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This paper presents cross sections for the production of a W boson in association with jets, measured in proton--proton collisions at $\sqrt{s}=7$ TeV with the ATLAS experiment at the Large Hadron Collider. With an integrated luminosity of $4.6 fb^{-1}$, this data set allows for an exploration of a large kinematic range, including jet production up to a transverse momentum of 1 TeV and multiplicities up to seven associated jets. The production cross sections for W bosons are measured in both the electron and muon decay channels. Differential cross sections for many observables are also presented including measurements of the jet observables such as the rapidities and the transverse momenta as well as measurements of event observables such as the scalar sums of the transverse momenta of the jets. The measurements are compared to numerous QCD predictions including next-to-leading-order perturbative calculations, resummation calculations and Monte Carlo generators.
Distribution of inclusive jet multiplicity.
Breakdown of systematic uncertainties in percent in inclusive jet multiplicity in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in inclusive jet multiplicity in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of exclusive jet multiplicity.
Breakdown of systematic uncertainties in percent in exclusive jet multiplicity in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in exclusive jet multiplicity in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of pT (leading jet) [GeV] with at least one jet in the event.
Breakdown of systematic uncertainties in percent in pT (leading jet) [GeV] with at least one jet in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in pT (leading jet) [GeV] with at least one jet in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of pT (leading jet) [GeV] with exactly one jet in the event.
Breakdown of systematic uncertainties in percent in pT (leading jet) [GeV] with exactly one jet in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in pT (leading jet) [GeV] with exactly one jet in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of pT (leading jet) [GeV] with at least two jets in the event.
Breakdown of systematic uncertainties in percent in pT (leading jet) [GeV] with at least two jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in pT (leading jet) [GeV] with at least two jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of pT (leading jet) [GeV] with at least three jets in the event.
Breakdown of systematic uncertainties in percent in pT (leading jet) [GeV] with at least three jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in pT (leading jet) [GeV] with at least three jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of pT (2nd jet) [GeV] with at least two jets in the event.
Breakdown of systematic uncertainties in percent in pT (2nd jet) [GeV] with at least two jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in pT (2nd jet) [GeV] with at least two jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of pT (3rd jet) [GeV] with at least three jets in the event.
Breakdown of systematic uncertainties in percent in pT (3rd jet) [GeV] with at least three jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in pT (3rd jet) [GeV] with at least three jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of pT (4th jet) [GeV] with at least four jets in the event.
Breakdown of systematic uncertainties in percent in pT (4th jet) [GeV] with at least four jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in pT (4th jet) [GeV] with at least four jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of pT (5th jet) [GeV] with at least five jets in the event.
Breakdown of systematic uncertainties in percent in pT (5th jet) [GeV] with at least five jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in pT (5th jet) [GeV] with at least five jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of leading jet rapidity with at least one jet in the event.
Breakdown of systematic uncertainties in percent in leading jet rapidity with at least one jet in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in leading jet rapidity with at least one jet in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of 2nd jet rapidity with at least two jets in the event.
Breakdown of systematic uncertainties in percent in 2nd jet rapidity with at least two jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in 2nd jet rapidity with at least two jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of HT [GeV] with at least one jet in the event.
Breakdown of systematic uncertainties in percent in HT [GeV] with at least one jet in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in HT [GeV] with at least one jet in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of HT [GeV] with exactly one jet in the event.
Breakdown of systematic uncertainties in percent in HT [GeV] with exactly one jet in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in HT [GeV] with exactly one jet in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of HT [GeV] with at least two jets in the event.
Breakdown of systematic uncertainties in percent in HT [GeV] with at least two jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in HT [GeV] with at least two jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of HT [GeV] with exactly two jets in the event.
Breakdown of systematic uncertainties in percent in HT [GeV] with exactly two jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in HT [GeV] with exactly two jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of HT [GeV] with at least three jets in the event.
Breakdown of systematic uncertainties in percent in HT [GeV] with at least three jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in HT [GeV] with at least three jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of HT [GeV] with exactly three jets in the event.
Breakdown of systematic uncertainties in percent in HT [GeV] with exactly three jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in HT [GeV] with exactly three jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of HT [GeV] with at least four jets in the event.
Breakdown of systematic uncertainties in percent in HT [GeV] with at least four jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in HT [GeV] with at least four jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of HT [GeV] with at least five jets in the event.
Breakdown of systematic uncertainties in percent in HT [GeV] with at least five jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in HT [GeV] with at least five jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of DPhi(jj) [GeV] with at least two jets in the event.
Breakdown of systematic uncertainties in percent in DPhi(jj) [GeV] with at least two jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in DPhi(jj) [GeV] with at least two jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of Dy(jj) [GeV] with at least two jets in the event.
Breakdown of systematic uncertainties in percent in Dy(jj) [GeV] with at least two jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in Dy(jj) [GeV] with at least two jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of DR(jj) [GeV] with at least two jets in the event.
Breakdown of systematic uncertainties in percent in DR(jj) [GeV] with at least two jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in DR(jj) [GeV] with at least two jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of m(jj) [GeV] with at least two jets in the event.
