Charged-particle multiplicities in proton-proton collisions at a centre-of mass energy of 13000 GeV as a function of transverse momentum for events with the number of charged particles >=2 having transverse momentum >100 MeV and absolute(pseudorapidity) <2.5.

Charged-particle multiplicity distribution in proton-proton collisions at a centre-of mass energy of 13000 GeV for events with the number of charged particles >=2 having transverse momentum >100 MeV and absolute(pseudorapidity) <2.5.

Average transverse momentum in proton-proton collisions at a centre-of mass energy of 13000 GeV as a function of the number of charged particles in the event for events with the number of charged particles >=2 having transverse momentum >100 MeV and absolute(pseudorapidity) <2.5.

Extrapolated ($\tau > 30$ ps) charged-particle multiplicities in proton-proton collisions at a centre-of mass energy of 13000 GeV as a function of pseudorapidity for events with the number of charged particles >=2 having transverse momentum >100 MeV and absolute(pseudorapidity) <2.5.

Extrapolated ($\tau > 30$ ps) charged-particle multiplicities in proton-proton collisions at a centre-of mass energy of 13000 GeV as a function of transverse momentum for events with the number of charged particles >=2 having transverse momentum >100 MeV and absolute(pseudorapidity) <2.5.

Extrapolated ($\tau > 30$ ps) charged-particle multiplicity distributions in proton-proton collisions at a centre-of mass energy of 13000 GeV for events with the number of charged particles >=2 having transverse momentum >100 MeV and absolute(pseudorapidity) <2.5.

Extrapolated ($\tau > 30$ ps) average transverse momentum in proton-proton collisions at a centre-of mass energy of 13000 GeV as a function of the number of charged particles in the event for events with the number of charged particles >=2 having transverse momentum >100 MeV and absolute(pseudorapidity) <2.5.

pT-differential cross section of inclusive Dzero mesons in p-Pb collisions at sqrt{sNN}=5.02 TeV in the rapidity interval -0.96<y<0.04. Branching ratio of D0->Kpi : 0.0388.

pT-differential cross section of prompt Dzero mesons in p-Pb collisions at sqrt{sNN}=5.02 TeV in the rapidity interval -0.96<y<0.04. Branching ratio of D0->Kpi : 0.0388. Data points for pt<2 GeV/c from analysis "without vertexing". Data points for pt>2 GeV/c from the analysis "with vertexing" taken from PRL 113 (2014) 232301 (http://hepdata.cedar.ac.uk/view/ins1296081).

First column: production cross sections per unit of rapidity for prompt D0 mesons, inclusive D0 mesons (no feed-down subtraction) and charm quarks in -0.96 < ycm < 0.04 in p-Pb collisions at 5.02 TeV. For D0 mesons, the second (sys) error is from the luminosity uncertainty, the third (sys) error is from the branching-ratio uncertainties. For charm quarks, the second (sys) error is from the luminosity uncertainty, the third (sys) error is from the Fragmentation Function uncertainties, the fourth (sys) error is from the rapidity shapes of D0 mesons and single charm quarks. Second column: value of <pT> of prompt D0 mesons in p-Pb collisions at 5.02 TeV in the rapidity interval -0.96 < y < 0.04. The first uncertainty is statistical, the second is the systematic uncertainty.

Ratio of D+ to D0 meson yield in p-Pb collisions at sqrt{sNN}=5.02 TeV in -0.96<y< 0.04 as a function of pT. Branching ratio of D+->Kpipi : 0.0913. Branching ratio of D0->Kpi : 0.0388.

Ratio of D*+ to D0 meson yield in p-Pb collisions at sqrt{sNN}=5.02 TeV in -0.96<y< 0.04 as a function of pT. Branching ratio of D*+->D0pi->Kpipi : 0.0388*0.677. Branching ratio of D0->Kpi : 0.0388.

Ratio of Ds to D0 meson yield in p-Pb collisions at sqrt{sNN}=5.02 TeV in -0.96<y< 0.04 as a function of pT. Branching ratio of Ds->phipi->KKpi : 0.0224. Branching ratio of D0->Kpi : 0.0388.

