Two-dimensional distribution of the invariant mass $m_{DV}$ and the track multiplicity in the High-pT jet SR for observed data events

Two-dimensional distribution of the invariant mass $m_{DV}$ and the track multiplicity in the High-pT jet SR for expected signal events in the strong gluino pair pair production model with m(gluino)=1.8 TeV, m(chi0)=0.2 TeV, tau(chi0)=0.1 ns

Two-dimensional distribution of the invariant mass $m_{DV}$ and the track multiplicity in the Trackless jet SR for observed data events

Two-dimensional distribution of the invariant mass $m_{DV}$ and the track multiplicity in the Trackless jet SR for expected signal events in the electroweak pair production model

Expected exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Observed exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Expected exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Observed exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Exclusion limits at 95% CL on the production cross section in the electroweak pair production model.

Exclusion limits at 95% CL on the production cross section in the strong gluino pair production models and m(gluino)=2.4 TeV

Expected exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Observed exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Expected exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Observed exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Expected exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Observed exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Expected exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Observed exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Expected exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Expected (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Expected (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Observed exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Observed (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Observed (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Expected exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Expected (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Expected (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Observed exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Observed (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Observed (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Expected exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Expected (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Expected (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Observed exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Observed (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Observed (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Expected exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Expected (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Expected (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Observed exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Observed (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Observed (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Exclusion limits at 95% CL on the production cross section in the strong gluino pair production models and m($ ilde{\chi}^0_1$)=1.25 TeV

Acceptance cutflow for the High-pT SR for representative points in the strong gluino pair production model. See additional resources for more information.

Acceptance cutflow for the Trackless SR for representative points in the electroweak pair production model. See additional resources for more information.

Acceptance cutflow for the Trackless SR for representative points in the electroweak pair production model with heavy-flavor quarks final state. See additional resources for more information.

Acceptance cutflow for the High-pT SR for representative points in the electroweak pair production model with heavy-flavor quarks final state. See additional resources for more information.

Reinterpretation Material: Event-level Efficiency for HighPt SR selections, R < 1150 mm

Reinterpretation Material: Event-level Efficiency for HighPt SR selections, R [1150, 3870] mm

Reinterpretation Material: Event-level Efficiency for HighPt SR selections, R > 3870 mm

Reinterpretation Material: Event-level Efficiency for Trackless SR selections, R < 1150 mm

Reinterpretation Material: Event-level Efficiency for Trackless SR selections, R [1150, 3870] mm

Reinterpretation Material: Event-level Efficiency for Trackless SR selections, R > 3870 mm

Reinterpretation Material: Vertex-level Efficiency for R < 22 mm

Reinterpretation Material: Vertex-level Efficiency for R [22, 25] mm

Reinterpretation Material: Vertex-level Efficiency for R [25, 29] mm

Reinterpretation Material: Vertex-level Efficiency for R [29, 38] mm

Reinterpretation Material: Vertex-level Efficiency for R [38, 46] mm

Reinterpretation Material: Vertex-level Efficiency for R [46, 73] mm

Reinterpretation Material: Vertex-level Efficiency for R [73, 84] mm

Reinterpretation Material: Vertex-level Efficiency for R [84, 111] mm

Reinterpretation Material: Vertex-level Efficiency for R [111, 120] mm

Reinterpretation Material: Vertex-level Efficiency for R [120, 145] mm

Reinterpretation Material: Vertex-level Efficiency for R [145, 180] mm

Reinterpretation Material: Vertex-level Efficiency for R [180, 300] mm

Cutflow (acceptance x efficiency) for the High-pT SR for representative points in the strong gluino pair production model. See additional resources for more information.

Cutflow (acceptance x efficiency) for the Trackless SR for representative points in the electroweak pair production model. See additional resources for more information.

Cutflow (acceptance x efficiency) for the Trackless SR for representative points in the electroweak pair production model with heavy-flavor quarks. See additional resources for more information.

Cutflow (acceptance x efficiency) for the High-pT SR for representative points in the electroweak pair production model with heavy-flavor quarks. See additional resources for more information.