Breakdown of systematic uncertainties in percent in m(jj) [GeV] with at least two jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in m(jj) [GeV] with at least two jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of 3rd jet rapidity with at least three jets in the event.
Breakdown of systematic uncertainties in percent in 3rd jet rapidity with at least three jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in 3rd jet rapidity with at least three jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of 4th jet rapidity with at least four jets in the event.
Breakdown of systematic uncertainties in percent in 4th jet rapidity with at least four jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in 4th jet rapidity with at least four jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of 5th jet rapidity with at least five jets in the event.
Breakdown of systematic uncertainties in percent in 5th jet rapidity with at least five jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in 5th jet rapidity with at least five jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of ST [GeV] with at least one jet in the event.
Breakdown of systematic uncertainties in percent in ST [GeV] with at least one jet in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in ST [GeV] with at least one jet in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of ST [GeV] with at least two jets in the event.
Breakdown of systematic uncertainties in percent in ST [GeV] with at least two jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in ST [GeV] with at least two jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of ST [GeV] with exactly two jets in the event.
Breakdown of systematic uncertainties in percent in ST [GeV] with exactly two jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in ST [GeV] with exactly two jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of ST [GeV] with at least three jets in the event.
Breakdown of systematic uncertainties in percent in ST [GeV] with at least three jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in ST [GeV] with at least three jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of ST [GeV] with exactly three jets in the event.
Breakdown of systematic uncertainties in percent in ST [GeV] with exactly three jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in ST [GeV] with exactly three jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of ST [GeV] with at least four jets in the event.
Breakdown of systematic uncertainties in percent in ST [GeV] with at least four jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in ST [GeV] with at least four jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Distribution of ST [GeV] with at least five jets in the event.
Breakdown of systematic uncertainties in percent in ST [GeV] with at least five jets in the event in the electron channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
Breakdown of systematic uncertainties in percent in ST [GeV] with at least five jets in the event in the muon channel.Uncertainties have been symmetrised and the sign denotes the sign of the original up-variation.
This paper presents measurements of top-antitop quark pair ($t\bar{t}$) production in association with additional $b$-jets. The analysis utilises 140 fb$^{-1}$ of proton-proton collision data collected with the ATLAS detector at the Large Hadron Collider at a centre-of-mass energy of 13 TeV. Fiducial cross-sections are extracted in a final state featuring one electron and one muon, with at least three or four $b$-jets. Results are presented at the particle level for both integrated cross-sections and normalised differential cross-sections, as functions of global event properties, jet kinematics, and $b$-jet pair properties. Observable quantities characterising $b$-jets originating from the top quark decay and additional $b$-jets are also measured at the particle level, after correcting for detector effects. The measured integrated fiducial cross-sections are consistent with $t\bar{t}b\bar{b}$ predictions from various next-to-leading-order matrix element calculations matched to a parton shower within the uncertainties of the predictions. State-of-the-art theoretical predictions are compared with the differential measurements; none of them simultaneously describes all observables. Differences between any two predictions are smaller than the measurement uncertainties for most observables.
Measured and predicted fiducial cross-section results for additional b-jet production in four phase-space regions. The dashes (–) indicate that the predictions are not available. The differences between the various MC generator predictions are smaller than the size of theoretical uncertainties (20%–50%, not presented here) in the predictions.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least two $b$-jets as a function of the number of $b$-jets compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of the number of $b$-jets compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of the number of $l/c$-jets compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $H_{\text{T}}^{\text{had}}$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $\Delta R_{\text{avg}}^{bb}$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $p_{\text{T}}(b_{1})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $p_{\text{T}}(b_{2})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $p_{\text{T}}(b_{1}^{\text{top}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $p_{\text{T}}(b_{2}^{\text{top}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $p_{\text{T}}(b_{3})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $p_{\text{T}}(b_{1}^{\text{add}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $m(b_{1}b_{2})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $p_{\text{T}}(b_{1}b_{2})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $m(bb^{\text{top}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $p_{\text{T}}(bb^{\text{top}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $\Delta R(e\mu bb^{\text{top}}, b_{1}^{\text{add}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets and at least one $l/c$-jet as a function of $\Delta R(e\mu bb^{\text{top}}, l/c\text{-jet}_{1})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets and at least one $l/c$-jet as a function of $p_{\text{T}}(l/c\text{-jet}_{1})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets and at least one $l/c$-jet as a function of $p_{\text{T}}(l/c\text{-jet}_{1}) - p_{\text{T}}(b_{1}^{\text{add}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $m(bb^{\text{min}\Delta R})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(bb^{\text{min}\Delta R})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $m(bb^{\text{add}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(bb^{\text{add}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $|\eta(b_{3})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $|\eta(b_{1}^{\text{add}})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $\Delta R(b_{1}b_{2})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $m(e\mu bb^{\text{top}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $|\eta(l/c\text{-jet}_{1})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $\Delta\eta_{\text{max}}^{jj}$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $H_{\text{T}}^{\text{all}}$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $m(e\mu b_{1}b_{2})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $|\eta(b_{1})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $|\eta(b_{2})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $|\eta(b_{1}^{\text{top}})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $|\eta(b_{2}^{\text{top}})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(b_{1})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(b_{2})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(b_{1}^{\text{top}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(b_{2}^{\text{top}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(b_{3})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(b_{4})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(b_{1}^{\text{add}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(b_{2}^{\text{add}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $m(b_{1}b_{2})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(b_{1}b_{2})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $m(bb^{\text{top}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(bb^{\text{top}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $H_{\text{T}}^{\text{all}}$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $m(e\mu