Ratio of Ds to D+ meson yield in p-Pb collisions at sqrt{sNN}=5.02 TeV in -0.96<y< 0.04 as a function of pT. Branching ratio of Ds->phipi->KKpi : 0.0224. Branching ratio of D+->Kpipi : 0.0913.

cross section of prompt Dzero mesons in p-Pb collisions at sqrt{sNN}=5.02 TeV vs rapidity in the pt interval 2<pt<5 GeV/c. Branching ratio of D0->Kpi : 0.0388. The second (sys) error is the systematic uncertainty from the B feed-down contribution. The first (sys) error is the systematic uncertainty from the other sources.

cross section of prompt Dzero mesons in p-Pb collisions at sqrt{sNN}=5.02 TeV vs rapidity in the pt interval 5<pt<8 GeV/c. Branching ratio of D0->Kpi : 0.0388. The second (sys) error is the systematic uncertainty from the B feed-down contribution. The first (sys) error is the systematic uncertainty from the other sources.

cross section of prompt Dzero mesons in p-Pb collisions at sqrt{sNN}=5.02 TeV vs rapidity in the pt interval 8<pt<16 GeV/c. Branching ratio of D0->Kpi : 0.0388. The second (sys) error is the systematic uncertainty from the B feed-down contribution. The first (sys) error is the systematic uncertainty from the other sources.

cross section of prompt Dplus mesons in p-Pb collisions at sqrt{sNN}=5.02 TeV vs rapidity in the pt interval 2<pt<5 GeV/c. Branching ratio of D+->Kpipi : 0.0913. The second (sys) error is the systematic uncertainty from the B feed-down contribution. The first (sys) error is the systematic uncertainty from the other sources.

cross section of prompt Dplus mesons in p-Pb collisions at sqrt{sNN}=5.02 TeV vs rapidity in the pt interval 5<pt<8 GeV/c. Branching ratio of D+->Kpipi : 0.0913. The second (sys) error is the systematic uncertainty from the B feed-down contribution. The first (sys) error is the systematic uncertainty from the other sources.

cross section of prompt Dplus mesons in p-Pb collisions at sqrt{sNN}=5.02 TeV vs rapidity in the pt interval 8<pt<16 GeV/c. Branching ratio of D+->Kpipi : 0.0913. The second (sys) error is the systematic uncertainty from the B feed-down contribution. The first (sys) error is the systematic uncertainty from the other sources.

cross section of prompt Dstar mesons in p-Pb collisions at sqrt{sNN}=5.02 TeV vs rapidity in the pt interval 2<pt<5 GeV/c. Branching ratio of D*+->D0pi->Kpipi : 0.0388*0.677. The second (sys) error is the systematic uncertainty from the B feed-down contribution. The first (sys) error is the systematic uncertainty from the other sources.

cross section of prompt Dstar mesons in p-Pb collisions at sqrt{sNN}=5.02 TeV vs rapidity in the pt interval 5<pt<8 GeV/c. Branching ratio of D*+->D0pi->Kpipi : 0.0388*0.677. The second (sys) error is the systematic uncertainty from the B feed-down contribution. The first (sys) error is the systematic uncertainty from the other sources.

cross section of prompt Dstar mesons in p-Pb collisions at sqrt{sNN}=5.02 TeV vs rapidity in the pt interval 8<pt<16 GeV/c. Branching ratio of D*+->D0pi->Kpipi : 0.0388*0.677. The second (sys) error is the systematic uncertainty from the B feed-down contribution. The first (sys) error is the systematic uncertainty from the other sources.

Nuclear modification factor RpPb of D0 mesons in p-Pb collisions at sqrt{sNN}=5.02 TeV in -0.96<y<0.04 as a function of pT. Data point for 0<pt<1 GeV/c from analysis "without vertexing". Data points for pt>1 GeV/c from the analysis "with vertexing" taken from PRL 113 (2014) 232301 (http://hepdata.cedar.ac.uk/view/ins1296081).

Pt-integrated nuclear modification factor RpA of prompt D0 mesons in -0.96 < ycm < 0.04. The first error is the statistical uncertainty, the second is the systematic uncertainty.

$R_{pPb}$ as a function of $p_{T}$ integrated over rapidity range $-1.8<y*<1.3$ for the 0--90% centrality interval for the three geometric models: (a) Glauber, (b) Glauber-Gribov with $\omega_{\sigma}=0.11$ and (c) Glauber-Gribov with $\omega_{\sigma}=0.2$.