Nuclear modification factor of $\Upsilon(1\mathrm{S})$ as a function of the average number of participants $\langle N_{\mathrm{part}} \rangle$ or as a function of the collision centrality.

Nuclear modification factor of $\Upsilon(2\mathrm{S})$ as a function of the average number of participants $\langle N_{\mathrm{part}} \rangle$ or as a function of the collision centrality.

Ratio of $\Upsilon(2\mathrm{S})$ and $\Upsilon(1\mathrm{S})$ yields (cf. equation 2 in the article for the definition) as a function of the average number of participants $\langle N_{\mathrm{part}} \rangle$ or as a function of the collision centrality. The global uncertainty is the quadratic sum of the branching ratio uncertainties.

Relative nuclear modification factor or double yield ratio between $\Upsilon(2\mathrm{S})$ and $\Upsilon(1\mathrm{S})$ as a function of the average number of participants $\langle N_{\mathrm{part}} \rangle$ or as a function of the collision centrality. The global uncertainty corresponds to the systematic uncertainty on the cross-section ratio in proton–proton collisions.

Nuclear modification factor of $\Upsilon(1\mathrm{S})$ as a function of transverse momentum for the 0–90% centrality interval.

Nuclear modification factor of $\Upsilon(1\mathrm{S})$ as a function of rapidity for the 0–90% centrality interval.

Nuclear modification factor of $\Upsilon(2\mathrm{S})$ as a function of rapidity for the 0–90% centrality interval.

Interpolated production cross sections and cross-section ratio for $\Upsilon(1\mathrm{S}) \rightarrow \mu^{+}\mu^{-}$ and $\Upsilon(2\mathrm{S}) \rightarrow \mu^{+}\mu^{-}$ in proton–proton collisions, integrated over the rapidity interval 2.5–4.0 and $p_{\mathrm{T}} <$ 15 GeV/$c$. Results used for the determination of the integrated nuclear modification factors and of the nuclear modification factors as a function of centrality (Figures 4 and 5 (right)).

Interpolated $p_{\mathrm{T}}$-differential cross section for $\Upsilon(1\mathrm{S}) \rightarrow \mu^{+}\mu^{-}$ in proton–proton collisions. Results used for the determination of the nuclear modification factor of $\Upsilon(1\mathrm{S})$ as a function of its transverse momentum (Figure 6).

Interpolated rapidity-differential cross section for $\Upsilon(1\mathrm{S}) \rightarrow \mu^{+}\mu^{-}$ in proton–proton collisions. Results used for the determination of the nuclear modification factor of $\Upsilon(1\mathrm{S})$ as a function of rapidity (Figure 7).

Interpolated rapidity-differential cross section for $\Upsilon(2\mathrm{S}) \rightarrow \mu^{+}\mu^{-}$ in proton–proton collisions. Results used for the determination of the nuclear modification factor of $\Upsilon(2\mathrm{S})$ as a function of rapidity (Figure 7).

A comparison of the measured cell $E_T^{miss}$ distribution with that predicted by the two-component model for two pile-up scenarios. The magenta points extend the measured distribution using L1 $E_T^{miss} > 30\,$GeV and L1 $E_T^{miss} > 50\,$GeV data. The red curve is the prediction from the calorimeter-resolution part of the model. The green curve is the high $E_T^{miss}$ tail's probability distribution for the mean number of $pp$ interactions $\mu$ in each figure. The blue curve is the full model prediction computed by combining the $E_T^{miss}$ from these two individual sources shown in red and green, each calculated for $\mu=\langle\mu\rangle$. The black points show the unbiased $E_T^{miss}$ distribution measured in data. Corresponds to a prediction for $\langle\mu\rangle = 25$.

A comparison of the measured cell $E_T^{miss}$ distribution with that predicted by the two-component model for two pile-up scenarios. The magenta points extend the measured distribution using L1 $E_T^{miss} > 30\,$GeV and L1 $E_T^{miss} > 50\,$GeV data. The red curve is the prediction from the calorimeter-resolution part of the model. The green curve is the high $E_T^{miss}$ tail's probability distribution for the mean number of $pp$ interactions $\mu$ in each figure. The blue curve is the full model prediction computed by combining the $E_T^{miss}$ from these two individual sources shown in red and green, each calculated for $\mu=\langle\mu\rangle$. The black points show the unbiased $E_T^{miss}$ distribution measured in data. Corresponds to a prediction for $\langle\mu\rangle = 25$.