b_{1}b_{2})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $m(e\mu bb^{\text{top}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $H_{\text{T}}^{\text{had}}$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $\text{min}\Delta R(bb)$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $\Delta R(e\mu bb^{\text{top}}, b_{1}^{\text{add}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $\Delta R_{\text{avg}}^{bb}$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $\Delta\eta_{\text{max}}^{jj}$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of the number of $l/c$-jets compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets and at least one $l/c$-jet as a function of $p_{\text{T}}(l/c\text{-jet}_{1})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets and at least one $l/c$-jet as a function of $|\eta(l/c\text{-jet}_{1})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets and at least one $l/c$-jet as a function of $\Delta R(e\mu bb^{\text{top}}, l/c\text{-jet}_{1})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets and at least one $l/c$-jet as a function of $p_{\text{T}}(l/c\text{-jet}_{1}) - p_{\text{T}}(b_{1}^{\text{add}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $|\eta(b_{1})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $|\eta(b_{2})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $|\eta(b_{1}^{\text{top}})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at leastfour $b$-jets as a function of $|\eta(b_{2}^{\text{top}})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $|\eta(b_{3})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $|\eta(b_{4})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $|\eta(b_{1}^{\text{add}})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $|\eta(b_{2}^{\text{add}})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.
The measured normalised differential cross-section as a function of $N_{b-\text{jets}}$ in the $e\mu+\geq2b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $H_{\text{T}}^{\text{had}}$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $H_{\text{T}}^{\text{all}}$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $\Delta R_{\text{avg}}^{bb}$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $\Delta\eta_{\text{max}}^{jj}$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{1})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{1}^{\text{top}})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{2})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{2}^{\text{top}})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{3})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{1}^{\text{add}})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $|\eta(b_{1})|$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $|\eta(b_{1}^{\text{top}})|$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $|\eta(b_{2})|$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $|\eta(b_{2}^{\text{top}})|$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $|\eta(b_{3})|$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $|\eta(b_{1}^{\text{add}})|$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $m(b_{1}b_{2})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{1}b_{2})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $m(bb^{\text{top}})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $p_{\text{T}}(bb^{\text{top}})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $m(e\mu b_{1}b_{2})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $m(e\mu bb^{\text{top}})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $\Delta R(b_{1}b_{2})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $N_{l/c-\text{jets}}$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $\Delta R(e\mu b_{1}b_{2},b_{3})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $\Delta R(e\mu bb^{\text{top}}, b_{1}^{\text{add}})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $\Delta R(e\mu bb^{\text{top}},l/c-\text{jet})$ in the $e\mu+\geq3b+\geq1l/c-\text{jet}$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $p_{\text{T}}(l/c\text{-jet}_{1}) - p_{\text{T}}(b_{1}^{\text{add}})$ in the $e\mu+\geq3b+\geq1l/c-\text{jet}$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $|\eta(l/c\text{-jet}_{1})|$ in the $e\mu+\geq3b+\geq1l/c-\text{jet}$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $p_{\text{T}}(l/c\text{-jet}_{1})$ in the $e\mu+\geq3b+\geq1l/c-\text{jet}$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $H_{\text{T}}^{\text{had}}$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $H_{\text{T}}^{\text{all}}$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $\Delta R_{\text{avg}}^{bb}$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $\Delta\eta_{\text{max}}^{jj}$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{1})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{1}^{\text{top}})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{2})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{2}^{\text{top}})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{3})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{1}^{\text{add}})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{4})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{2}^{\text{add}})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $|\eta(b_{1})|$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $|\eta(b_{1}^{\text{top}})|$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $|\eta(b_{2})|$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $|\eta(b_{2}^{\text{top}})|$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $|\eta(b_{3})|$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $|\eta(b_{1}^{\text{add}})|$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $|\eta(b_{4})|$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $|\eta(b_{2}^{\text{add}})|$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $m(b_{1}b_{2})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{1}b_{2})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $m(bb^{\text{top}})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $p_{\text{T}}(bb^{\text{top}})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $m(e\mu b_{1}b_{2})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $m(e\mu bb^{\text{top}})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $m(bb^{\text{min}\Delta R})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $p_{\text{T}}(bb^{\text{min}\Delta R})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $m(bb^{\text{add}})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $p_{\text{T}}(bb^{\text{add}})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $\text{min}\Delta R(bb)$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $\Delta R(b_{1}b_{2})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $N_{l/c-\text{jets}}$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $\Delta R(e\mu b_{1}b_{2},b_{3})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $\Delta R(e\mu bb^{\text{top}}, b_{1}^{\text{add}})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $\Delta R(e\mu bb^{\text{top}}, l/c\text{-jet}_{1})$ in the $e\mu+\geq4b+\geq1l/c-\text{jet}$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $p_{\text{T}}(l/c\text{-jet}_{1}) - p_{\text{T}}(b_{1}^{\text{add}})$ in the $e\mu+\geq4b+\geq1l/c-\text{jet}$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $|\eta(l/c\text{-jet}_{1})|$ in the $e\mu+\geq4b+\geq1l/c-\text{jet}$ phase space. The overflow is included in the last bin.
