Measured cross section in bins of $p_{\rm{T}}^{\rm{j}1}$.

Measured fractions in bins of $p_{\rm{T}}^{\rm{H}}$.

Measured fractions in bins of $|y^{\rm{H}}|$.

Measured fractions in bins of $N_{\rm{jets}}$.

Measured fractions in bins of $p_{\rm{T}}^{\rm{j1}}$.

Correlation matrix for the total uncertainty of the differential cross-section measurement in bins of $p_{\rm{T}}^{\rm{H}}$.

Correlation matrix for the total uncertainty of the differential cross-section measurement in bins of $|y^{\rm{H}}|$.

Correlation matrix for the total uncertainty of the differential cross-section measurement in bins of $N_{\rm{jets}}$.

Correlation matrix for the total uncertainty of the differential cross-section measurement in bins of $p_{\rm{T}}^{\rm{j1}}$.

Correlation matrix for the total uncertainty of the differential shape measurement in bins of $p_{\rm{T}}^{\rm{H}}$.

Correlation matrix for the total uncertainty of the differential shape measurement in bins of $|y^{\rm{H}}|$.

Correlation matrix for the total uncertainty of the differential shape measurement in bins of $N_{\rm{jets}}$.

Correlation matrix for the total uncertainty of the differential shape measurement in bins of $p_{\rm{T}}^{\rm{j1}}$.

The total $pp\to H$ cross section in the $H\to\gamma\gamma$ and $H\to ZZ^*\to 4\ell$ channels and their combination.

Vertex-level efficiency if no re-tracking is performed, as a function of the vertex radial position for an RPV SUSY model of squark production with $\tilde{q}\to q[\tilde{\chi}_1^0\to\mu qq]$, where $m(\tilde{q}) = 700$ GeV, $m(\tilde{\chi}_1^0) = 494$ GeV and $c\tau(\tilde{\chi}_1^0)$ = 175 mm. The result with re-tracking is tabulated in http://hepdata.cedar.ac.uk/view/ins1362183/d1.

Upper limits (95% CL) on the number of DV+muon displaced vertices in 20.3 fb$^{-1}$ and the corresponding vertex-level efficiencies (from Auxiliary Figure 7a) for four RPV SUSY models as a function of the $\tilde{\chi}_1^0$ proper decay distance $c\tau$. The models consider squark or gluino pair production, with masses in GeV as indicated, with either $\tilde{q}\to q[\tilde{\chi}_1^0\to\mu qq]$ or $\tilde{g}\to qq[\tilde{\chi}_1^0\to\mu qq]$ decays, respectively.

Upper limits (95% CL) on the number of DV+muon displaced vertices in 20.3 fb$^{-1}$ and the corresponding vertex-level efficiencies (from Auxiliary Figure 7b) for four RPV SUSY models as a function of the $\tilde{\chi}_1^0$ proper decay distance $c\tau$. The models consider squark or gluino pair production, with masses in GeV as indicated, with either $\tilde{q}\to q\tilde{\chi}_1^0$ or $\tilde{g}\to qq\tilde{\chi}_1^0$ decays, respectively.

Upper limits (95% CL) on the number of DV+electron displaced vertices in 20.3 fb$^{-1}$ and the corresponding vertex-level efficiencies (from Auxiliary Figure 7c) for four RPV SUSY models as a function of the $\tilde{\chi}_1^0$ proper decay distance $c\tau$. The models consider squark or gluino pair production, with masses in GeV as indicated, with either $\tilde{q}\to q[\tilde{\chi}_1^0\to e qq]$ or $\tilde{g}\to qq[\tilde{\chi}_1^0\to e qq]$ decays, respectively.

Upper limits (95% CL) on the number of DV+electron displaced vertices in 20.3 fb$^{-1}$ and the corresponding vertex-level efficiencies (from Auxiliary Figure 7d) for four RPV SUSY models as a function of the $\tilde{\chi}_1^0$ proper decay distance $c\tau$. The models consider squark or gluino pair production, with masses in GeV as indicated, with either $\tilde{q}\to q\tilde{\chi}_1^0$ or $\tilde{g}\to qq\tilde{\chi}_1^0$ decays, respectively.

Upper limits (95% CL) on the number of dilepton $e^+e^-$ displaced vertices in 20.3 fb$^{-1}$ and the corresponding vertex-level efficiencies (from Auxiliary Figure 5a) for four RPV SUSY models as a function of the $\tilde{\chi}_1^0$ proper decay distance $c\tau$. The models consider gluino pair production, with $\tilde{g}\to qq[\tilde{\chi}_1^0\to ee\nu]$ decays and masses in GeV as indicated. A dash indicates results omitted due to limited statistical precision.

Upper limits (95% CL) on the number of dilepton $e^{\pm}\mu^{\mp}$ displaced vertices in 20.3 fb$^{-1}$ and the corresponding vertex-level efficiencies (from Auxiliary Figure 5b) for four RPV SUSY models as a function of the $\tilde{\chi}_1^0$ proper decay distance $c\tau$. The models consider gluino pair production, with $\tilde{g}\to qq[\tilde{\chi}_1^0\to e\mu\nu]$ decays and masses in GeV as indicated.

Upper limits (95% CL) on the number of $\mu^+\mu^-$ displaced vertices in 20.3 fb$^{-1}$ and the corresponding vertex-level efficiencies (from Auxiliary Figure 5c) for four RPV SUSY models as a function of the $\tilde{\chi}_1^0$ proper decay distance $c\tau$. The models consider gluino pair production, with $\tilde{g}\to qq[\tilde{\chi}_1^0\to \mu\mu\nu]$ decays and masses in GeV as indicated. A dash indicates results omitted due to limited statistical precision.

Upper limits (95% CL) on the number of dilepton ($e^+e^-+e^{\pm}\mu^{\mp}+\mu^+\mu^-$) displaced vertices in 20.3 fb$^{-1}$ and the corresponding vertex-level efficiencies (from Auxiliary Figure 5d) for two GGM SUSY models as a function of the $\tilde{\chi}_1^0$ proper decay distance $c\tau$. The models consider gluino pair production, with $\tilde{g}\to qq[\tilde{\chi}_1^0\to Z\tilde{G}]$ decays, $m(\tilde{g})$ = 1100 GeV and $m(\tilde{\chi}_1^0)$ = 400 GeV.

Upper limits (95% CL) on the number of dilepton ($e^+e^-+e^{\pm}\mu^{\mp}+\mu^+\mu^-$) displaced vertices in 20.3 fb$^{-1}$ and the corresponding vertex-level efficiencies (from Auxiliary Figure 5d) for two GGM SUSY models as a function of the $\tilde{\chi}_1^0$ proper decay distance $c\tau$. The models consider gluino pair production, with $\tilde{g}\to qq[\tilde{\chi}_1^0\to Z\tilde{G}]$ decays, $m(\tilde{g})$ = 1100 GeV and $m(\tilde{\chi}_1^0)$ = 1000 GeV.

