Transverse momentum distribution of the sub-leading lepton in the signal region SR1a showing both data points with statistical errors only and the expected standard model background.

Transverse momentum distribution of the 3rd-leading lepton in the signal region SR1a showing both data points with statistical errors only and the expected standard model background.

Missing transverse energy distribution in the signal region SR1a showing both data points with statistical errors only and the expected standard model background.

Mass distribution of Same Flavour Opposite Sign lepton pairs in the signal region SR1a showing both data points with statistical errors only and the expected standard model background.

Jet multiplicity distribution in the signal region SR1a showing both data points with statistical errors only and the expected standard model background.

Transverse mass distribution in the signal region SR1a showing both data points with statistical errors only and the expected standard model background.

Transverse momentum distribution of the leading lepton in the signal region SR2 showing both data points with statistical errors only and the expected standard model background.

Transverse momentum distribution of the sub-leading lepton in the signal region SR2 showing both data points with statistical errors only and the expected standard model background.

Transverse momentum distribution of the 3rd-leading lepton in the signal region SR2 showing both data points with statistical errors only and the expected standard model background.

Missing transverse energy distribution in the signal region SR2 showing both data points with statistical errors only and the expected standard model background.

Jet multiplicity distribution in the signal region SR2 showing both data points with statistical errors only and the expected standard model background.

Transverse mass distribution in the signal region SR2 showing both data points with statistical errors only and the expected standard model background.

Transverse momentum distribution of the leading lepton in the validation region VR1 showing both data points with statistical errors only and the expected standard model background.

Transverse momentum distribution of the sub-leading lepton in the validation region VR1 showing both data points with statistical errors only and the expected standard model background.

Transverse momentum distribution of the 3rd-leading lepton in the validation region VR1 showing both data points with statistical errors only and the expected standard model background.

Transverse momentum distribution of the leading lepton in the validation region VR2 showing both data points with statistical errors only and the expected standard model background.

Transverse momentum distribution of the sub-leading lepton in the validation region VR2 showing both data points with statistical errors only and the expected standard model background.

Transverse momentum distribution of the 3rd-leading lepton in the validation region VR2 showing both data points with statistical errors only and the expected standard model background.

Transverse momentum distribution of the leading lepton in the validation region VR3 showing both data points with statistical errors only and the expected standard model background.

Transverse momentum distribution of the sub-leading lepton in the validation region VR3 showing both data points with statistical errors only and the expected standard model background.

Transverse momentum distribution of the 3rd-leading lepton in the validation region VR3 showing both data points with statistical errors only and the expected standard model background.

The efficiencies in the different signal regions across the MSSM Direct Gaugino grid of the Higgs mass parameter MU and gaugino massess M1 and M2.

The acceptance in the different signal regions across the MSSM Direct Gaugino grid of the Higgs mass parameter MU and gaugino massess M1 and M2.

The total absolute systematic uncertainty (in number of events) in the different signal regions, not including uncertainties from Monte Carlo statistics, across the MSSM Direct Gaugino grid of the Higgs mass parameter MU and gaugino massess M1 and M2.

The observed CL_s values in the different signal regions across the MSSM Direct Gaugino grid of the Higgs mass parameter MU and gaugino massess M1 and M2.

The cross-section across the MSSM Direct Gaugino grid of the Higgs mass parameter MU and gaugino massess M1 and M2.

The number of generated events across the MSSM Direct Gaugino grid of the Higgs mass parameter MU and gaugino massess M1 and M2.

The efficiencies in the different signal regions across the simplified models with and without intermediate sleptons.

The acceptance in the different signal regions across the simplified models with and without intermediate sleptons.

The total absolute systematic uncertainty (in number of events) in the different signal regions, not including uncertainties from Monte Carlo statistics, across the simplified models with and without intermediate sleptons.

The observed CL_s values in the different signal regions across the simplified models with and without intermediate sleptons.

The cross-section across the simplified models with and without intermediate sleptons.

The number of generated events across the simplified models with and without intermediate sleptons.

Inclusive jet PT distribution for the |y| range 1.2-2.1 and R=0.4.

Inclusive jet PT distribution for the |y| range 2.1-2.8 and R=0.4.

Inclusive jet PT distribution for the |y| range 2.8-3.6 and R=0.4.

Inclusive jet PT distribution for the |y| range 3.6-4.4 and R=0.4.

Inclusive jet PT distribution for the |y| range 0.0-0.3 and R=0.6.

Inclusive jet PT distribution for the |y| range 0.3-0.8 and R=0.6.

Inclusive jet PT distribution for the |y| range 0.8-1.2 and R=0.6.