The measured normalised differential cross-section as a function of $p_{\text{T}}(l/c\text{-jet}_{1})$ in the $e\mu+\geq4b+\geq1l/c-\text{jet}$ phase space. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $N_{b-\text{jets}}$ in the phase space with at least two b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $N_{b-\text{jets}}$ in the phase space with at least three b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $H_{\text{T}}^{\text{had}}$ in the phase space with at least three b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $H_{\text{T}}^{\text{all}}$ in the phase space with at least three b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $\Delta R_{\text{avg}}^{bb}$ in the phase space with at least three b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $\Delta\eta_{\text{max}}^{jj}$ in the phase space with at least three b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{1})$ in the phase space with at least three b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{1}^{\text{top}})$ in the phase space with at least three b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{2})$ in the phase space with at least three b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{2}^{\text{top}})$ in the phase space with at least three b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{3})$ in the phase space with at least three b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{1}^{\text{add}})$ in the phase space with at least three b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{1})|$ in the phase space with at least three b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{1}^{\text{top}})|$ in the phase space with at least three b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{2}^{\text{top}})|$ in the phase space with at least three b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{2}^{\text{top}})|$ in the phase space with at least three b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{3})|$ in the phase space with at least three b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{1}^{\text{add}})|$ in the phase space with at least three b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $m(b_{1}b_{2})$ in the phase space with at least three b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{1}b_{2})$ in the phase space with at least three b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $m(bb^{\text{top}})$ in the phase space with at least three b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(bb^{\text{top}})$ in the phase space with at least three b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $m(e\mu b_{1}b_{2})$ in the phase space with at least three b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $m(e\mu bb^{\text{top}})$ in the phase space with at least three b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $\Delta R(b_{1}b_{2})$ in the phase space with at least three b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $N_{l/c-\text{jets}}$ in the phase space with at least three b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $\Delta R(e\mu b_{1}b_{2},b_{3})$ in the phase space with at least three b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $\Delta R(e\mu bb^{\text{top}}, b_{1}^{\text{add}})$ in the phase space with at least three b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $\Delta R(e\mu bb^{\text{top}},l/c-\text{jet})$ in the phase space with at least three b-jets and at least one $l/c$-jet. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(l/c\text{-jet}_{1}) - p_{\text{T}}(b_{1}^{\text{add}})$ in the phase space with at least three b-jets and at least one $l/c$-jet. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(l/c\text{-jet}_{1})|$ in the phase space with at least three b-jets and at least one $l/c$-jet. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(l/c\text{-jet}_{1})$ in the phase space with at least three b-jets and at least one $l/c$-jet. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $H_{\text{T}}^{\text{had}}$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $H_{\text{T}}^{\text{all}}$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $\Delta R_{\text{avg}}^{bb}$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $\Delta\eta_{\text{max}}^{jj}$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{1})$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{1}^{\text{top}})$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{2})$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{2}^{\text{top}})$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{3})$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{1}^{\text{add}})$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{4})$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{2}^{\text{add}})$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{1})|$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{1}^{\text{top}})|$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{2})|$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{2}^{\text{top}})|$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{3})|$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{1}^{\text{add}})|$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{4})|$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{2}^{\text{add}})|$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $m(b_{1}b_{2})$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{1}b_{2})$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $m(bb^{\text{top}})$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(bb^{\text{top}})$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $m(e\mu b_{1}b_{2})$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $m(e\mu bb^{\text{top}})$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $m(bb^{\text{min}\Delta R})$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(bb^{\text{min}\Delta R})$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $m(bb^{\text{add}})$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(bb^{\text{add}})$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $\text{min}\Delta R(bb)$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $\Delta R(b_{1}b_{2})$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $N_{l/c-\text{jets}}$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $\Delta R(e\mu b_{1}b_{2},b_{3})$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $\Delta R(e\mu bb^{\text{top}}, b_{1}^{\text{add}})$ in the phase space with at least four b-jets. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $\Delta R(e\mu bb^{\text{top}}, l/c\text{-jet}_{1})$ in the phase space with at least four b-jets and at least one $l/c$-jet. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(l/c\text{-jet}_{1}) - p_{\text{T}}(b_{1}^{\text{add}})$ in the phase space with at least four b-jets and at least one $l/c$-jet. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(l/c\text{-jet}_{1})|$ in the phase space with at least four b-jets and at least one $l/c$-jet. The overflow is included in the last bin.
The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(l/c\text{-jet}_{1})$ in the phase space with at least four b-jets and at least one $l/c$-jet. The overflow is included in the last bin.