Upper limits (95% CL) from the dilepton $e^+e^-+e^{\pm}\mu^{\mp}$ channels on the production cross-section and the corresponding event-level efficiencies (from Auxiliary Figure 6a) for four RPV SUSY models as a function of the $\tilde{\chi}_1^0$ proper decay distance $c\tau$. The models consider gluino pair production, with $\tilde{g}\to qq[\tilde{\chi}_1^0\to e\mu\nu/ee\nu]$ decays and masses in GeV as indicated. For comparison, the production cross-sections for $m(\tilde{g})$ = 600 GeV and 1300 GeV are $1280\pm230$ fb and $1.7\pm0.7$ fb, respectively.

Upper limits (95% CL) from the dilepton $e^{\pm}\mu^{\mp}+\mu^+\mu^-$ channels on the production cross-section and the corresponding event-level efficiencies (from Auxiliary Figure 6b) for four RPV SUSY models as a function of the $\tilde{\chi}_1^0$ proper decay distance $c\tau$. The models consider gluino pair production, with $\tilde{g}\to qq[\tilde{\chi}_1^0\to e\mu\nu/\mu\mu\nu]$ decays and masses in GeV as indicated. For comparison, the production cross-sections for $m(\tilde{g})$ = 600 GeV and 1300 GeV are $1280\pm230$ fb and $1.7\pm0.7$ fb, respectively. A dash indicates results omitted due to limited statistical precision.

Upper limits (95% CL) from the dilepton $e^+e^-+e^{\pm}\mu^{\mp}+\mu^+\mu^-$ channels on the production cross-section and the corresponding event-level efficiencies (from Auxiliary Figure 6c) for two GGM SUSY models as a function of the $\tilde{\chi}_1^0$ proper decay distance $c\tau$. The models consider gluino pair production, with $\tilde{g}\to qq[\tilde{\chi}_1^0\to Z\tilde{G}]$ decays, $m(\tilde{g})$ = 1100 GeV and $m(\tilde{\chi}_1^0)$ = 400 GeV. For comparison, the production cross-section for $m(\tilde{g})$ = 1100 GeV is $7.6\pm2.8$ fb.

Upper limits (95% CL) from the dilepton $e^+e^-+e^{\pm}\mu^{\mp}+\mu^+\mu^-$ channels on the production cross-section and the corresponding event-level efficiencies (from Auxiliary Figure 6c) for two GGM SUSY models as a function of the $\tilde{\chi}_1^0$ proper decay distance $c\tau$. The models consider gluino pair production, with $\tilde{g}\to qq[\tilde{\chi}_1^0\to Z\tilde{G}]$ decays, $m(\tilde{g})$ = 1100 GeV and $m(\tilde{\chi}_1^0)$ = 1000 GeV. For comparison, the production cross-section for $m(\tilde{g})$ = 1100 GeV is $7.6\pm2.8$ fb.

Upper limits (95% CL) from the DV+jets channel on the production cross-section and the corresponding event-level efficiencies (from Auxiliary Figure 8a) for four RPV SUSY models as a function of the $\tilde{\chi}_1^0$ proper decay distance $c\tau$. The models consider squark pair production, with $\tilde{q}\to q\tilde{\chi}_1^0$ decays, $m(\tilde{q})$ = 700 GeV and $m(\tilde{\chi}_1^0)$ = 494 GeV. For comparison, the production cross-section for $m(\tilde{q})$ = 700 GeV is $124\pm17$ fb. A dash indicates where the limit-setting procedure did not converge.

Upper limits (95% CL) from the DV+jets channel on the production cross-section and the corresponding event-level efficiencies (from Auxiliary Figure 8b) for four RPV SUSY models as a function of the $\tilde{\chi}_1^0$ proper decay distance $c\tau$. The models consider squark pair production, with $\tilde{q}\to q\tilde{\chi}_1^0$ decays, $m(\tilde{q})$ = 1000 GeV and $m(\tilde{\chi}_1^0)$ = 108 GeV. For comparison, the production cross-section for $m(\tilde{q})$ = 1000 GeV is $11.9\pm1.5$ fb. A dash indicates where the limit-setting procedure did not converge.

Upper limits (95% CL) from the DV+$E_T^{miss}$ channel on the production cross-section and the corresponding event-level efficiencies (from Auxiliary Figure 9a) for two GGM SUSY models as a function of the $\tilde{\chi}_1^0$ proper decay distance $c\tau$. The models consider gluino pair production, with $\tilde{g}\to qq[\tilde{\chi}_1^0\to Z\tilde{G}]$ decays, $m(\tilde{g})$ = 1100 GeV and a $\tilde{\chi}_1^0$ mass in GeV as indicated. For comparison, the production cross-section for $m(\tilde{g})$ = 1100 GeV is $7.6\pm2.8$ fb.

Upper limits (95% CL) from the DV+jets channel on the production cross-section and the corresponding event-level efficiencies (from Auxiliary Figure 9b) for two GGM SUSY models as a function of the $\tilde{\chi}_1^0$ proper decay distance $c\tau$. The models consider gluino pair production, with $\tilde{g}\to qq[\tilde{\chi}_1^0\to Z\tilde{G}]$ decays, $m(\tilde{g})$ = 1100 GeV and a $\tilde{\chi}_1^0$ mass in GeV as indicated. For comparison, the production cross-section for $m(\tilde{g})$ = 1100 GeV is $7.6\pm2.8$ fb. A dash indicates where the limit-setting procedure did not converge.

Upper limits (95% CL) from the DV+$E_T^{miss}$ channel on the production cross-section and the corresponding event-level efficiencies (from Auxiliary Figure 10a) for four split-SUSY models as a function of the $\tilde{g}$ proper decay distance $c\tau$. The models consider gluino pair production, with $[\tilde{g}\to g/qq \tilde{\chi}_1^0]$ decays, $\tilde{g}$ masses in GeV as indicated and $m(\tilde{\chi}_1^0)$ = 100 GeV. For comparison, the production cross-sections for $m(\tilde{g})$ = 400 GeV, 800 GeV and 1400 GeV are $18700\pm2800$ fb, $149\pm31$ fb and $0.71\pm0.32$ fb, respectively.

Upper limits (95% CL) from the DV+jets channel on the production cross-section and the corresponding event-level efficiencies (from Auxiliary Figure 10b) for four split-SUSY models as a function of the $\tilde{g}$ proper decay distance $c\tau$. The models consider gluino pair production, with $[\tilde{g}\to g/qq \tilde{\chi}_1^0]$ decays, $\tilde{g}$ masses in GeV as indicated and $m(\tilde{\chi}_1^0)$ = 100 GeV. For comparison, the production cross-sections for $m(\tilde{g})$ = 400 GeV, 800 GeV and 1400 GeV are $18700\pm2800$ fb, $149\pm31$ fb and $0.71\pm0.32$ fb, respectively. A dash indicates where the limit-setting procedure did not converge or the limit is greater than $10^8$ fb.