A comparison of the measured cell $E_T^{miss}$ distribution with that predicted by the two-component model for two pile-up scenarios. The magenta points extend the measured distribution using L1 $E_T^{miss} > 30\,$GeV and L1 $E_T^{miss} > 50\,$GeV data. The red curve is the prediction from the calorimeter-resolution part of the model. The green curve is the high $E_T^{miss}$ tail's probability distribution for the mean number of $pp$ interactions $\mu$ in each figure. The blue curve is the full model prediction computed by combining the $E_T^{miss}$ from these two individual sources shown in red and green, each calculated for $\mu=\langle\mu\rangle$. The black points show the unbiased $E_T^{miss}$ distribution measured in data. Corresponds to a prediction for $\langle\mu\rangle = 55$.

A comparison of the measured cell $E_T^{miss}$ distribution with that predicted by the two-component model for two pile-up scenarios. The magenta points extend the measured distribution using L1 $E_T^{miss} > 30\,$GeV and L1 $E_T^{miss} > 50\,$GeV data. The red curve is the prediction from the calorimeter-resolution part of the model. The green curve is the high $E_T^{miss}$ tail's probability distribution for the mean number of $pp$ interactions $\mu$ in each figure. The blue curve is the full model prediction computed by combining the $E_T^{miss}$ from these two individual sources shown in red and green, each calculated for $\mu=\langle\mu\rangle$. The black points show the unbiased $E_T^{miss}$ distribution measured in data. Corresponds to a prediction for $\langle\mu\rangle = 55$.

A comparison of the measured cell $E_T^{miss}$ distribution with that predicted by the two-component model for two pile-up scenarios. The magenta points extend the measured distribution using L1 $E_T^{miss} > 30\,$GeV and L1 $E_T^{miss} > 50\,$GeV data. The red curve is the prediction from the calorimeter-resolution part of the model. The green curve is the high $E_T^{miss}$ tail's probability distribution for the mean number of $pp$ interactions $\mu$ in each figure. The blue curve is the full model prediction computed by combining the $E_T^{miss}$ from these two individual sources shown in red and green, each calculated for $\mu=\langle\mu\rangle$. The black points show the unbiased $E_T^{miss}$ distribution measured in data. Corresponds to a prediction for $\langle\mu\rangle = 55$.

A comparison of the measured cell $E_T^{miss}$ distribution with that predicted by the two-component model for two pile-up scenarios. The magenta points extend the measured distribution using L1 $E_T^{miss} > 30\,$GeV and L1 $E_T^{miss} > 50\,$GeV data. The red curve is the prediction from the calorimeter-resolution part of the model. The green curve is the high $E_T^{miss}$ tail's probability distribution for the mean number of $pp$ interactions $\mu$ in each figure. The blue curve is the full model prediction computed by combining the $E_T^{miss}$ from these two individual sources shown in red and green, each calculated for $\mu=\langle\mu\rangle$. The black points show the unbiased $E_T^{miss}$ distribution measured in data. Corresponds to a prediction for $\langle\mu\rangle = 55$.

A comparison of the measured cell $E_T^{miss}$ distribution with that predicted by the two-component model for two pile-up scenarios. The magenta points extend the measured distribution using L1 $E_T^{miss} > 30\,$GeV and L1 $E_T^{miss} > 50\,$GeV data. The red curve is the prediction from the calorimeter-resolution part of the model. The green curve is the high $E_T^{miss}$ tail's probability distribution for the mean number of $pp$ interactions $\mu$ in each figure. The blue curve is the full model prediction computed by combining the $E_T^{miss}$ from these two individual sources shown in red and green, each calculated for $\mu=\langle\mu\rangle$. The black points show the unbiased $E_T^{miss}$ distribution measured in data. Corresponds to a prediction for $\langle\mu\rangle = 55$.