The measurement of charged-particle event shape variables is presented in inclusive inelastic pp collisions at a center-of-mass energy of 7 TeV using the ATLAS detector at the LHC. The observables studied are the transverse thrust, thrust minor and transverse sphericity, each defined using the final-state charged particles' momentum components perpendicular to the beam direction. Events with at least six charged particles are selected by a minimum-bias trigger. In addition to the differential distributions, the evolution of each event shape variable as a function of the leading charged particle transverse momentum, charged particle multiplicity and summed transverse momentum is presented. Predictions from several Monte Carlo models show significant deviations from data.
Normalized distributions of Tranverse Thrust for 4 ranges of leading particle PT.
Normalized distributions of Tranverse Thrust for 5 lower limit values of leading particle PT.
Normalized distributions of Tranverse Thrust Minor for 4 ranges of leading particle PT.
Normalized distributions of Tranverse Thrust Minor for 5 lower limit values of leading particle PT.
Normalized distributions of Tranverse Sphericity for 4 ranges of leading particle PT.
Normalized distributions of Tranverse Sphericity for 5 lower limit values of leading particle PT.
Mean Values of Thrust, Thrust Minor and Sphericity verses Multiplicity.
Mean Values of Thrust, Thrust Minor and Sphericity verses charged particle PT scalar sum.
A search for strongly produced supersymmetric particles is conducted using signatures involving multiple energetic jets and either two isolated leptons ($e$ or $\mu$) with the same electric charge, or at least three isolated leptons. The search also utilises jets originating from b-quarks, missing transverse momentum and other observables to extend its sensitivity. The analysis uses a data sample corresponding to a total integrated luminosity of 20.3 fb$^{-1}$ of $\sqrt{s} =$ 8 TeV proton-proton collisions recorded with the ATLAS detector at the Large Hadron Collider in 2012. No deviation from the Standard Model expectation is observed. New or significantly improved exclusion limits are set on a wide variety of supersymmetric models in which the lightest squark can be of the first, second or third generations, and in which R-parity can be conserved or violated.
Numbers of observed and background events for SR0b for each bin of the distribution in Meff. The table corresponds to Fig. 4(b). The statistical and systematic uncertainties are combined for the expected backgrounds.
Numbers of observed and background events for SR1b for each bin of the distribution in Meff. The table corresponds to Fig. 4(c). The statistical and systematic uncertainties are combined for the predicted numbers.
Numbers of observed and background events for SR3b for each bin of the distribution in Meff. The table corresponds to Fig. 4(a). The statistical and systematic uncertainties are combined for the predicted numbers.
Numbers of observed and background events for SR3L low for each bin of the distribution in Meff. The table corresponds to Fig. 4(d). The statistical and systematic uncertainties are combined for the predicted numbers.
Numbers of observed and background events for SR3L high for each bin of the distribution in Meff. The table corresponds to Fig. 4(e). The statistical and systematic uncertainties are combined for the predicted numbers.
The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks that decay into two steps into q q W Z W Z chi1^0 chi1^0 (see Fig. 6c in the paper).
The efficiencies are calculated for all simplified extra dimension model (see Fig. 8d in the paper). For each model, the values are given for the five signal regions and their combination.
The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay via sleptons into q q q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6d in the paper).
The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into q q q q W W chi1^0 chi1^0 (see Fig. 6a in the paper).
The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into t tbar t tbar chi1^0 chi1^0 (see Fig. 5a in the paper). This particular model assumes that top quark is much heavier than gluino.
The efficiencies are calculated for all mSUGRA models (see Fig. 8a in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, and mu>0.
The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos. A gluino decays into t c chi1^0 (see Fig. 5c in the paper). This particular model assumes that m(chi1^0) = m(stop) - 20 GeV.
The efficiencies are calculated for all GMSB models (see Fig. 8c in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes mmess=250 TeV, m5=3, mu>0, and Cgrav=1.
The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7a in the paper). This particular model assumes that m(chi1^0)=60 GeV.
The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos and top squarks. Top squarks undergo R-parity violating decays into b s and gluinos decay into t stop (see Fig. 5d in the paper).
The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7b in the paper). This particular model assumes that m(chi1^0)=2(chi1^0).
The efficiencies are calculated for all mSUGRA/CMSSM models with bRPV (see Fig. 8b in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, mu>0, and bRPV.
The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks. Squarks decay into q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6e in the paper).
The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos that decay via a two-step process into q q q q W Z W Z chi1^0 chi1^0 (see Fig. 6b in the paper).
The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair production of gluinos. A gluino decays into t stop. Consequently, a top squark squark decays into b chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 5b in the paper). This particular model assumes that m(stop) < m(gluino), m(chi1^0)=6 GeV, and m(chi1^(+-))=118 GeV.
The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks that decay into two steps into q q W Z W Z chi1^0 chi1^0 (see Fig. 6c in the paper).
The acceptances (in percent, %) are calculated for all simplified extra dimension model (see Fig. 8d in the paper). For each model, the values are given for the five signal regions and their combination.
The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay via sleptons into q q q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6d in the paper).
The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into q q q q W W chi1^0 chi1^0 (see Fig. 6a in the paper).
The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into t tbar t tbar chi1^0 chi1^0 (see Fig. 5a in the paper). This particular model assumes that top quark is much heavier than gluino.