Upper limits (95% CL) from the DV+$E_T^{miss}$ channel on the production cross-section and the corresponding event-level efficiencies (from Auxiliary Figure 10c) for three split-SUSY models as a function of the $\tilde{g}$ proper decay distance $c\tau$. The models consider gluino pair production, with $[\tilde{g}\to tt \tilde{\chi}_1^0]$ decays, $\tilde{g}$ masses in GeV as indicated and $m(\tilde{\chi}_1^0)$ = 100 GeV. For comparison, the production cross-sections for $m(\tilde{g})$ = 600 GeV, 1000 GeV and 1400 GeV are $1270\pm230$ fb, $22\pm6$ fb and $0.71\pm0.32$ fb, respectively.

Upper limits (95% CL) from the DV+jets channel on the production cross-section and the corresponding event-level efficiencies (from Auxiliary Figure 10d) for three split-SUSY models as a function of the $\tilde{g}$ proper decay distance $c\tau$. The models consider gluino pair production, with $[\tilde{g}\to tt \tilde{\chi}_1^0]$ decays, $\tilde{g}$ masses in GeV as indicated and $m(\tilde{\chi}_1^0)$ = 100 GeV. For comparison, the production cross-sections for $m(\tilde{g})$ = 600 GeV, 1000 GeV and 1400 GeV are $1270\pm230$ fb, $22\pm6$ fb and $0.71\pm0.32$ fb, respectively. A dash indicates where the limit-setting procedure did not converge.

Upper limits (95% CL) from the DV+$E_T^{miss}$ channel on the production cross-section and the corresponding event-level efficiencies (from Auxiliary Figure 10e) for four split-SUSY models as a function of the $\tilde{g}$ proper decay distance $c\tau$. The models consider gluino pair production, with $[\tilde{g}\to tt \tilde{\chi}_1^0]$ decays, $\tilde{g}$ masses in GeV as indicated and $m(\tilde{\chi}_1^0)$ = $m(\tilde{g}) - 480$ GeV. For comparison, the production cross-sections for $m(\tilde{g})$ = 500 GeV, 800 GeV and 1400 GeV are $4450\pm700$ fb, $149\pm31$ fb and $0.71\pm0.32$ fb, respectively.

Upper limits (95% CL) from the DV+jets channel on the production cross-section and the corresponding event-level efficiencies (from Auxiliary Figure 10f) for four split-SUSY models as a function of the $\tilde{g}$ proper decay distance $c\tau$. The models consider gluino pair production, with $[\tilde{g}\to tt \tilde{\chi}_1^0]$ decays, $\tilde{g}$ masses in GeV as indicated and $m(\tilde{\chi}_1^0)$ = $m(\tilde{g}) - 480$ GeV. For comparison, the production cross-sections for $m(\tilde{g})$ = 500 GeV, 800 GeV and 1400 GeV are $4450\pm700$ fb, $149\pm31$ fb and $0.71\pm0.32$ fb, respectively. A dash indicates where the limit-setting procedure did not converge.

Observed 95% CL exclusion contour in the $m(\tilde{g})$-$c\tau$ plane for the split-SUSY model with gluino production, $[\tilde{g}\to g/qq \tilde{\chi}_1^0]$ decays and $m(\tilde{\chi}_1^0)$ = 100 GeV. These results are obtained from the DV+$E_T^{miss}$ and DV+jets channels, see http://hepdata.cedar.ac.uk/view/ins1362183/d34 for details.

Expected 95% CL exclusion contour in the $m(\tilde{g})$-$c\tau$ plane for the split-SUSY model with gluino production, $[\tilde{g}\to g/qq \tilde{\chi}_1^0]$ decays and $m(\tilde{\chi}_1^0)$ = 100 GeV. These results are obtained from the DV+$E_T^{miss}$ and DV+jets channels, see http://hepdata.cedar.ac.uk/view/ins1362183/d34 for details.

Observed 95% CL exclusion contour in the $m(\tilde{g})$-$c\tau$ plane for the split-SUSY model with gluino production, $[\tilde{g}\to tt \tilde{\chi}_1^0]$ decays and $m(\tilde{\chi}_1^0)$ = 100 GeV. These results are obtained from the DV+$E_T^{miss}$ and DV+jets channels, see http://hepdata.cedar.ac.uk/view/ins1362183/d34 for details.

Expected 95% CL exclusion contour in the $m(\tilde{g})$-$c\tau$ plane for the split-SUSY model with gluino production, $[\tilde{g}\to tt \tilde{\chi}_1^0]$ decays and $m(\tilde{\chi}_1^0)$ = 100 GeV. These results are obtained from the DV+$E_T^{miss}$ and DV+jets channels, see http://hepdata.cedar.ac.uk/view/ins1362183/d34 for details.

Observed 95% CL exclusion contour in the $m(\tilde{g})$-$c\tau$ plane for the split-SUSY model with gluino production, $[\tilde{g}\to g/qq \tilde{\chi}_1^0]$ decays and $m(\tilde{\chi}_1^0)$ = $m(\tilde{g})$ - 480 GeV. These results are obtained from the DV+$E_T^{miss}$ and DV+jets channels, see http://hepdata.cedar.ac.uk/view/ins1362183/d34 for details.

Expected 95% CL exclusion contour in the $m(\tilde{g})$-$c\tau$ plane for the split-SUSY model with gluino production, $[\tilde{g}\to g/qq \tilde{\chi}_1^0]$ decays and $m(\tilde{\chi}_1^0)$ = $m(\tilde{g})$ - 480 GeV. These results are obtained from the DV+$E_T^{miss}$ and DV+jets channels, see http://hepdata.cedar.ac.uk/view/ins1362183/d34 for details.

Choice of signal region in the $m(\tilde{g})$-$c\tau$ plane for the split-SUSY models with gluino decays and neutralino masses in GeV as indicated. A value of 1 indicates that the DV+$E_T^{miss}$ channel provided the best expected constraint for that point, while a value of -1 indicates the DV+jets channel. A dash indicates where results were not calculated for a particular mass/lifetime combination.

Upper limits (95% CL) from the DV+$E_T^{miss}$ channel on the production cross-section and the corresponding event-level efficiencies (from Auxiliary Figure 11a) for four RPV SUSY models as a function of the $\tilde{\chi}_1^0$ proper decay distance $c\tau$. The models consider squark or gluino pair production, with masses in GeV as indicated, with either $\tilde{q}\to q[\tilde{\chi}_1^0\to \nu qq]$ or $\tilde{g}\to qq[\tilde{\chi}_1^0\to \nu qq]$ decays, respectively. For comparison, the production cross-sections for $m(\tilde{g})$ = 700 GeV, $m(\tilde{q})$ = 700 GeV and $m(\tilde{q})$ = 1000 GeV are $430\pm80$ fb, $124\pm17$ fb and $11.9\pm1.5$ fb, respectively.