The $E_T^{miss}$ model predicted trigger rate as a function of $\mu$ for the cell $E_T^{miss}$ algorithm with a threshold of $80\,$GeV and $120\,$GeV, assuming no additional pile-up mitigation.

The L1 $E_T^{miss}$ trigger efficiency, shown as a function of $p_T(\mu\mu)$ in $Z\rightarrow\mu\mu$ events.

The efficiencies in the plot are shown for events satisfying a $Z\rightarrow\mu\mu$ selection and with $p_T(\mu\mu)$ larger than $150\,$GeV vs pile-up for each of the four years of data taking.

The L1 $E_T^{miss}$ trigger rate as a function of $\langle\mu\rangle$ for runs in three different periods ($\alpha$, $\beta$, $\gamma$) in the year 2017.

The L1 $E_T^{miss}$ trigger rate as a function of $\langle\mu\rangle$ for runs in three different periods ($\alpha$, $\beta$, $\gamma$) in the year 2017.

The L1 $E_T^{miss}$ trigger rate as a function of $\langle\mu\rangle$ for runs in three different periods ($\alpha$, $\beta$, $\gamma$) in the year 2017.

The L1 $E_T^{miss}$ trigger efficiency is shown as a function of mean pile-up for events satisfying a $Z\rightarrow\mu\mu$ selection and with $p_T(\mu\mu)$ larger than $150\,$GeV in three periods during the year 2017.

Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $0\leq\langle\mu\rangle < 20$.

Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $0\leq\langle\mu\rangle < 20$.

Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $0\leq\langle\mu\rangle < 20$.

Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $0\leq\langle\mu\rangle < 20$.

Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $0\leq\langle\mu\rangle < 20$.

Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $20\leq\langle\mu\rangle < 30$.

Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $20\leq\langle\mu\rangle < 30$.

Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $20\leq\langle\mu\rangle < 30$.

Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $20\leq\langle\mu\rangle < 30$.

Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $20\leq\langle\mu\rangle < 30$.

Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $30\leq\langle\mu\rangle < 40$.

Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $30\leq\langle\mu\rangle < 40$.

Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $30\leq\langle\mu\rangle < 40$.

Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $30\leq\langle\mu\rangle < 40$.

Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $30\leq\langle\mu\rangle < 40$.

Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $40\leq\langle\mu\rangle$.

Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $40\leq\langle\mu\rangle$.

Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $40\leq\langle\mu\rangle$.

Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $40\leq\langle\mu\rangle$.

Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $40\leq\langle\mu\rangle$.

Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.

Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.

Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.

Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.

Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.

Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.

Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.

Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.

Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.

Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.

Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.

Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.

Turn-on efficiency curves are shown for $Z\rightarrow\mu\mu$ events for three algorithms: the cell algorithm alone, the pufit algorithm alone and the combined cell+pufit algorithm. The thresholds are set such that the algorithms have equal rates, and the data were recorded in the year 2018. Here the trigger efficiency is shown with respect to $p_T(\mu\mu)$.

Turn-on efficiency curves are shown for $Z\rightarrow\mu\mu$ events for three algorithms: the cell algorithm alone, the pufit algorithm alone and the combined cell+pufit algorithm. The thresholds are set such that the algorithms have equal rates, and the data were recorded in the year 2018. Here the trigger efficiency is shown with respect to the offline $E_T^{miss}$ calculation with muons treated as being invisible.

Efficiencies for $Z\rightarrow\mu\mu$ events are shown for the L1 $E_T^{miss}>50\,$GeV trigger and for the complete L1+HLT trigger chain that also requires pufit > 110 GeV. Each is shown as a function of $\langle\mu\rangle$ for a $p_T(\mu\mu)$ threshold of 150 GeV.

Efficiencies for $Z\rightarrow\mu\mu$ events are shown for the L1 $E_T^{miss}>50\,$GeV trigger and for the complete L1+HLT trigger chain that also requires pufit > 110 GeV. Each is shown as a function of $\langle\mu\rangle$ for an offline $E_T^{miss}$ threshold of 150 GeV.

Efficiencies for $Z\rightarrow\mu\mu$ events are shown for the L1 $E_T^{miss}>50\,$GeV trigger and for the complete L1+HLT trigger chain that also requires pufit > 110 GeV. Each is shown as a function of $\langle\mu\rangle$ for an $p_T(\mu\mu)$ threshold of 175 GeV.