The acceptances (in percent, %) are calculated for all mSUGRA models (see Fig. 8a in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, and mu>0.
The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos. A gluino decays into t c chi1^0 (see Fig. 5c in the paper). This particular model assumes that m(chi1^0) = m(stop) - 20 GeV.
The acceptances (in percent, %) are calculated for all GMSB models (see Fig. 8c in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes mmess=250 TeV, m5=3, mu>0, and Cgrav=1.
The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7a in the paper). This particular model assumes that m(chi1^0)=60 GeV.
The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos and top squarks. Top squarks undergo R-parity violating decays into bs and gluinos decay into t stop (see Fig. 5d in the paper).
The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W chi1^0 (see Fig. 7b in the paper). This particular model assumes that m(chi1^0)=2(chi1^0).
The acceptances (in percent, %) are calculated for all mSUGRA/CMSSM models with bRPV (see Fig. 8b in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, mu>0, and bRPV.
The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks. Squarks decay into q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6e in the paper).
The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos that decay via a two-step process into q q q q W Z W Z chi1^0 chi1^0 (see Fig. 6b in the paper).
The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair production of gluinos. A gluino decays into t stop. Consequently, a top squark squark decays into b chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 5b in the paper). This particular model assumes that m(stop) < m(gluino), m(chi1^0)=6 GeV, and m(chi1^(+-))=118 GeV.
The limits on observed cross section are calculated for all simplified models. The simplified models are for direct pair production of squarks that decay into two steps into q q W Z W Z chi1^0 chi1^0 (see Fig. 6c in the paper).
The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct pair-production of gluinos that decay via sleptons into q q q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6d in the paper).
The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct production of gluinos that decay into q q q q W W chi1^0 chi1^0 (see Fig. 6a in the paper).
The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct production of gluinos that decay into t tbar t tbar chi1^0 chi1^0 (see Fig. 5a in the paper). This particular model assumes that top quark is much heavier than gluino.
The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct pair production of gluinos. A gluino decays into t c chi1^0 (see Fig. 5c in the paper). This particular model assumes that m(chi1^0) = m(stop) - 20 GeV.
The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7a in the paper). This particular model assumes that m(chi1^0)=60 GeV.
The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct production of gluinos and top squarks. Top squarks undergo R-parity violating decays into bs and gluinos decay into t stop (see Fig. 5d in the paper).
The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7b in the paper). This particular model assumes that m(chi1^0)=2(chi1^0).
The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct production of squarks. Squarks decay into q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6e in the paper).
The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct pair-production of gluinos that decay via a two-step process into q q q q W Z W Z chi1^0 chi1^0 (see Fig. 6b in the paper).
The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct pair production of gluinos. A gluino decays into t stop. Consequently, a top squark squark decays into b chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 5b in the paper). This particular model assumes that m(stop) < m(gluino), m(chi1^0)=6 GeV, and m(chi1^(+-))=118 GeV.
The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks that decay into two steps into q q W Z W Z chi1^0 chi1^0 (see Fig. 6c in the paper).
The signal event yields are calculated for all simplified extra dimension model (see Fig. 8d in the paper). For each model, the values are given for the five signal regions and their combination.
The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay via sleptons into q q q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6d in the paper).
The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into q q q q W W chi1^0 chi1^0 (see Fig. 6a in the paper).
The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into t tbar t tbar chi1^0 chi1^0 (see Fig. 5a in the paper). This particular model assumes that top quark is much heavier than gluino.
The signal event yields are calculated for all mSUGRA models (see Fig. 8a in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, and mu>0.
The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos. A gluino decays into t c chi1^0 (see Fig. 5c in the paper). This particular model assumes that m(chi1^0) = m(stop)-20 GeV.
The signal event yields are calculated for all GMSB models (see Fig. 8c in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes mmess=250 TeV, m5=3, mu>0, and Cgrav=1.
The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7a in the paper). This particular model assumes that m(chi1^0)=60 GeV.
The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos and top squarks. Top squarks undergo R-parity violating decays into bs and gluinos decay into t stop (see Fig. 5d in the paper).
The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7b in the paper). This particular model assumes that m(chi1^0)=2(chi1^0).
The signal event yields are calculated for all mSUGRA/CMSSM models with bRPV (see Fig. 8b in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, mu>0, and bRPV.
The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks. Squarks decay into q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6e in the paper).
The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos that decay via a two-step process into q q q q W Z W Z chi1^0 chi1^0 (see Fig. 6b in the paper).
The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos. A gluino decays into t stop. Consequently, a top squark squark decays into b chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 5b in the paper). This particular model assumes that m(stop) < m(gluino), m(chi1^0)=6 GeV, and m(chi1^(+-))=118 GeV.
Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks that decay into two steps into q q W Z W Z chi1^0 chi1^0 (see Fig. 6c in the paper).
Experimental uncertainties on the signal event yields are calculated for all simplified extra dimension model (see Fig. 8d in the paper). For each model, the values are given for the five signal regions and their combination.
Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay via sleptons into q q q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6d in the paper).
Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into q q q q W W chi1^0 chi1^0 (see Fig. 6a in the paper).
Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into t tbar t tbar chi1^0 chi1^0 (see Fig. 5a in the paper). This particular model assumes that top quark is much heavier than gluino.
Experimental uncertainties on the signal event yields are calculated for all mSUGRA models (see Fig. 8a in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, and mu>0.
Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos. A gluino decays into t c chi1^0 (see Fig. 5c in the paper). This particular model assumes that m(chi1^0) = m(stop) - 20 GeV.
Experimental uncertainties on the signal event yields are calculated for all GMSB models (see Fig. 8c in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes mmess=250 TeV, m5=3, mu>0, and Cgrav=1.
Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7a in the paper). This particular model assumes that m(chi1^0)=60 GeV.
Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos and top squarks. Top squarks undergo R-parity violating decays into bs and gluinos decay into t stop (see Fig. 5d in the paper).
Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7b in the paper). This particular model assumes that m(chi1^0)=2(chi1^0).
Experimental uncertainties on the signal event yields are calculated for all mSUGRA/CMSSM models with bRPV (see Fig. 8b in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, mu>0, and bRPV.
Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks. Squarks decay into q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6e in the paper).
Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos that decay via a two-step process into q q q q W Z W Z chi1^0 chi1^0 (see Fig. 6b in the paper).
Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos. A gluino decays into t stop. Consequently, a top squark squark decays into b chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 5b in the paper). This particular model assumes that m(stop) < m(gluino), m(chi1^0)=6 GeV, and m(chi1^(+-))=118 GeV.
Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks that decay into two steps into q q W Z W Z chi1^0 chi1^0 (see Fig. 6c in the paper).
Statistical uncertainties on the signal event yields are calculated for all simplified extra dimension model (see Fig. 8d in the paper). For each model, the values are given for the five signal regions and their combination.
Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay via sleptons into q q q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6d in the paper).
Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into q q q q W W chi1^0 chi1^0 (see Fig. 6a in the paper).
Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into t tbar t tbar chi1^0 chi1^0 (see Fig. 5a in the paper). This particular model assumes that top quark is much heavier than gluino.
Statistical uncertainties on the signal event yields are calculated for all mSUGRA models (see Fig. 8a in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, and mu>0.
Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos. A gluino decays into t c chi1^0 (see Fig. 5c in the paper). This particular model assumes that m(chi1^0) = m(stop) - 20 GeV.
Statistical uncertainties on the signal event yields are calculated for all GMSB models (see Fig. 8c in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes mmess=250 TeV, m5=3, mu>0, and Cgrav=1.
Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7a in the paper). This particular model assumes that m(chi1^0)=60 GeV.
Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos and top squarks. Top squarks undergo R-parity violating decays into bs and gluinos decay into t stop (see Fig. 5d in the paper).
Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7b in the paper). This particular model assumes that m(chi1^0)=2(chi1^0).
Statistical uncertainties on the signal event yields are calculated for all mSUGRA/CMSSM models with bRPV (see Fig. 8b in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, mu>0, and bRPV.
Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks. Squarks decay into q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6e in the paper).
Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos that decay via a two-step process into q q q q W Z W Z chi1^0 chi1^0 (see Fig. 6b in the paper).
Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos. A gluino decays into t stop. Consequently, a top squark squark decays into b chi1^(+-) and chi1^(+-) --> W ^(+-) chi1^0 (see Fig. 5b in the paper). This particular model assumes that m(stop) < m(gluino), m(chi1^0)=6 GeV, and m(chi1^(+-))=118 GeV.
The confidence levels are calculated for all simplified models. For each model, the observed and expected values are given. The simplified model is for direct production of gluinos that decay into t tbar t tbar chi1^0 chi1^0 (see Fig. 5a in the paper). This particular model assumes that top quark is much heavier than gluino.
The confidence levels are calculated for all simplified models. For each model, the observed and expected values are given. The simplified model is for direct production of squarks that decay into two steps into q q W Z W Z chi1^0 chi1^0 (see Fig. 6c in the paper).
The confidence levels are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos that decay via a two-step process into q q q q W Z W Z chi1^0 chi1^0 (see Fig. 6b in the paper).
The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct production of gluinos that decay via sleptons into q q q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6d in the paper).
The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct pair-production of gluinos. A gluino decays into t stop. Consequently, a top squark squark decays into b chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 5b in the paper). This particular model assumes that m(stop) < m(gluion), m(chi1^0)=6 GeV, and m(chi1^(+-))=118 GeV.
The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct production of gluinos. A gluino decays into t c chi1^0 (see Fig. 5c in the paper). This particular model assumes that m(chi1^0) = m(stop) - 20 GeV.
The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7b in the paper). This particular model assumes that m(chi1^0)=2(chi1^0).
The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7a in the paper). This particular model assumes that m(chi1^0)=60 GeV.
The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct production of squarks. Squarks decay into q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6e in the paper).
The confidence levels are calculated for all GMSB models (see Fig. 8c in the paper). For each model, the expected and observed values are given. The model assumes mmess=250 TeV, m5=3, mu>0, and Cgrav=1.
The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct production of gluinos and top squarks. Top squarks undergo R-parity violating decays into bs and gluinos decay into t stop (see Fig. 5d in the paper).