$R_{pPb}$ values as a function of $p_{T}$ in the 0--90% centrality interval averaged over $|y*|<0.5$.The $\langle T_{Pb} \rangle$ value for the ATLAS centrality correction is calculated with the Glauber model. The total systematic uncertainties, which include the uncertainty in $\langle T_{Pb} \rangle$, are indicated by lines of the same colour. Strict quantitative agreement is not expected as each measurement uses different rapidity intervals for the centrality determination and apply different event selection criteria to reject diffractive collisions.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields integrated over $-1.8<y*<1.3$ for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields integrated over $-1.8<y*<1.3$ for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields integrated over $-1.8<y*<1.3$ for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{CP}$ as a function of $p_{T}$ extracted from the invariant yields integrated over $|\eta|<2.3$ for seven centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{CP}$ as a function of $p_{T}$ extracted from the invariant yields integrated over $|\eta|<2.3$ for seven centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{CP}$ as a function of $p_{T}$ extracted from the invariant yields integrated over $|\eta|<2.3$ for seven centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $p_{T}$ extracted from the invariant yields for six rapidity ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

$R_{pPb}$ as a function of $y*$ extracted from the invariant yields for eight $p_{T}$ ranges, for eight centrality intervals, and for different geometrical models used to calculate $\langle T_{Pb} \rangle$.

NLO cross sections and selection efficiencies (assuming $\beta$ = 1) for different signal points.

Interpretation of results in the T1tttt model. The colored regions show the upper limits (95\% CL) on the production cross section for $pp\rightarrow \tilde{g}\tilde{g},\tilde{g}\rightarrow t\bar{t}\tilde{\chi}^0_1$ in the $m_{\tilde{g}}$-$m_{\tilde{\chi}^0_1}$ plane.

Interpretation of results in the T1tttt model. The colored regions show the upper limits (95\% CL) on the production cross section for $pp\rightarrow \tilde{g}\tilde{g},\tilde{g}\rightarrow t\bar{t}\tilde{\chi}^0_1$ in the $m_{\tilde{g}}$-$m_{\tilde{\chi}^0_1}$ plane. The curve shows the observed limit on the corresponding SUSY particle masses obtained by comparing the excluded cross section with theoretical cross sections.

Interpretation of results in the T1tttt model. The colored regions show the upper limits (95\% CL) on the production cross section for $pp\rightarrow \tilde{g}\tilde{g},\tilde{g}\rightarrow t\bar{t}\tilde{\chi}^0_1$ in the $m_{\tilde{g}}$-$m_{\tilde{\chi}^0_1}$ plane. The curve shows the observed limit on the corresponding SUSY particle masses obtained by comparing the excluded cross section with $+1\sigma$ theoretical cross sections.

Interpretation of results in the T1tttt model. The colored regions show the upper limits (95\% CL) on the production cross section for $pp\rightarrow \tilde{g}\tilde{g},\tilde{g}\rightarrow t\bar{t}\tilde{\chi}^0_1$ in the $m_{\tilde{g}}$-$m_{\tilde{\chi}^0_1}$ plane. The curve shows the observed limit on the corresponding SUSY particle masses obtained by comparing the excluded cross section with $-1\sigma$ theoretical cross sections.

Interpretation of results in the T1tttt model. The colored regions show the upper limits (95\% CL) on the production cross section for $pp\rightarrow \tilde{g}\tilde{g},\tilde{g}\rightarrow t\bar{t}\tilde{\chi}^0_1$ in the $m_{\tilde{g}}$-$m_{\tilde{\chi}^0_1}$ plane. The curve shows the expected limit on the corresponding SUSY particle masses obtained by comparing the excluded cross section with theoretical cross sections.

Interpretation of results in the T1tttt model. The colored regions show the upper limits (95\% CL) on the production cross section for $pp\rightarrow \tilde{g}\tilde{g},\tilde{g}\rightarrow t\bar{t}\tilde{\chi}^0_1$ in the $m_{\tilde{g}}$-$m_{\tilde{\chi}^0_1}$ plane. The curve shows the expected limit on the corresponding SUSY particle masses corresponding to a $+1\sigma$ variation of the experimental uncertainty.

Interpretation of results in the T1tttt model. The colored regions show the upper limits (95\% CL) on the production cross section for $pp\rightarrow \tilde{g}\tilde{g},\tilde{g}\rightarrow t\bar{t}\tilde{\chi}^0_1$ in the $m_{\tilde{g}}$-$m_{\tilde{\chi}^0_1}$ plane. The curve shows the expected limit on the corresponding SUSY particle masses corresponding to a $-1\sigma$ variation of the experimental uncertainty.