Efficiencies for $Z\rightarrow\mu\mu$ events are shown for the L1 $E_T^{miss}>50\,$GeV trigger and for the complete L1+HLT trigger chain that also requires pufit > 110 GeV. Each is shown as a function of $\langle\mu\rangle$ for an offline $E_T^{miss}$ threshold of 175 GeV.

HLT_xe70_mht trigger output rate as a function of $\langle\mu\rangle$ shown for an example run in year 2015.

HLT_xe90_mht trigger output rate as a function of $\langle\mu\rangle$ shown for an example run in year 2016.

HLT_xe110_mht trigger output rate as a function of $\langle\mu\rangle$ shown for an example run in year 2016.

HLT_xe110_pufit trigger output rate as a function of $\langle\mu\rangle$ shown for an example run in year 2017. This trigger included an implicit requirement of cell $E_T^{miss}>50\,$GeV.

HLT_xe110_pufit_xe65 trigger output rate as a function of $\langle\mu\rangle$ shown for an example run in year 2018.

HLT_xe110_pufit_xe70 trigger output rate as a function of $\langle\mu\rangle$ shown for an example run in year 2018.

Full-chain trigger efficiencies for each year as a function of $p_T(\mu\mu)$. The efficiency corresponds to that of the lowest unprescaled trigger that is adjusted throughout each year.

Full-chain trigger efficiencies for 2015, 2016, 2017 and 2018 as a function of $\langle\mu\rangle$ for $p_T(\mu\mu)>150$ GeV. The efficiency corresponds to that of the lowest unprescaled trigger that is adjusted throughout the year.

Efficiencies for the first-level trigger L1XE50 and the combined L1+HLT trigger chain HLT_xe110_pufit_xe65_L1XE50 in data recorded in the year 2018 are shown as a function of $\langle\mu\rangle$ for $W\rightarrow e\nu$ and $Z\rightarrow\mu\mu$ selections with offline $E_T^{miss}>150\,$GeV.

Efficiencies for the first-level trigger L1XE50 and the combined L1+HLT trigger chain HLT_xe110_pufit_xe65_L1XE50 in data recorded in the year 2018 are shown as a function of $\langle\mu\rangle$ for $t\bar t$ with offline $E_T^{miss}>150\,$GeV.

Efficiencies for the first-level trigger L1XE50 and the combined L1+HLT trigger chain HLT_xe110_pufit_xe65_L1XE50 in data recorded in the year 2018 are shown as a function of $\langle\mu\rangle$ for $W\rightarrow e\nu$ and $Z\rightarrow\mu\mu$ selections with offline $E_T^{miss}>175\,$GeV.

Efficiencies for the first-level trigger L1XE50 and the combined L1+HLT trigger chain HLT_xe110_pufit_xe65_L1XE50 in data recorded in the year 2018 are shown as a function of $\langle\mu\rangle$ for $t\bar t$ with offline $E_T^{miss}>175\,$GeV.

Xi pt spectrum in 20-40% multiplicity class.

Xi pt spectrum in 40-60% multiplicity class.

Xi pt spectrum in 60-80% multiplicity class.

Xi pt spectrum in 80-100% multiplicity class.

Omega pt spectrum in 0-5% multiplicity class.

Omega pt spectrum in 5-10% multiplicity class.

Omega pt spectrum in 10-20% multiplicity class.

Omega pt spectrum in 20-40% multiplicity class.

Omega pt spectrum in 40-60% multiplicity class.

Omega pt spectrum in 60-80% multiplicity class.

Omega pt spectrum in 80-100% multiplicity class.

Mean pT of XI- in p-Pb collisions with centre-of-mass energy/nucleon=5.02 TeV for each V0A multiplicity event class.

Mean pT of XIBAR+ in p-Pb collisions with centre-of-mass energy/nucleon=5.02 TeV for each V0A multiplicity event class.

Mean pT of OMEGA- in p-Pb collisions with centre-of-mass energy/nucleon=5.02 TeV for each V0A multiplicity event class.