Upper limits (95% CL) from the DV+$E_T^{miss}$ channel on the production cross-section and the corresponding event-level efficiencies (from Auxiliary Figure 11b) for four RPV SUSY models as a function of the $\tilde{\chi}_1^0$ proper decay distance $c\tau$. The models consider squark pair production, with $\tilde{q}\to q\tilde{\chi}_1^0$ decays and masses in GeV as indicated. For comparison, the production cross-sections for $m(\tilde{q})$ = 700 GeV and 1000 GeV are $124\pm17$ fb and $11.9\pm1.5$ fb, respectively.

Vertex mass distributions in data and one RPV SUSY signal model, for vertices with 3, 4 and $\geq$5 tracks in the DV+muon channel. The entries are the number of DVs in each bin, not normalized according to bin size. The signal model is for squark pair production, with $\tilde{q}\to q[\tilde{\chi}_1^0\to\mu qq]$ decays, $m(\tilde{q})$ = 700 GeV, $m(\tilde{\chi}_1^0)$ = 494 GeV and $c\tau(\tilde{\chi}_1^0)$ = 175 mm.

Vertex mass distributions in data and one GGM SUSY signal model, for vertices with 3, 4 and $\geq$5 tracks in the DV+jets channel. The entries are the number of DVs in each bin, not normalized according to bin size. The signal model is for gluino pair production, with $\tilde{g}\to qq[\tilde{\chi}_1^0\to Z\tilde{G}]$ decays, $m(\tilde{g})$ = 1100 GeV, $m(\tilde{\chi}_1^0)$ = 400 GeV and $c\tau(\tilde{\chi}_1^0)$ = 175 mm.

Vertex mass distributions in data and one RPV SUSY signal model, for vertices with 3, 4 and $\geq$5 tracks in the DV+electron channel. The entries are the number of DVs in each bin, not normalized according to bin size. The signal model is for squark pair production, with $\tilde{q}\to q[\tilde{\chi}_1^0\to e qq]$ decays, $m(\tilde{q})$ = 700 GeV, $m(\tilde{\chi}_1^0)$ = 494 GeV and $c\tau(\tilde{\chi}_1^0)$ = 175 mm.

Vertex mass distributions in data and one split-SUSY signal model, for vertices with 3, 4 and $\geq$5 tracks in the DV+$E_T^{miss}$ channel. The entries are the number of DVs in each bin, not normalized according to bin size. The signal model is for gluino pair production, with $[\tilde{g}\to g/qq \tilde{\chi}_1^0]$ decays, $m(\tilde{g})$ = 1400 GeV, $m(\tilde{\chi}_1^0)$ = 100 GeV and $c\tau(\tilde{g})$ = 175 mm.

Vertex mass distributions in data and one RPV SUSY signal model, for vertices with 0, 1 and $\geq$2 charged leptons in the dilepton $e^+e^-$ channel. The entries are the number of DVs in each bin, not normalized according to bin size. The signal model is for gluino pair production, with $\tilde{g}\to qq[\tilde{\chi}_1^0\to e\mu\nu/ee\nu]$ decays, $m(\tilde{g})$ = 1300 GeV, $m(\tilde{\chi}_1^0)$ = 50 GeV and $c\tau(\tilde{\chi}_1^0)$ = 30 mm.

Vertex mass distributions in data and one RPV SUSY signal model, for vertices with 0, 1 and $\geq$2 charged leptons in the dilepton $e^{\pm}\mu^{\mp}$ channel. The entries are the number of DVs in each bin, not normalized according to bin size. The signal model is for gluino pair production, with $\tilde{g}\to qq[\tilde{\chi}_1^0\to e\mu\nu/ee\nu]$ decays, $m(\tilde{g})$ = 1300 GeV, $m(\tilde{\chi}_1^0)$ = 50 GeV and $c\tau(\tilde{\chi}_1^0)$ = 30 mm.

Vertex mass distributions in data and one RPV SUSY signal model, for vertices with 0, 1 and $\geq$2 charged leptons in the dilepton $\mu^+\mu^-$ channel. The entries are the number of DVs in each bin, not normalized according to bin size. The signal model is for gluino pair production, with $\tilde{g}\to qq[\tilde{\chi}_1^0\to e\mu\nu/\mu\mu\nu]$ decays, $m(\tilde{g})$ = 1300 GeV, $m(\tilde{\chi}_1^0)$ = 50 GeV and $c\tau(\tilde{\chi}_1^0)$ = 30 mm.

Details of sparticle decay modes, model parameters, approximate number of generated events $N_{\rm evts}$ and total production cross-section $\sigma$ for selected models considered in this analysis. The long-lived particle (LLP) is the $\tilde{\chi}_1^0$ in all cases except for the model used for DV+$E_T^{miss}$, where it is the $\tilde{g}$. Events in some models are filtered to make better use of computing resources, details are given in the original table and the associated efficiency is already taken into account in the quoted cross-sections.

Numbers of events satisfying each selection criterion in turn for the DV+muon channel, using the model listed in http://hepdata.cedar.ac.uk/view/ins1362183/d44. The ''Filter and trigger'' line includes the requirements placed on the primary vertex.

Numbers of events satisfying each selection criterion in turn for the DV+electron channel, using the model listed in http://hepdata.cedar.ac.uk/view/ins1362183/d44. The ''Filter and trigger'' line includes the requirements placed on the primary vertex.

Numbers of events satisfying each selection criterion in turn for the DV+jets channel, using the model listed in http://hepdata.cedar.ac.uk/view/ins1362183/d44. The ''Filter and trigger'' line includes the requirements placed on the primary vertex.

Numbers of events satisfying each selection criterion in turn for the DV+$E_T^{miss}$ channel, using the model listed in http://hepdata.cedar.ac.uk/view/ins1362183/d44. The ''Filter and trigger'' line includes the requirements placed on the primary vertex.

Numbers of events satisfying each selection criterion in turn for the dilepton $e^+e^-$ channel, using the model listed in http://hepdata.cedar.ac.uk/view/ins1362183/d44. The ''Trigger'' line includes the event-level cosmic-muon veto and the requirements placed on the primary vertex, but not the offline filter selection. This is included in the ''Lepton reconstruction and DV match'' line, along with all other requirements placed on offline-reconstructed leptons. About 20,000 events of the full sample are analyzed, which contain an equal mixture of $\tilde{\chi}_1^0 \to e^{\pm}\mu^{\mp}\nu$ and $\tilde{\chi}_1^0 \to e^+e^-\nu$ decays.

