limits on the gluino mass, from gluino $R$-hadron pair production, as a function of gluino lifetime for two neutralino mass assumptions of (a) $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$ and (b) $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$. The upper $1 \sigma_\text{exp}$ expected bound is very close to the expected limit for some lifetime values due to the expected background getting very close to 0 events.

(a) Lower limits on the chargino mass as a function of lifetime, and (b) the contours around the excluded mass-lifetime region for stau pair production.

(a) Lower limits on the chargino mass as a function of lifetime, and (b) the contours around the excluded mass-lifetime region for stau pair production.

(a) Lower limits on the chargino mass as a function of lifetime, and (b) the contours around the excluded mass-lifetime region for stau pair production.

(a) Lower limits on the chargino mass as a function of lifetime, and (b) the contours around the excluded mass-lifetime region for stau pair production.

Comparison of the observed and expected VAR distributionsin VR-LowPt-Trk-IBL0_Low. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.

Comparison of the observed and expected VAR distributionsin VR-LowPt-Mu-IBL0_Low. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.

Comparison of the observed and expected VAR distributionsin VR-LowPt-Trk-IBL0_High. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.

Comparison of the observed and expected VAR distributionsin VR-LowPt-Mu-IBL0_High. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.

Comparison of the observed and expected VAR distributionsin VR-LowPt-Trk-IBL1. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.

Comparison of the observed and expected VAR distributionsin VR-LowPt-Mu-IBL1. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.

Comparison of the observed and expected VAR distributionsin VR-HiEta-Trk-IBL0_Low. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.

Comparison of the observed and expected VAR distributionsin VR-HiEta-Mu-IBL0_Low. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.

Comparison of the observed and expected VAR distributionsin VR-HiEta-Trk-IBL0_High. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.

Comparison of the observed and expected VAR distributionsin VR-HiEta-Mu-IBL0_High. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.

Comparison of the observed and expected VAR distributionsin VR-HiEta-Trk-IBL1. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.

Comparison of the observed and expected VAR distributionsin VR-HiEta-Mu-IBL1. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.

The observed $p_{\rm T$ distribution in the SR-Trk-IBL0_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed $p_{\rm T$ distribution in the SR-Mu-IBL0_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed $p_{\rm T$ distribution in the SR-Trk-IBL0_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed $p_{\rm T$ distribution in the SR-Mu-IBL0_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed $p_{\rm T$ distribution in the SR-Trk-IBL1 signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed $p_{\rm T$ distribution in the SR-Mu-IBL1 signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed dE/dx distribution in the SR-Trk-IBL0_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed dE/dx distribution in the SR-Mu-IBL0_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed dE/dx distribution in the SR-Trk-IBL0_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed dE/dx distribution in the SR-Mu-IBL0_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed dE/dx distribution in the SR-Trk-IBL1 signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed dE/dx distribution in the SR-Mu-IBL1 signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

Expected and observed distributions in SR-Inclusive_Low of missing transverse momentum. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

Expected and observed distributions in SR-Inclusive_High of missing transverse momentum. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

Expected and observed distributions in SR-Inclusive_Low of relative phi-angle between pTmiss and the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

Expected and observed distributions in SR-Inclusive_High of relative phi-angle between pTmiss and the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

Expected and observed distributions in SR-Inclusive_Low of the transverse mass of pTmiss and the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

Expected and observed distributions in SR-Inclusive_High of the transverse mass of pTmiss and the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

Expected and observed distributions in SR-Inclusive_Low of the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

Expected and observed distributions in SR-Inclusive_High of the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

Expected and observed distributions in SR-Inclusive_Low of the relative phi-angle between the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track, and the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

Expected and observed distributions in SR-Inclusive_High of the relative phi-angle between the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track, and the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

Expected and observed distributions in SR-Inclusive_Low of the relative phi-angle between pTmiss and the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

Expected and observed distributions in SR-Inclusive_High of the relative phi-angle between pTmiss and the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

Expected and observed distributions in SR-Inclusive_Low of the transverse mass of pTmiss and the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

Expected and observed distributions in SR-Inclusive_High of the transverse mass of pTmiss and the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

Expected and observed distributions in SR-Inclusive_Low of the effective mass, defined as the scalar sum pT of the signal candidate track, jets satisfying pT > 30 GeV, excluding ones within deltaR < 0.4 with respect to the signal candidate track, and pTmiss. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

Expected and observed distributions in SR-Inclusive_High of the effective mass, defined as the scalar sum pT of the signal candidate track, jets satisfying pT > 30 GeV, excluding ones within deltaR < 0.4 with respect to the signal candidate track, and pTmiss. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

The expected upper limits on cross-section for gluinos with $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$, with lifetime with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.

The expected upper limits on cross-section for gluinos with $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$, with lifetime with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.

The expected upper limits on cross-section for gluinos with $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$, with lifetime with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.

The expected upper limits on cross-section for gluinos with $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$, with lifetime with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.

The expected upper limits on cross-section for gluinos with $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$, with lifetime with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.

The expected upper limits on cross-section for gluinos with $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$, with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, and (d) 30 ns.

The expected upper limits on cross-section for gluinos with $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$, with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, and (d) 30 ns.

The expected upper limits on cross-section for gluinos with $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$, with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, and (d) 30 ns.

The expected upper limits on cross-section for gluinos with $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$, with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, and (d) 30 ns.