Observed excluded region (95\% CL), shown in blue, in the $m_{\tilde{g}}$-$m_{\tilde{\chi}^0_1}$ plane for a model combining T5tttt, gluino pair production, followed by gluino decay to an on-shell top squark, together with a model for direct top squark pair production. The top squarks decay via the two-body process $\tilde{t}\rightarrow t\tilde{\chi}^0_1$. The neutralino and top squark masses are related by the constraint $m_{\tilde{t}} = m_{\tilde{\chi}^0_1} + 175$ GeV.

Expected excluded region (95\% CL), shown in blue, in the $m_{\tilde{g}}$-$m_{\tilde{\chi}^0_1}$ plane for a model combining T5tttt, gluino pair production, followed by gluino decay to an on-shell top squark, together with a model for direct top squark pair production. The top squarks decay via the two-body process $\tilde{t}\rightarrow t\tilde{\chi}^0_1$. The neutralino and top squark masses are related by the constraint $m_{\tilde{t}} = m_{\tilde{\chi}^0_1} + 175$ GeV.

Inclusive Jet Cross Section for |rapidity| 1.5 TO 2.0 as a function of the jet transverse momentum. Jets are clustered with the anti-kt algorithm ( R = 0.7). The (sys) error is the total systematic error, including the luminosity uncertainty of 2.7%.

Inclusive Jet Cross Section for |rapidity| 2.0 TO 2.5 as a function of the jet transverse momentum. Jets are clustered with the anti-kt algorithm ( R = 0.7). The (sys) error is the total systematic error, including the luminosity uncertainty of 2.7%.

Inclusive Jet Cross Section for |rapidity| 2.5 TO 3.0 as a function of the jet transverse momentum. Jets are clustered with the anti-kt algorithm ( R = 0.7). The (sys) error is the total systematic error, including the luminosity uncertainty of 2.7%.

Inclusive Jet Cross Section for |rapidity| 3.2 TO 4.7 as a function of the jet transverse momentum. Jets are clustered with the anti-kt algorithm ( R = 0.7). The (sys) error is the total systematic error, including the luminosity uncertainty of 2.7%.

Inclusive Jet Cross Section for |rapidity| < 0.5 as a function of the jet transverse momentum. Jets are clustered with the anti-kt algorithm ( R = 0.4). The (sys) error is the total systematic error, including the luminosity uncertainty of 2.7%.

Inclusive Jet Cross Section for |rapidity| 0.5 TO 1.0 as a function of the jet transverse momentum. Jets are clustered with the anti-kt algorithm ( R = 0.4). The (sys) error is the total systematic error, including the luminosity uncertainty of 2.7%.

Inclusive Jet Cross Section for |rapidity| 1.0 TO 1.5 as a function of the jet transverse momentum. Jets are clustered with the anti-kt algorithm ( R = 0.4). The (sys) error is the total systematic error, including the luminosity uncertainty of 2.7%.

Inclusive Jet Cross Section for |rapidity| 1.5 TO 2.0 as a function of the jet transverse momentum. Jets are clustered with the anti-kt algorithm ( R = 0.4). The (sys) error is the total systematic error, including the luminosity uncertainty of 2.7%.

Inclusive Jet Cross Section for |rapidity| 2.0 TO 2.5 as a function of the jet transverse momentum. Jets are clustered with the anti-kt algorithm ( R = 0.4). The (sys) error is the total systematic error, including the luminosity uncertainty of 2.7%.

Inclusive Jet Cross Section for |rapidity| 2.5 TO 3.0 as a function of the jet transverse momentum. Jets are clustered with the anti-kt algorithm ( R = 0.4). The (sys) error is the total systematic error, including the luminosity uncertainty of 2.7%.

Inclusive Jet Cross Section for |rapidity| 3.2 TO 4.7 as a function of the jet transverse momentum. Jets are clustered with the anti-kt algorithm ( R = 0.4). The (sys) error is the total systematic error, including the luminosity uncertainty of 2.7%.

Observed and expected background and signal effective mass distributions for SR2jl. For signal, a squark direct decay model with $m(\tilde q)=800$ GeV and $m(\tilde\chi^0_1)=400$ GeV is shown.

Observed and expected background and signal effective mass distributions for SR2jm. For signal, a gluino direct decay model with $m(\tilde g)=750$ GeV and $m(\tilde\chi^0_1)=660$ GeV is shown.