Numbers of events satisfying each selection criterion in turn for the dilepton $e^{\pm}\mu^{\mp}$ channel, using the model listed in http://hepdata.cedar.ac.uk/view/ins1362183/d44. The ''Trigger'' line includes the event-level cosmic-muon veto and the requirements placed on the primary vertex, but not the offline filter selection. This is included in the ''Lepton reconstruction and DV match'' line, along with all other requirements placed on offline-reconstructed leptons. The sample contains about 50% $\tilde{\chi}_1^0 \to e^{\pm}\mu^{\mp}\nu$ decays, 25% $\tilde{\chi}_1^0 \to e^+e^-\nu$ and 25% $\tilde{\chi}_1^0 \to \mu^+\mu^-\nu$ decays.

Numbers of events satisfying each selection criterion in turn for the dilepton $\mu^+\mu^-$ channel, using the model listed in http://hepdata.cedar.ac.uk/view/ins1362183/d44. The ''Trigger'' line includes the event-level cosmic-muon veto and the requirements placed on the primary vertex, but not the offline filter selection. This is included in the ''Lepton reconstruction and DV match'' line, along with all other requirements placed on offline-reconstructed leptons. About 20,000 events of the full sample are analyzed, which contain an equal mixture of $\tilde{\chi}_1^0 \to e^{\pm}\mu^{\mp}\nu$ and $\tilde{\chi}_1^0 \to \mu^+\mu^-\nu$ decays.

Signal selection efficiency as a function of mA.

Expected +2 sigma uncertainty band exclusion limit for Type-I models, as a function of tan beta and cos(beta-alpha).

Expected +1 sigma uncertainty band exclusion limit for Type-I models, as a function of tan beta and cos(beta-alpha).

Expected exclusion limit for Type-I models, as a function of tan beta and cos(beta-alpha).

Expected -1 sigma uncertainty band exclusion limit for Type-I models, as a function of tan beta and cos(beta-alpha).

Expected -2 sigma uncertainty band exclusion limit for Type-I models, as a function of tan beta and cos(beta-alpha).

Observed exclusion limit for Type-I models, as a function of tan beta and cos(beta-alpha).

Expected +2 sigma uncertainty band exclusion limit for Type-II models, as a function of tan beta and cos(beta-alpha).

Expected +1 sigma uncertainty band exclusion limit for Type-II models, as a function of tan beta and cos(beta-alpha).

Expected exclusion limit for Type-II models, as a function of tan beta and cos(beta-alpha).

Expected -1 sigma uncertainty band exclusion limit for Type-II models, as a function of tan beta and cos(beta-alpha).

Expected -2 sigma uncertainty band exclusion limit for Type-II models, as a function of tan beta and cos(beta-alpha).

Observed exclusion limit for Type-II models, as a function of tan beta and cos(beta-alpha).

Observed limits on the pair production cross section as a function of mass for vector-like B quarks. These limits assume branching ratios given by the model where the B quark exists as a singlet.

Observed limits on the pair production cross section as a function of mass for vector-like T quarks. These limits assume branching ratios given by the model where the T quark exists as a singlet.

Expected and observed cross section limits as a function of mass on T_5/3 pair production.

Expected and observed cross section limits as a function of mass on T_5/3 pair production plus single production for $\lambda = 0.5$.

Expected and observed cross section limits as a function of mass on T_5/3 pair production plus single production for $\lambda = 1.0$.

Expected and observed limits for the sgluon pair-production cross section times branching ratio to four top quarks as a function of the sgluon mass.

Expected and observed limits on the four- top-quark production rate for the 2UED/RPP model in the symmetric case. The theory line corresponds to the production of four-top-quark events by tier (1, 1) with a branching ratio of A^(1,1) to tttt of 100%.

Charged-particle spectra in different centrality intervals for Pb+Pb.

Charged-particle spectra in different centrality intervals for Pb+Pb (not shown in Fig. 10).

Charged-particle spectra in different centrality intervals for Pb+Pb.

Charged-particle spectra in different centrality intervals for Pb+Pb (not shown in Fig. 10).

Charged-particle spectra in different centrality intervals for Pb+Pb.

Charged-particle spectra in different centrality intervals for Pb+Pb.

Charged-particle spectra in different eta intervals for pp.

Charged-particle spectra in different eta intervals for Pb+Pb.

Charged-particle spectra in different eta intervals for pp.

Charged-particle spectra in different eta intervals for Pb+Pb.

Charged-particle spectra in different eta intervals for pp.

Charged-particle spectra in different eta intervals for Pb+Pb.

Charged-particle spectra in different eta intervals for pp.

Charged-particle spectra in different eta intervals for Pb+Pb.

Charged-particle spectra in different eta intervals for pp.

Charged-particle spectra in different eta intervals for Pb+Pb.

Charged-particle spectra in different eta intervals for pp.

Charged-particle spectra in different eta intervals for Pb+Pb.

Charged-particle spectra in different eta intervals for pp.

Charged-particle spectra in different eta intervals for Pb+Pb.

Charged-particle spectra in different eta intervals for pp.

Charged-particle spectra in different eta intervals for Pb+Pb.

Rcp in different centrality intervals.

Rcp in different centrality intervals (not shown in Fig. 12).

Rcp in different centrality intervals.

Rcp in different centrality intervals (not shown in Fig. 12).

Rcp in different centrality intervals.

Rcp in different centrality intervals (not shown in Fig. 12).

Rcp in different centrality intervals.

Raa in different centrality intervals.

Raa in different centrality intervals (not shown in Fig. 13).

Raa in different centrality intervals.

Raa in different centrality intervals (not shown in Fig. 13).

Raa in different centrality intervals.

Raa in different centrality intervals (not shown in Fig. 13).

Raa in different centrality intervals.

Raa in different centrality intervals.

Raa in different eta intervals.

Raa in different eta intervals.

Raa in different eta intervals.

Raa in different eta intervals.

Raa in different eta intervals.

Raa in different eta intervals.

Raa in different eta intervals.

Raa in different eta intervals.

Raa.

Raa as a function of <Npart>.

Raa as a function of <Npart>.

Raa as a function of <Npart>.

Raa as a function of <Npart>.

Charged-particle spectra in different eta intervals for pp.

Charged-particle spectra in different eta intervals for Pb+Pb.

Charged-particle spectra in different eta intervals for Pb+Pb (not shown in Fig. 17).

Charged-particle spectra in different eta intervals for Pb+Pb.

Charged-particle spectra in different eta intervals for Pb+Pb (not shown in Fig. 17).

Charged-particle spectra in different eta intervals for Pb+Pb.

Charged-particle spectra in different eta intervals for Pb+Pb (not shown in Fig. 17).

Charged-particle spectra in different eta intervals for Pb+Pb.

Charged-particle spectra in different eta intervals for Pb+Pb.