Mean pT of OMEGABAR+ in p-Pb collisions with centre-of-mass energy/nucleon=5.02 TeV for each V0A multiplicity event class.

XiMinus yield as a function of charged particle multiplicity per unit pseudorapidity.

XiPlus yield as a function of charged particle multiplicity per unit pseudorapidity.

OmegaMinus yield as a function of charged particle multiplicity per unit pseudorapidity.

OmegaPlus yield as a function of charged particle multiplicity per unit pseudorapidity.

Xi/pi ratio as a function of charged particle multiplicity per unit pseudorapidity.

Omega/pi ratio as a function of charged particle multiplicity per unit pseudorapidity.

dN/dy and MEAN(PT) extracted from Levy-Tsallis fits to the measured PI, K, P spectra at mid-rapidity in inelastic pp collisions at SQRT(S) = 7 TeV. Combined statistical and systematic uncertainties (statistical uncertainties are negligible) are reported. The systematic uncertainty on dN/dy due to normalization to inelastic collisions (+7-4%) is not included. Integrated yields of Kaon/Pion and Proton/Pion ratios are also reported with combined statistical and systematic uncertainties (statistical uncertainties are negligible).

dN/dy and MEAN(PT) extracted from Levy-Tsallis fits to the measured PI, K, P spectra at mid-rapidity in inelastic pp collisions at SQRT(S) = 2.76 TeV. Combined statistical and systematic uncertainties (statistical uncertainties are negligible) are reported. The systematic uncertainty on dN/dy due to normalization to inelastic collisions (+6-4%) is not included. Integrated yields of Kaon/Pion and Proton/Pion ratios are also reported with combined statistical and systematic uncertainties (statistical uncertainties are negligible).

Forward-backward asymmetry, $N_{\ell}(+\eta_{\textrm{lab}})/ N_{\ell}(-\eta_{\textrm{lab}})$, for the negative leptons.

Forward-backward asymmetry, $N_{\ell}(+\eta_{\textrm{lab}})/ N_{\ell}(-\eta_{\textrm{lab}})$, for the positive leptons.

Forward-backward asymmetry, $N_{\ell}(+\eta_{\textrm{lab}})/ N_{\ell}(-\eta_{\textrm{lab}})$, for the charged-summed W bosons, as a function of the lepton pseudorapidity.

Ratio of the jet spectrum with a leading track $p_{\mathrm{T}}$ > 5 GeV/$c$ over the inclusive jet spectrum for $R=0.2$ in pp collisions at $\sqrt{s}=2.76$ TeV.

Ratios of jet spectra with different leading track $p_{\mathrm{T}}$ requirements ("$0$ over $5$", "$3$ over $5$", "$7$ over $5$" and "$10$ over $5$") for $R=0.2$ jets in 0-10% most central Pb-Pb collisions at $\sqrt{s_{\mathrm{NN}}}=2.76$ TeV.

$R_{\mathrm{AA}}$ for $R=0.2$ jets with the leading track requirement of $5$ GeV/$c$ in 0-10% most central Pb-Pb collisions at $\sqrt{s_{\mathrm{NN}}}=2.76$ TeV.

$R_{\mathrm{AA}}$ for $R=0.2$ jets with the leading track requirement of $5$ GeV/$c$ in 10-30% most central Pb-Pb collisions at $\sqrt{s_{\mathrm{NN}}}=2.76$ TeV.

Nuclear modification factor RAA of psi(2S) integrated over centrality, for the midrapidity and forward rapidity analysis bins.

Normalised differential TOP TOPBAR production cross section as a function of the number of additional jets with PT(JET) > 30 GeV in the lepton+jets channel. The total uncertainties are shown and include the statistical and systematic uncertainties.

Measured gap fraction in the dilepton channel as a function of the additional jet transverse momentum, GAPFRAC(PT) = N(PT)/N(TOTAL) where N(PT) is the number of events that do not contain additional jets above the given PT threshold.

Measured gap fraction in the dilepton channel as a function of the scalar sum of the transverse momentum of the additional jets, HT = SUM(PT(ADD. JETS)), GAPFRAC(HT) = N(HT)/N(TOTAL) where N(HT) is the number of events in which HT (with PT > 30 GeV) is less than the given threshold.