The expected upper limits on cross-section for charginos with lifetime (c) 10 ns, (d) 30 ns, and (e) stable.

The expected upper limits on cross-section for charginos with lifetime (c) 10 ns, (d) 30 ns, and (e) stable.

The expected upper limits on cross-section for charginos with lifetime (c) 10 ns, (d) 30 ns, and (e) stable.

The expected upper limits on cross-section for charginos with lifetime (c) 10 ns, (d) 30 ns, and (e) stable.

The expected upper limits on cross-section for charginos with lifetime (c) 10 ns, (d) 30 ns, and (e) stable.

The expected upper limits on cross-section for sleptons with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.

The expected upper limits on cross-section for sleptons with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.

The expected upper limits on cross-section for sleptons with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.

The expected upper limits on cross-section for sleptons with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.

The expected upper limits on cross-section for sleptons with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.

Muon reconstruction efficiency as a function of β and |η| for (a) stable charginos and (b) stable charged R-hadrons. For weakly interacting LLPs with calorimeter materials the efficiency for the chargino is recommended to refer to. The muon reconstruction efficiency for R-hadrons is significantly lower due to having QCD interactions with materials.

Muon reconstruction efficiency as a function of β and |η| for (a) stable charginos and (b) stable charged R-hadrons. For weakly interacting LLPs with calorimeter materials the efficiency for the chargino is recommended to refer to. The muon reconstruction efficiency for R-hadrons is significantly lower due to having QCD interactions with materials.

Trigger and event selection efficiencies. The band on the marker indicates a typical size of fluctuation by the LLP mass and lifetime observed by the samples used in efficiency derivation, but it does not indicate the full envelope of model dependence.

Trigger and event selection efficiencies. The band on the marker indicates a typical size of fluctuation by the LLP mass and lifetime observed by the samples used in efficiency derivation, but it does not indicate the full envelope of model dependence.

Signal track selection efficiency as a function of CLLP $\beta\gamma$ for SR-Inclusive_Low and SR-Inclusive_High bins. The band on the marker indicates a typical size of fluctuation by the LLP mass and lifetime observed by the samples used in efficiency derivation, but it does not indicate the full envelope of model dependence.

Signal selection efficiency by the mass window for SR-Inclusive_Low and SR-Inclusive_High bins.

Acceptance for the R-hadron pair-production model with m(N1) = 100 GeV for various masses and lifetimes. The acceptance is defined as the fraction of events having at least one charged LLP satisfying pT > 120 GeV, |\eta| < 1.8 and r_decay > 500 mm.

Acceptance for the R-hadron pair-production model with DeltaM(gluino, N1) = 30 GeV for various masses and lifetimes. The acceptance is defined as the fraction of events having at least one charged LLP satisfying pT > 120 GeV, |eta| < 1.8 and r_decay > 500 mm.

Acceptance for the chargino pair-production model for various masses and lifetimes. The acceptance is defined as the fraction of events having at least one charged LLP satisfying pT > 120 GeV, |\eta| < 1.8 and r_decay > 500 mm.

Acceptance for the stau pair-production model for various masses and lifetimes. The acceptance is defined as the fraction of events having at least one charged LLP satisfying pT > 120 GeV, |\eta| < 1.8 and r_decay > 500 mm.

Event-level efficiency for the R-hadron pair-production model with m(N1) = 100 GeV for various masses and lifetimes. The efficiency is defined as the fraction of events satisfying the selection of trigger, event and jet cleaning, ETmiss and primary vertex requirements per events satisfying the acceptance criteria.

Event-level efficiency for the R-hadron pair-production model with DeltaM(gluino, N1) = 30 GeV for various masses and lifetimes. The efficiency is defined as the fraction of events satisfying the selection of trigger, event and jet cleaning, ETmiss and primary vertex requirements per events satisfying the acceptance criteria.

Event-level efficiency for the chargino pair-production model for various masses and lifetimes. The efficiency is defined as the fraction of events satisfying the selection of trigger, event and jet cleaning, ETmiss and primary vertex requirements per events satisfying the acceptance criteria.

Event-level efficiency for the stau pair-production model for various masses and lifetimes. The efficiency is defined as the fraction of events satisfying the selection of trigger, event and jet cleaning, ETmiss and primary vertex requirements per events satisfying the acceptance criteria.

Efficiency of SR-Inclusive_Highfor the R-hadron pair-production model with m(N1) = 100 GeV for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.

Efficiency of SR-Inclusive_Highfor the R-hadron pair-production model with DeltaM(gluino, N1) = 30 GeV for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.

Efficiency of SR-Inclusive_Highfor the chargino pair-production model for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.

Efficiency of SR-Inclusive_Highfor the stau pair-production model for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.

Efficiency of SR-Inclusive_Low for the R-hadron pair-production model with m(N1) = 100 GeV for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.

Efficiency of SR-Inclusive_Low for the R-hadron pair-production model with DeltaM(gluino, N1) = 30 GeV for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.

Efficiency of SR-Inclusive_Low for the chargino pair-production model for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.

Efficiency of SR-Inclusive_Low for the stau pair-production model for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.

Passing events in event selection steps for the R-hadron pair-production model with m(N1) = 100 GeV for various masses and lifetimes.

Passing events in event selection steps for the R-hadron pair-production model with DeltaM(gluino, N1) = 30 GeV for various masses and lifetimes.

Passing events in event selection steps for the chargino pair-production model for various masses and lifetimes.

Passing events in event selection steps for the stau pair-production model for various masses and lifetimes.