Charged-particle spectra in different eta intervals for pp.

Charged-particle spectra in different eta intervals for Pb+Pb.

Charged-particle spectra in different eta intervals for Pb+Pb (not shown in Fig. 17).

Charged-particle spectra in different eta intervals for Pb+Pb.

Charged-particle spectra in different eta intervals for Pb+Pb (not shown in Fig. 17).

Charged-particle spectra in different eta intervals for Pb+Pb.

Charged-particle spectra in different eta intervals for Pb+Pb (not shown in Fig. 17).

Charged-particle spectra in different eta intervals for Pb+Pb.

Charged-particle spectra in different eta intervals for Pb+Pb.

Charged-particle spectra in different eta intervals for pp.

Charged-particle spectra in different eta intervals for Pb+Pb.

Charged-particle spectra in different eta intervals for Pb+Pb (not shown in Fig. 17).

Charged-particle spectra in different eta intervals for Pb+Pb.

Charged-particle spectra in different eta intervals for Pb+Pb (not shown in Fig. 17).

Charged-particle spectra in different eta intervals for Pb+Pb.

Charged-particle spectra in different eta intervals for Pb+Pb (not shown in Fig. 17).

Charged-particle spectra in different eta intervals for Pb+Pb.

Charged-particle spectra in different eta intervals for Pb+Pb.

Charged-particle spectra in different eta intervals for pp.

Charged-particle spectra in different eta intervals for Pb+Pb.

Charged-particle spectra in different eta intervals for Pb+Pb (not shown in Fig. 17).

Charged-particle spectra in different eta intervals for Pb+Pb.

Charged-particle spectra in different eta intervals for Pb+Pb (not shown in Fig. 17).

Charged-particle spectra in different eta intervals for Pb+Pb.

Charged-particle spectra in different eta intervals for Pb+Pb (not shown in Fig. 17).

Charged-particle spectra in different eta intervals for Pb+Pb.

Charged-particle spectra in different eta intervals for Pb+Pb.

Raa in different eta intervals.

Raa in different eta intervals (not shown in Fig. 18).

Raa in different eta intervals.

Raa in different eta intervals (not shown in Fig. 18).

Raa in different eta intervals.

Raa in different eta intervals (not shown in Fig. 18).

Raa in different eta intervals.

Raa in different eta intervals.

Raa in different eta intervals.

Raa in different eta intervals (not shown in Fig. 18).

Raa in different eta intervals.

Raa in different eta intervals (not shown in Fig. 18).

Raa in different eta intervals.

Raa in different eta intervals (not shown in Fig. 18).

Raa in different eta intervals.

Raa in different eta intervals.

Raa in different eta intervals.

Raa in different eta intervals (not shown in Fig. 18).

Raa in different eta intervals.

Raa in different eta intervals (not shown in Fig. 18).

Raa in different eta intervals.

Raa in different eta intervals (not shown in Fig. 18).

Raa in different eta intervals.

Raa in different eta intervals.

Raa in different eta intervals.

Raa in different eta intervals (not shown in Fig. 18).

Raa in different eta intervals.

Raa in different eta intervals (not shown in Fig. 18).

Raa in different eta intervals.

Raa in different eta intervals (not shown in Fig. 18).

Raa in different eta intervals.

Raa in different eta intervals.

Covariance matrix of total experimental uncertainties (statistical and systematic uncertainties added in quadrature) of absolute double differential fiducial cross section. The bin index is PT_i + 10*y_j.

Observed exclusion limits in the plane of DM particle mass and interaction scale, with the region below the solid curve excluded at a 90% CL. The background-only expectations are represented by their median (dashed line) and by the 68% and 95% CL bands. A lower bound of the validity of the EFT is indicated by the upper edge of the hatched area. The four curves, corresponding to different g and R values, represent the lower bound on $M_{*}$ for which 50% and 80% of signal events have a pair of DM particles with an invariant mass less than $g\sqrt{M_{*}^{3}/m_{t}}$, where $g = 4\pi$ and $g = 2\pi$ respectively.

$v_{5}$ data for various $q_2$ bins, Centrality 0-5%.

$v_{2}$ data for various $q_2$ bins, Centrality 5-10%.

$v_{3}$ data for various $q_2$ bins, Centrality 5-10%.

$v_{4}$ data for various $q_2$ bins, Centrality 5-10%.

$v_{5}$ data for various $q_2$ bins, Centrality 5-10%.

$v_{2}$ data for various $q_2$ bins, Centrality 10-15%.

$v_{3}$ data for various $q_2$ bins, Centrality 10-15%.

$v_{4}$ data for various $q_2$ bins, Centrality 10-15%.

$v_{5}$ data for various $q_2$ bins, Centrality 10-15%.

$v_{2}$ data for various $q_2$ bins, Centrality 15-20%.

$v_{3}$ data for various $q_2$ bins, Centrality 15-20%.

$v_{4}$ data for various $q_2$ bins, Centrality 15-20%.

$v_{5}$ data for various $q_2$ bins, Centrality 15-20%.

$v_{2}$ data for various $q_2$ bins, Centrality 20-25%.

$v_{3}$ data for various $q_2$ bins, Centrality 20-25%.

$v_{4}$ data for various $q_2$ bins, Centrality 20-25%.

$v_{5}$ data for various $q_2$ bins, Centrality 20-25%.

$v_{2}$ data for various $q_2$ bins, Centrality 25-30%.

$v_{3}$ data for various $q_2$ bins, Centrality 25-30%.

$v_{4}$ data for various $q_2$ bins, Centrality 25-30%.

$v_{5}$ data for various $q_2$ bins, Centrality 25-30%.

$v_{2}$ data for various $q_2$ bins, Centrality 30-35%.

$v_{3}$ data for various $q_2$ bins, Centrality 30-35%.

$v_{4}$ data for various $q_2$ bins, Centrality 30-35%.

$v_{5}$ data for various $q_2$ bins, Centrality 30-35%.

$v_{2}$ data for various $q_2$ bins, Centrality 35-40%.

$v_{3}$ data for various $q_2$ bins, Centrality 35-40%.

$v_{4}$ data for various $q_2$ bins, Centrality 35-40%.

$v_{5}$ data for various $q_2$ bins, Centrality 35-40%.

$v_{2}$ data for various $q_2$ bins, Centrality 40-45%.

$v_{3}$ data for various $q_2$ bins, Centrality 40-45%.

$v_{4}$ data for various $q_2$ bins, Centrality 40-45%.

$v_{5}$ data for various $q_2$ bins, Centrality 40-45%.

$v_{2}$ data for various $q_2$ bins, Centrality 45-50%.

$v_{3}$ data for various $q_2$ bins, Centrality 45-50%.

$v_{4}$ data for various $q_2$ bins, Centrality 45-50%.