Transverse-momentum distributions of (K*(892)0 + anti-K*(892)0)/2 in Pb-Pb collisions at sqrt(sNN)=2.76 TeV, centrality 60.0-80.0%.

Transverse-momentum distributions of phi(1020) mesons in Pb-Pb collisions at sqrt(sNN)=2.76 TeV, centrality 0.0-5.0%.

Transverse-momentum distributions of phi(1020) mesons in Pb-Pb collisions at sqrt(sNN)=2.76 TeV, centrality 5.0-10.0%.

Transverse-momentum distributions of phi(1020) mesons in Pb-Pb collisions at sqrt(sNN)=2.76 TeV, centrality 0.0-10.0%.

Transverse-momentum distributions of phi(1020) mesons in Pb-Pb collisions at sqrt(sNN)=2.76 TeV, centrality 10.0-20.0%.

Transverse-momentum distributions of phi(1020) mesons in Pb-Pb collisions at sqrt(sNN)=2.76 TeV, centrality 20.0-30.0%.

Transverse-momentum distributions of phi(1020) mesons in Pb-Pb collisions at sqrt(sNN)=2.76 TeV, centrality 30.0-40.0%.

Transverse-momentum distributions of phi(1020) mesons in Pb-Pb collisions at sqrt(sNN)=2.76 TeV, centrality 40.0-50.0%.

Transverse-momentum distributions of phi(1020) mesons in Pb-Pb collisions at sqrt(sNN)=2.76 TeV, centrality 50.0-60.0%.

Transverse-momentum distributions of phi(1020) mesons in Pb-Pb collisions at sqrt(sNN)=2.76 TeV, centrality 60.0-70.0%.

Transverse-momentum distributions of phi(1020) mesons in Pb-Pb collisions at sqrt(sNN)=2.76 TeV, centrality 70.0-80.0%.

Transverse-momentum distributions of phi(1020) mesons in Pb-Pb collisions at sqrt(sNN)=2.76 TeV, centrality 80.0-90.0%.

Mass of K*(892)0 mesons (combined with the antiparticle) as a function of pT for central (0-20%, first y column) and peripheral (60-80%, second y column) Pb-Pb collisions at sqrt(sNN)=2.76 TeV.

Width of K*(892)0 mesons (combined with the antiparticle) as a function of pT for central (0-20%, first y column) and peripheral (60-80%, second y column) Pb-Pb collisions at sqrt(sNN)=2.76 TeV.

Mass of phi(2010) mesons as a function of pT for central (0-10%, first y column) and peripheral (70-80%, second y column) Pb-Pb collisions at sqrt(sNN)=2.76 TeV. UPDATE (27 JAN 2015): replaced with the final published values.

Width of phi(1020) mesons as a function of pT for central (0-10%, first y column) and peripheral (70-80%, second y column) Pb-Pb collisions at sqrt(sNN)=2.76 TeV.

Yield (dN/dy) of (K*(892)0 + anti-K*(892)0)/2 for different centrality intervals in Pb-Pb collisions at sqrt(sNN)=2.76 TeV. In the table, the first systematic uncertainty is uncorrelated between centrality intervals, the second is the normalization uncertainty.

Yield (dN/dy) of phi(1020) mesons for different centrality intervals in Pb-Pb collisions at sqrt(sNN)=2.76 TeV. In the table, the first systematic uncertainty is uncorrelated between centrality intervals and the second is the normalization uncertainty.

Ratio of pT-integrated yields (K*(892)0 + anti-K*(892)0)/(2K-) for different centrality intervals in Pb-Pb collisions at sqrt(sNN)=2.76 TeV. The K- yields are taken from PRC 88, 044910 (2013). In the paper this ratio is plotted as a function of the cube root of the mid-rapidity charged-particle multiplicity density (dNch/deta)^1/3 values taken from PRL 106, 032301 (2011).

Ratio of pT-integrated yields phi(1020)/K- for different centrality intervals in Pb-Pb collisions at sqrt(sNN)=2.76 TeV. The K- yields are taken from PRC 88, 044910 (2013). In the paper this ratio is plotted as a function of the cube root of the mid-rapidity charged-particle multiplicity density (dNch/deta)^1/3 values taken from PRL 106, 032301 (2011).