Inclusive jet PT distribution for the |y| range 1.2-2.1 and R=0.6.

Inclusive jet PT distribution for the |y| range 2.1-2.8 and R=0.6.

Inclusive jet PT distribution for the |y| range 2.8-3.6 and R=0.6.

Inclusive jet PT distribution for the |y| range 3.6-4.4 and R=0.6.

Dijet Mass distribution for the |y*| range 0.0-0.5 and R=0.4.

Dijet Mass distribution for the |y*| range 0.5-1.0 and R=0.4.

Dijet Mass distribution for the |y*| range 1.0-1.5 and R=0.4.

Dijet Mass distribution for the |y*| range 1.5-2.0 and R=0.4.

Dijet Mass distribution for the |y*| range 2.0-2.5 and R=0.4.

Dijet Mass distribution for the |y*| range 2.5-3.0 and R=0.4.

Dijet Mass distribution for the |y*| range 3.0-3.5 and R=0.4.

Dijet Mass distribution for the |y*| range 3.5-4.0 and R=0.4.

Dijet Mass distribution for the |y*| range 4.0-4.4 and R=0.4.

Dijet Mass distribution for the |y*| range 0.0-0.5 and R=0.6.

Dijet Mass distribution for the |y*| range 0.5-1.0 and R=0.6.

Dijet Mass distribution for the |y*| range 1.0-1.5 and R=0.6.

Dijet Mass distribution for the |y*| range 1.5-2.0 and R=0.6.

Dijet Mass distribution for the |y*| range 2.0-2.5 and R=0.6.

Dijet Mass distribution for the |y*| range 2.5-3.0 and R=0.6.

Dijet Mass distribution for the |y*| range 3.0-3.5 and R=0.6.

Dijet Mass distribution for the |y*| range 3.5-4.0 and R=0.6.

Dijet Mass distribution for the |y*| range 4.0-4.4 and R=0.6.

Inclusive double differential b-jet cross section as a function of PT for the |rapidity| range 1.2-2.1 from the lifetime-based analysis.

Differential b-jet cross sections as a function of PT from summing the data in the previous tables.

Differential b-jet cross sections as a function of PT from the muon-based analysis.

Differential b-bbar dijet cross sections as a function of dijet mass from the lifetime-based analysis.

Differential b-bbar dijet cross sections as a function of azimuthal angle difference between the jets from the lifetime-based analysis.

Double differential b-bbar dijet cross sections as a function of the angular variable chi between the jets for two different jet mass ranges from the lifetime-based analysis.

Double differential b-bbar dijet cross sections as a function of the angular variable chi between the jets for two different jet mass ranges from the lifetime-based analysis.

Distribution of the heavy particle Mass estimated from the Tile Calorimeter data plus the simulated background and model estimates for three gluino masses. A cut of BETA < 1 is imposed.;.

Distribution of the heavy particle Mass estimated from the Pixel detector data plus the data driven background and model estimates for two gluino masses.;.

Distribution of the heavy particle Mass estimated from the Tile Calorimeter data plus the data driven background and model estimates for two gluino masses.;.

Inclusive muon cross section from W+->mu+nu simulated with MC with CTEQ6.6 pdf set for |eta| < 2.5 and pT > 4 GeV: the error shown is due to the MC statistics.

Inclusive muon cross section from W-->mu-nu simulated with MC with CTEQ6.6 pdf set for |eta| < 2.5 and pT > 4 GeV: the error shown is due to the MC statistics.

Inclusive muon cross section from Z->mu+mu- simulated with MC with CTEQ6.6 pdf set for |eta| < 2.5 and pT > 4 GeV (the Z is defined as Z/gamma* with m_ll > 60 GeV): the error shown is due to the MC statistics.

Inclusive muon cross section from backgrounds: Z->tau tau, ttbar, Drell-Yan->mu+mu- (Drell-Yan is defined as Z/gamma* with m_ll < 60 GeV) simulated with Pythia with MRSTLO* pdf set for |eta| < 2.5 and pT > 4 GeV: the error shown is due to the MC statistics.

Inclusive muon cross section from bbar+ccbar production and decays simulated with FONLL with CTEQ6.6 pdf set for |eta| < 2.5 and pT > 4 GeV: the error shown is the uncertainty due to scale variation, alpha_s+pdf using CTEQ6.6 error set and the heavy quark masses.

Inclusive muon cross section from bbar+ccbar simulated with FONLL removing the resummation term with CTEQ6.6 pdf set for |eta| < 2.5 and pT > 4 GeV?.