$v_{5}$ data for various $q_2$ bins, Centrality 45-50%.

$v_{2}$ data for various $q_2$ bins, Centrality 50-55%.

$v_{3}$ data for various $q_2$ bins, Centrality 50-55%.

$v_{4}$ data for various $q_2$ bins, Centrality 50-55%.

$v_{5}$ data for various $q_2$ bins, Centrality 50-55%.

$v_{2}$ data for various $q_2$ bins, Centrality 55-60%.

$v_{3}$ data for various $q_2$ bins, Centrality 55-60%.

$v_{4}$ data for various $q_2$ bins, Centrality 55-60%.

$v_{5}$ data for various $q_2$ bins, Centrality 55-60%.

$v_{2}$ data for various $q_2$ bins, Centrality 60-65%.

$v_{3}$ data for various $q_2$ bins, Centrality 60-65%.

$v_{4}$ data for various $q_2$ bins, Centrality 60-65%.

$v_{5}$ data for various $q_2$ bins, Centrality 60-65%.

$v_{2}$ data for various $q_2$ bins, Centrality 65-70%.

$v_{3}$ data for various $q_2$ bins, Centrality 65-70%.

$v_{4}$ data for various $q_2$ bins, Centrality 65-70%.

$v_{5}$ data for various $q_2$ bins, Centrality 65-70%.

$v_{2}$ data for various $q_2$ bins, Centrality 0-10%.

$v_{3}$ data for various $q_2$ bins, Centrality 0-10%.

$v_{4}$ data for various $q_2$ bins, Centrality 0-10%.

$v_{5}$ data for various $q_2$ bins, Centrality 0-10%.

$v_{2}$ data for various $q_2$ bins, Centrality 10-20%.

$v_{3}$ data for various $q_2$ bins, Centrality 10-20%.

$v_{4}$ data for various $q_2$ bins, Centrality 10-20%.

$v_{5}$ data for various $q_2$ bins, Centrality 10-20%.

$v_{2}$ data for various $q_2$ bins, Centrality 20-30%.

$v_{3}$ data for various $q_2$ bins, Centrality 20-30%.

$v_{4}$ data for various $q_2$ bins, Centrality 20-30%.

$v_{5}$ data for various $q_2$ bins, Centrality 20-30%.

$v_{2}$ data for various $q_2$ bins, Centrality 30-40%.

$v_{3}$ data for various $q_2$ bins, Centrality 30-40%.

$v_{4}$ data for various $q_2$ bins, Centrality 30-40%.

$v_{5}$ data for various $q_2$ bins, Centrality 30-40%.

$v_{2}$ data for various $q_2$ bins, Centrality 40-50%.

$v_{3}$ data for various $q_2$ bins, Centrality 40-50%.

$v_{4}$ data for various $q_2$ bins, Centrality 40-50%.

$v_{5}$ data for various $q_2$ bins, Centrality 40-50%.

$v_{2}$ data for various $q_3$ bins, Centrality 0-5%.

$v_{3}$ data for various $q_3$ bins, Centrality 0-5%.

$v_{4}$ data for various $q_3$ bins, Centrality 0-5%.

$v_{5}$ data for various $q_3$ bins, Centrality 0-5%.

$v_{2}$ data for various $q_3$ bins, Centrality 5-10%.

$v_{3}$ data for various $q_3$ bins, Centrality 5-10%.

$v_{4}$ data for various $q_3$ bins, Centrality 5-10%.

$v_{5}$ data for various $q_3$ bins, Centrality 5-10%.

$v_{2}$ data for various $q_3$ bins, Centrality 10-15%.

$v_{3}$ data for various $q_3$ bins, Centrality 10-15%.

$v_{4}$ data for various $q_3$ bins, Centrality 10-15%.

$v_{5}$ data for various $q_3$ bins, Centrality 10-15%.

$v_{2}$ data for various $q_3$ bins, Centrality 15-20%.

$v_{3}$ data for various $q_3$ bins, Centrality 15-20%.

$v_{4}$ data for various $q_3$ bins, Centrality 15-20%.

$v_{5}$ data for various $q_3$ bins, Centrality 15-20%.

$v_{2}$ data for various $q_3$ bins, Centrality 20-25%.

$v_{3}$ data for various $q_3$ bins, Centrality 20-25%.

$v_{4}$ data for various $q_3$ bins, Centrality 20-25%.

$v_{5}$ data for various $q_3$ bins, Centrality 20-25%.

$v_{2}$ data for various $q_3$ bins, Centrality 25-30%.

$v_{3}$ data for various $q_3$ bins, Centrality 25-30%.

$v_{4}$ data for various $q_3$ bins, Centrality 25-30%.

$v_{5}$ data for various $q_3$ bins, Centrality 25-30%.

$v_{2}$ data for various $q_3$ bins, Centrality 30-35%.

$v_{3}$ data for various $q_3$ bins, Centrality 30-35%.

$v_{4}$ data for various $q_3$ bins, Centrality 30-35%.

$v_{5}$ data for various $q_3$ bins, Centrality 30-35%.

$v_{2}$ data for various $q_3$ bins, Centrality 35-40%.

$v_{3}$ data for various $q_3$ bins, Centrality 35-40%.

$v_{4}$ data for various $q_3$ bins, Centrality 35-40%.

$v_{5}$ data for various $q_3$ bins, Centrality 35-40%.

$v_{2}$ data for various $q_3$ bins, Centrality 40-45%.

$v_{3}$ data for various $q_3$ bins, Centrality 40-45%.

$v_{4}$ data for various $q_3$ bins, Centrality 40-45%.

$v_{5}$ data for various $q_3$ bins, Centrality 40-45%.

$v_{2}$ data for various $q_3$ bins, Centrality 45-50%.

$v_{3}$ data for various $q_3$ bins, Centrality 45-50%.

$v_{4}$ data for various $q_3$ bins, Centrality 45-50%.

$v_{5}$ data for various $q_3$ bins, Centrality 45-50%.

$v_{2}$ data for various $q_3$ bins, Centrality 50-55%.

$v_{3}$ data for various $q_3$ bins, Centrality 50-55%.

$v_{4}$ data for various $q_3$ bins, Centrality 50-55%.

$v_{5}$ data for various $q_3$ bins, Centrality 50-55%.

$v_{2}$ data for various $q_3$ bins, Centrality 55-60%.

$v_{3}$ data for various $q_3$ bins, Centrality 55-60%.

$v_{4}$ data for various $q_3$ bins, Centrality 55-60%.

$v_{5}$ data for various $q_3$ bins, Centrality 55-60%.

$v_{2}$ data for various $q_3$ bins, Centrality 60-65%.

$v_{3}$ data for various $q_3$ bins, Centrality 60-65%.

$v_{4}$ data for various $q_3$ bins, Centrality 60-65%.

$v_{5}$ data for various $q_3$ bins, Centrality 60-65%.