Observed and expected background and signal effective mass distributions for SR2jt. For signal, a squark direct decay model with $m(\tilde q)=1200$ GeV and $m(\tilde\chi^0_1)=0$ GeV is shown.

Observed and expected background and signal effective mass distributions for SR4jt. For signal, a gluino direct decay model with $m(\tilde g)=1400$ GeV and $m(\tilde\chi^0_1)=0$ GeV is shown.

Observed and expected background and signal effective mass distributions for SR5j. For signal, a gluino one-step decay model with $m(\tilde g)=1265$ GeV, $m(\tilde\chi^\pm_1)=945$ GeV and $m(\tilde\chi^0_1)=625$ GeV is shown.

Observed and expected background and signal effective mass distributions for SR6jm. For signal, a gluino one-step decay model with $m(\tilde g)=1265$ GeV, $m(\tilde\chi^\pm_1)=945$ GeV and $m(\tilde\chi^0_1)=625$ GeV is shown.

Observed and expected background and signal effective mass distributions for SR6jt. For signal, a gluino one-step decay model with $m(\tilde g)=1385$ GeV, $m(\tilde\chi^\pm_1)=705$ GeV and $m(\tilde\chi^0_1)=25$ GeV is shown.

Expected limit at 95% CL for squark direct decay model grid.

Expected limits at 95% CL +1 sigma excursion due to experimental and background-only theoretical uncertainties for squark direct decay model grid.

Expected limits at 95% CL -1 sigma excursion due to experimental and background-only theoretical uncertainties for squark direct decay model grid.

Observed limits at 95% CL for squark direct decay model grid.

Observed limits at 95% CL +1 sigma excursion due to the signal cross-section uncertainty for squark direct decay model grid.

Observed limits at 95% CL -1 sigma excursion due to the signal cross-section uncertainty for squark direct decay model grid.

Expected limit at 95% CL for gluino direct decay model grid.

Expected limits at 95% CL +1 sigma excursion due to experimental and background-only theoretical uncertainties for gluino direct decay model grid.

Expected limits at 95% CL -1 sigma excursion due to experimental and background-only theoretical uncertainties for gluino direct decay model grid.

Observed limits at 95% CL for gluino direct decay model grid.

Observed limits at 95% CL +1 sigma excursion due to the signal cross-section uncertainty for gluino direct decay model grid.

Observed limits at 95% CL -1 sigma excursion due to the signal cross-section uncertainty for gluino direct decay model grid.

Expected limit at 95% CL for gluino one-step decay model grid.

Expected limits at 95% CL +1 sigma excursion due to experimental and background-only theoretical uncertainties for gluino one-step decay model grid.

Expected limits at 95% CL -1 sigma excursion due to experimental and background-only theoretical uncertainties for gluino one-step decay model grid.

Observed limits at 95% CL for gluino one-step decay model grid.

Observed limits at 95% CL +1 sigma excursion due to the signal cross-section uncertainty for gluino one-step decay model grid.

Observed limits at 95% CL -1 sigma excursion due to the signal cross-section uncertainty for gluino one-step decay model grid.

Observed and expected background effective mass distributions in control region CRgamma for SR2jl.

Observed and expected background effective mass distributions in validation region VRZ for SR2jl.

Observed and expected background effective mass distributions in control region CRW for SR2jl.

Observed and expected background effective mass distributions in control region CRT for SR2jl.

Observed and expected background effective mass distributions in control region CRgamma for SR2jm.

Observed and expected background effective mass distributions in validation region VRZ for SR2jm.

Observed and expected background effective mass distributions in control region CRW for SR2jm.

Observed and expected background effective mass distributions in control region CRT for SR2jm.

Observed and expected background effective mass distributions in control region CRgamma for SR2jt.

Observed and expected background effective mass distributions in validation region VRZ for SR2jt.

Observed and expected background effective mass distributions in control region CRW for SR2jt.

Observed and expected background effective mass distributions in control region CRT for SR2jt.

Observed and expected background effective mass distributions in control region CRgamma for SR4jt.

Observed and expected background effective mass distributions in validation region VRZ for SR4jt.

Observed and expected background effective mass distributions in control region CRW for SR4jt.

Observed and expected background effective mass distributions in control region CRT for SR4jt.

Observed and expected background effective mass distributions in control region CRgamma for SR5j.

Observed and expected background effective mass distributions in validation region VRZ for SR5j.