Inclusive muon cross section for |eta| < 2.0 excluding 1.37 < |eta| < 1.52 and pT > 4 GeV: (stat) statistical error, (sys) systematic error. The first systematic error is the intrinsic error of the measurement, the second is the error due to the luminosity.

Inclusive muon cross section after subtraction of W,Z, Drell-Yan and top background for |eta| < 2.0 excluding 1.37 < |eta| < 1.52 and pT > 4 GeV: (stat): statistical error, (sys): systematic error. The first systematic error is the intrinsic error of the measurement, the second the error due to the luminosity, the third is due to the subtraction of the background and is dominated by the error on the W, Z inclusive cross sections.

Inclusive muon cross section from W+->mu+nu simulated with MC with CTEQ6.6 pdf set for |eta| < 2.0 excluding 1.37 < |eta| < 1.52 and pT > 4 GeV: the error shown is due to the MC statistics.

Inclusive muon cross section from W-->mu-nu simulated with MC with CTEQ6.6 pdf set for |eta| < 2.0 excluding 1.37 < |eta| < 1.52 and pT > 4 GeV: the error shown is due to the MC statistics.

Inclusive muon cross section from Z->mu+mu- simulated with MC with CTEQ6.6 pdf set for |eta| < 2.0 excluding 1.37 < |eta| < 1.52 and pT > 4 GeV (the Z is defined as Z/gamma* with m_ll > 60 GeV): the error shown is due to the MC statistics.

Inclusive muon cross section from backgrounds: Z->tau tau, ttbar, Drell-Yan->mu+mu- (Drell-Yan is defined as Z/gamma* with m_ll < 60 GeV) simulated with Pythia with MRSTLO* pdf set for |eta| < 2.0 excluding 1.37 < |eta| < 1.52 and pT > 4 GeV: the error shown is due to the MC statistics.

Inclusive muon cross section from bbar+ccbar production and decays simulated with FONLL with CTEQ6.6 pdf set for |eta| < 2.0 excluding 1.37 < |eta| < 1.52 and pT > 4 GeV: the error shown is the uncertainty due to scale variation, alpha_s+pdf using CTEQ6.6 error set and the heavy quark masses.

Inclusive muon cross section from bbar+ccbar simulated with FONLL removing the resummation term with CTEQ6.6 pdf set for |eta| < 2.0 excluding 1.37 < |eta| < 1.52 and pT > 4 GeV.

95 PCT confidence lower limits to M(1/2).

Breakdown of systematic uncertainties in percent for the measured fiducial cross section times leptonic branching ratio for Z/gamma* production in the Z/gamma* -> mu+mu- final state at 13TeV.

Measured fiducial cross section times leptonic branching ratio for Z/gamma* production in the combined Z/gamma* -> l+l- (l = e, mu) final state.

Measured total cross section times leptonic branching ratio for Z/gamma* production in the combined Z/gamma* -> l+ l- (l = e, mu) final state.

Measured total cross-section for ttbar events using e-mu events with b-tagged jets.

Correlation coefficients amongst the combined (Z/gamma^* -> l+ l-) where (l = e, mu) fiducial cross section and ttbar total cross section at 13, 8, and 7TeV.

Correlation coefficients amongst the combined (Z/gamma^* -> l+ l-) where (l = e, mu) fiducial cross section and ttbar total cross section at 13, 8, and 7TeV, omitting the common normalisation uncertainty due to the luminosity calibration and beam energy.

Z-boson and ttbar production cross-section single ratios at 13, 8, 7TeV. The beam-energy uncertainty, which largely cancels in the ratios, is included in the systematic uncertainty. In the first column, the total (TOT) cross sections are used for both numerator and denominator. In the second column, the total cross section is used for the numerator while the fiducial (FID) cross section is used for the denominator. In the third column, the fiducial cross sections are used for both numerator and denominator. Apart for the MZ requirement, the kinematic fiducial requirements listed below apply only to the fiducial cross sections. The luminosity uncertainty almost entirely cancels in some of the ratio measurements.

Z-boson and ttbar production cross-section double ratios at 13, 8, 7TeV. The beam-energy uncertainty, which largely cancels in the ratios, is included in the systematic uncertainty. In the first column, the total (TOT) cross sections are used for both ttbar and Z processes. In the second column, the total cross section is used for ttbar while the fiducial (FID) cross section is used for Z. In the third column, the fiducial cross sections are used for both ttbar and Z. Apart for the MZ requirement, the kinematic fiducial requirements listed below apply only to the fiducial cross sections.

$R_{pPb}$ 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 $\langle T_{Pb} \rangle$.