$v_{2}$ data for various $q_3$ bins, Centrality 65-70%.

$v_{3}$ data for various $q_3$ bins, Centrality 65-70%.

$v_{4}$ data for various $q_3$ bins, Centrality 65-70%.

$v_{5}$ data for various $q_3$ bins, Centrality 65-70%.

$v_{2}$ data for various $q_3$ bins, Centrality 0-10%.

$v_{3}$ data for various $q_3$ bins, Centrality 0-10%.

$v_{4}$ data for various $q_3$ bins, Centrality 0-10%.

$v_{5}$ data for various $q_3$ bins, Centrality 0-10%.

$v_{2}$ data for various $q_3$ bins, Centrality 10-20%.

$v_{3}$ data for various $q_3$ bins, Centrality 10-20%.

$v_{4}$ data for various $q_3$ bins, Centrality 10-20%.

$v_{5}$ data for various $q_3$ bins, Centrality 10-20%.

$v_{2}$ data for various $q_3$ bins, Centrality 20-30%.

$v_{3}$ data for various $q_3$ bins, Centrality 20-30%.

$v_{4}$ data for various $q_3$ bins, Centrality 20-30%.

$v_{5}$ data for various $q_3$ bins, Centrality 20-30%.

$v_{2}$ data for various $q_3$ bins, Centrality 30-40%.

$v_{3}$ data for various $q_3$ bins, Centrality 30-40%.

$v_{4}$ data for various $q_3$ bins, Centrality 30-40%.

$v_{5}$ data for various $q_3$ bins, Centrality 30-40%.

$v_{2}$ data for various $q_3$ bins, Centrality 40-50%.

$v_{3}$ data for various $q_3$ bins, Centrality 40-50%.

$v_{4}$ data for various $q_3$ bins, Centrality 40-50%.

$v_{5}$ data for various $q_3$ bins, Centrality 40-50%.

$v_{2}$ - $v_{2}$ inclusive correlation in 5% centrality intervals.

$v_{2}$ - $v_{2}$ correlation within each centrality.

$v_{2}$ - $v_{2}$ inclusive correlation in 5% centrality intervals.

$v_{2}$ - $v_{2}$ correlation within each centrality.

$v_{2}$ - $v_{2}$ inclusive correlation in 5% centrality intervals.

$v_{2}$ - $v_{2}$ correlation within each centrality.

$v_{2}$ - $v_{2}$ inclusive correlation in 5% centrality intervals.

$v_{2}$ - $v_{2}$ correlation within each centrality.

$v_{2}$ - $v_{2}$ inclusive correlation in 5% centrality intervals.

$v_{2}$ - $v_{2}$ correlation within each centrality.

$v_{3}$ - $v_{3}$ inclusive correlation in 5% centrality intervals.

$v_{3}$ - $v_{3}$ correlation within each centrality.

$v_{3}$ - $v_{3}$ inclusive correlation in 5% centrality intervals.

$v_{3}$ - $v_{3}$ correlation within each centrality.

$v_{3}$ - $v_{3}$ inclusive correlation in 5% centrality intervals.

$v_{3}$ - $v_{3}$ correlation within each centrality.

$v_{3}$ - $v_{3}$ inclusive correlation in 5% centrality intervals.

$v_{3}$ - $v_{3}$ correlation within each centrality.

$v_{2}$ - $v_{3}$ inclusive correlation in 5% centrality intervals.

$v_{2}$ - $v_{3}$ correlation for various q2 bins within each centrality.

$v_{2}$ - $v_{3}$ inclusive correlation in 5% centrality intervals.

$v_{2}$ - $v_{3}$ correlation for various q2 bins within each centrality.

$v_{2}$ - $v_{3}$ inclusive correlation in 5% centrality intervals.

$v_{2}$ - $v_{3}$ correlation for various q2 bins within each centrality.

$v_{2}$ - $v_{3}$ inclusive correlation in 5% centrality intervals.

$v_{2}$ - $v_{3}$ correlation for various q2 bins within each centrality.

linear fit result of $v_{2}$ - $v_{3}$ correlation within each centrality.

$v_{3}$ - $v_{2}$ inclusive correlation in 5% centrality intervals.

$v_{3}$ - $v_{2}$ correlation for various q3 bins within each centrality.

$v_{3}$ - $v_{2}$ inclusive correlation in 5% centrality intervals.

$v_{3}$ - $v_{2}$ correlation for various q3 bins within each centrality.

$v_{3}$ - $v_{2}$ inclusive correlation in 5% centrality intervals.

$v_{3}$ - $v_{2}$ correlation for various q3 bins within each centrality.

$v_{3}$ - $v_{2}$ inclusive correlation in 5% centrality intervals.

$v_{3}$ - $v_{2}$ correlation for various q3 bins within each centrality.

$v_{2}$ - $v_{4}$ inclusive correlation in 5% centrality intervals.

$v_{2}$ - $v_{4}$ correlation for various q2 bins within each centrality.

$v_{2}$ - $v_{4}$ inclusive correlation in 5% centrality intervals.

$v_{2}$ - $v_{4}$ correlation for various q2 bins within each centrality.

$v_{2}$ - $v_{4}$ inclusive correlation in 5% centrality intervals.

$v_{2}$ - $v_{4}$ correlation for various q2 bins within each centrality.

$v_{2}$ - $v_{4}$ inclusive correlation in 5% centrality intervals.

$v_{2}$ - $v_{4}$ correlation for various q2 bins within each centrality.

$v_{3}$ - $v_{4}$ inclusive correlation in 5% centrality intervals.

$v_{3}$ - $v_{4}$ correlation within each centrality.

$v_{3}$ - $v_{4}$ inclusive correlation in 5% centrality intervals.

$v_{3}$ - $v_{4}$ correlation within each centrality.

$v_4$ decomposed into linear and nonlinear contributions based on q2 event-shape selection.

$v_4$ decomposed into linear and nonlinear contributions based on q2 event-shape selection.

$v_4$ decomposed into linear and nonlinear contributions based on q2 event-shape selection.

$v_4$ decomposed into linear and nonlinear contributions based on q2 event-shape selection.

$v_4$ decomposed into linear and nonlinear contributions based on q2 event-shape selection.

$v_5$ decomposed into linear and nonlinear contributions based on q2 event-shape selection.

$v_5$ decomposed into linear and nonlinear contributions based on q3 event-shape selection.

RMS eccentricity scaled v_n.

RMS eccentricity scaled v_n.

$v_{2}$ - $v_{5}$ inclusive correlation in 5% centrality intervals.

$v_{2}$ - $v_{5}$ correlation for various q2 bins within each centrality.

$v_{3}$ - $v_{5}$ inclusive correlation in 5% centrality intervals.

$v_{3}$ - $v_{5}$ correlation for various q2 bins within each centrality.