Observed and expected background effective mass distributions in control region CRW for SR5j.

Observed and expected background effective mass distributions in control region CRT for SR5j.

Observed and expected background effective mass distributions in control region CRgamma for SR6jm.

Observed and expected background effective mass distributions in validation region VRZ for SR6jm.

Observed and expected background effective mass distributions in control region CRW for SR6jm.

Observed and expected background effective mass distributions in control region CRT for SR6jm.

Observed and expected background effective mass distributions in control region CRgamma for SR6jt.

Observed and expected background effective mass distributions in validation region VRZ for SR6jt.

Observed and expected background effective mass distributions in control region CRW for SR6jt.

Observed and expected background effective mass distributions in control region CRT for SR6jt.

Observed and expected event yields in VRZ as a function of signal region.

Observed and expected event yields in VRW as a function of signal region.

Observed and expected event yields in VRWv as a function of signal region.

Observed and expected event yields in VRT as a function of signal region.

Observed and expected event yields in VRTv as a function of signal region.

Observed and expected event yields in VRQa as a function of signal region.

Observed and expected event yields in VRQb as a function of signal region.

Signal acceptance for SR2jl in squark direct decay model grid.

Signal acceptance times efficiency for SR2jl in squark direct decay model grid.

Signal acceptance for SR2jm in squark direct decay model grid.

Signal acceptance times efficiency for SR2jm in squark direct decay model grid.

Signal acceptance for SR2jt in squark direct decay model grid.

Signal acceptance times efficiency for SR2jt in squark direct decay model grid.

Signal acceptance for SR4jt in squark direct decay model grid.

Signal acceptance times efficiency for SR4jt in squark direct decay model grid.

Signal acceptance for SR5j in squark direct decay model grid.

Signal acceptance times efficiency for SR5j in squark direct decay model grid.

Signal acceptance for SR6jm in squark direct decay model grid.

Signal acceptance times efficiency for SR6jm in squark direct decay model grid.

Signal acceptance for SR6jt in squark direct decay model grid.

Signal acceptance times efficiency for SR6jt in squark direct decay model grid.

Signal acceptance for SR2jl in gluino direct decay model grid.

Signal acceptance times efficiency for SR2jl in gluino direct decay model grid.

Signal acceptance for SR2jm in gluino direct decay model grid.

Signal acceptance times efficiency for SR2jm in gluino direct decay model grid.

Signal acceptance for SR2jt in gluino direct decay model grid.

Signal acceptance times efficiency for SR2jt in gluino direct decay model grid.

Signal acceptance for SR4jt in gluino direct decay model grid.

Signal acceptance times efficiency for SR4jt in gluino direct decay model grid.

Signal acceptance for SR5j in gluino direct decay model grid.

Signal acceptance times efficiency for SR5j in gluino direct decay model grid.

Signal acceptance for SR6jm in gluino direct decay model grid.

Signal acceptance times efficiency for SR6jm in gluino direct decay model grid.

Signal acceptance for SR6jt in gluino direct decay model grid.

Signal acceptance times efficiency for SR6jt in gluino direct decay model grid.

Signal acceptance for SR2jl in gluino one-step decay model grid.

Signal acceptance times efficiency for SR2jl in gluino one-step decay model grid.

Signal acceptance for SR2jm in gluino one-step decay model grid.

Signal acceptance times efficiency for SR2jm in gluino one-step decay model grid.

Signal acceptance for SR2j5 in gluino one-step decay model grid.

Signal acceptance times efficiency for SR2jt in gluino one-step decay model grid.

Signal acceptance for SR4jt in gluino one-step decay model grid.

Signal acceptance times efficiency for SR4jt in gluino one-step decay model grid.

Signal acceptance for SR5j in gluino one-step decay model grid.

Signal acceptance times efficiency for SR5j in gluino one-step decay model grid.

Signal acceptance for SR6jm in gluino one-step decay model grid.

Signal acceptance times efficiency for SR6jm in gluino one-step decay model grid.

Signal acceptance for SR6jt in gluino one-step decay model grid.

Signal acceptance times efficiency for SR6jt in gluino one-step decay model grid.

No description provided.

No description provided.

No description provided.

No description provided.

No description provided.

No description provided.

Centrality dependence of normalized observables SC(4,2) and SC(3,2) in Pb-Pb collisions at 2.76 TeV, in 0-10% most central collisions.