Mean transverse momentum of K*(892)0 mesons (combined with the antiparticle) for different centrality intervals in Pb-Pb collisions at sqrt(sNN)=2.76 TeV. In the paper this ratio is plotted as a function of the <Npart> values (the mean number of participant nucleons per collision) taken from PRC 88, 044909 (2013).

Mean transverse momentum of phi(1020) mesons for different centrality intervals in Pb-Pb collisions at sqrt(sNN)=2.76 TeV. In the paper this ratio is plotted as a function of the <Npart> values (the mean number of participant nucleons per collision) taken from PRC 88, 044909 (2013).

pT-dependent ratio (Omega- + anti-Omega+)/phi(1020) in Pb-Pb collisions at sqrt(sNN)=2.76 TeV, centrality 0.0-10.0%. The Omega pT distributions are taken from PLB 728, 216 (2013).

pT-dependent ratio (p + anti-p)/phi(1020) in Pb-Pb collisions at sqrt(sNN)=2.76 TeV, centrality 0.0-10.0%.

pT-dependent ratio (p + anti-p)/phi(1020) in Pb-Pb collisions at sqrt(sNN)=2.76 TeV, centrality 10.0-20.0%.

pT-dependent ratio (p + anti-p)/phi(1020) in Pb-Pb collisions at sqrt(sNN)=2.76 TeV, centrality 20.0-40.0%.

pT-dependent ratio (p + anti-p)/phi(1020) in Pb-Pb collisions at sqrt(sNN)=2.76 TeV, centrality 40.0-60.0%.

pT-dependent ratio (p + anti-p)/phi(1020) in Pb-Pb collisions at sqrt(sNN)=2.76 TeV, centrality 60.0-80.0%.

pT-dependent ratio (p + anti-p)/phi(1020) in Pb-Pb collisions at sqrt(sNN)=2.76 TeV, centrality 80.0-90.0%.

pT-dependent ratio phi(1020)/(pi+ + pi-) in Pb-Pb collisions at sqrt(sNN)=2.76 TeV, centrality 0.0-10.0%.

Enhancement ratio of phi(1020) for different centrality intervals in Pb-Pb collisions at sqrt(sNN)=2.76 TeV. The enhancement ratio is the ratio of the yield of a particle in A-A collisions to the yield of the particle in pp collisions, scaled by the average number of participant nucleons: Enhancement=[Yield(A-A)/<Npart(A-A)>]/[Yield(pp)/2]. The phi(1020) yield for pp collisions at sqrt(s)=2.76 TeV is interpolated between the measured yields at sqrt(s)=900 GeV and sqrt(s)=7 TeV. In the tables, the first systematic uncertainty is the uncorrelated uncertainty from the Pb-Pb data, the second is the normalization uncertainty from the Pb-Pb data, and the third is from the uncertainty in <Npart>. In the paper this ratio is plotted as a function of the <Npart> values taken from PRC 88, 044909 (2013).

Enhancement ratio of Lambda for different centrality intervals in Pb-Pb collisions at sqrt(sNN)=2.76 TeV. The enhancement ratio is the ratio of the yield of a particle in A-A collisions to the yield of the particle in pp collisions, scaled by the average number of participant nucleons: Enhancement=[Yield(A-A)/<Npart(A-A)>]/[Yield(pp)/2]. The Lambda yield for pp collisions at sqrt(s)=2.76 TeV is extrapolated from the measured yield at sqrt(s)=7 TeV. In the tables, the first systematic uncertainty is the uncertainty from the Pb-Pb data and the second is from the uncertainty in <Npart>. In the paper this ratio is plotted as a function of the <Npart> values taken from PRC 88, 044909 (2013).

Ratio of pT-integrated yields phi(1020)/(pi+ + pi-) for different centrality intervals in Pb-Pb collisions at sqrt(sNN)=2.76 TeV. The charged pion yields are taken from PRC 88, 044910 (2013). In the paper this ratio is plotted as a function of the <Npart> values taken from PRC 88, 044909 (2013).