The confidence levels are calculated for all mSUGRA/CMSSM models with bRPV (see Fig. 8b in the paper). For each model, the expected and observed values are given. The model assumes tan(beta)=30, A0=2m0, mu>0, and bRPV.
The confidence levels are calculated for all simplified extra dimension model (see Fig. 8d in the paper). For each model, the expected and observed values are given.
The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct production of gluinos that decay into q q q q W W chi1^0 chi1^0 (see Fig. 6a in the paper).
The confidence levels are calculated for all mSUGRA models (see Fig. 8a in the paper). For each model, the expected and observed values are given. The model assumes tan(beta)=30, A0=2m0, and mu>0.
Various differential cross-sections are measured in top-quark pair ($t\bar{t}$) events produced in proton-proton collisions at a centre-of-mass energy of $\sqrt{s} = 7$ TeV at the LHC with the ATLAS detector. These differential cross-sections are presented in a data set corresponding to an integrated luminosity of $4.6$ fb$^{-1}$. The differential cross-sections are presented in terms of kinematic variables, such as momentum, rapidity and invariant mass, of a top-quark proxyreferred to as the pseudo-top-quark as well as the pseudo-top-quark pair system. The dependence of the measurement on theoretical models is minimal. The measurements are performed on $t\bar{t}$ events in the lepton+jets channel, requiring exactly one charged lepton and at least four jets with at least two of them tagged as originating from a $b$-quark. The hadronic and leptonic pseudo-top-quarks are defined via the leptonic or hadronic decay mode of the $W$ boson produced by the top-quark decay in events with a single charged lepton. Differential cross-section measurements of the pseudo-top-quark variables are compared with several Monte Carlo models that implement next-to-leading order or leading-order multi-leg matrix-element calculations.
Measured $t\bar{t}$ differential cross-section and relative uncertainty as a function of the hadronic pseudo-top-quark $p_{\mathrm{T}}(\hat{t}_{\mathrm{h}})$in the muon channel. The results shown in this table are one of the inputs for the combined results.
Measured $t\bar{t}$ differential cross-section and relative uncertainty as a function of the hadronic pseudo-top-quark $p_{\mathrm{T}}(\hat{t}_{\mathrm{h}})$ in the electron channel. The results shown in this table are one of the inputs for the combined results.
Measured $t\bar{t}$ differential cross-section and relative uncertainty as a function of the hadronic pseudo-top-quark $|y(\hat{t}_{\mathrm{h}})|$ in the muon channel. The results shown in this table are one of the inputs for the combined results.
Measured $t\bar{t}$ differential cross-section and relative uncertainty as a function of the hadronic pseudo-top-quark $|y(\hat{t}_{\mathrm{h}})|$ in the electron channel. The results shown in this table are one of the inputs for the combined results.
Measured $t\bar{t}$ differential cross-section and relative uncertainty as a function of the leptonic pseudo-top-quark $p_{\mathrm{T}}(\hat{t}_{\mathrm{l}})$ in the muon channel. The results shown in this table are one of the inputs for the combined results.
Measured $t\bar{t}$ differential cross-section and relative uncertainty as a function of the leptonic pseudo-top-quark $p_{\mathrm{T}}(\hat{t}_{\mathrm{l}})$ in the electron channel. The results shown in this table are one of the inputs for the combined results.
Measured $t\bar{t}$ differential cross-section and relative uncertainty as a function of the leptonic pseudo-top-quark $|y(\hat{t}_{\mathrm{l}})|$ in the muon channel. The results shown in this table are one of the inputs for the combined results.
Measured $t\bar{t}$ differential cross-section and relative uncertainty as a function of the leptonic pseudo-top-quark $|y(\hat{t}_{\mathrm{l}})|$ in the electron channel. The results shown in this table are one of the inputs for the combined results.
Measured $t\bar{t}$ differential cross-section and relative uncertainty as a function of the pseudo-top-quark-pair $p_{\mathrm{T}}(\hat{t}_{\mathrm{l}}\hat{t}_{\mathrm{h}})$ in the muon channel.The results shown in this table are one of the inputs for the combined results.
Measured $t\bar{t}$ differential cross-section and relative uncertainty as a function of the pseudo-top-quark-pair $p_{\mathrm{T}}(\hat{t}_{\mathrm{l}}\hat{t}_{\mathrm{h}})$ in the electron channel. The results shown in this table are one of the inputs for the combined results.
Measured $t\bar{t}$ differential cross-section and relative uncertainty as a function of the pseudo-top-quark-pair $|y(\hat{t}_{\mathrm{l}}\hat{t}_{\mathrm{h}})|$ in the muon channel. The results shown in this table are one of the inputs for the combined results.
Measured $t\bar{t}$ differential cross-section and relative uncertainty as a function of the pseudo-top-quark-pair $|y(\hat{t}_{\mathrm{l}}\hat{t}_{\mathrm{h}})|$ in the electron channel. The results shown in this table are one of the inputs for the combined results.
Measured $t\bar{t}$ differential cross-section and relative uncertainty as a function of the pseudo-top-quark-pair $m(\hat{t}_{\mathrm{l}}\hat{t}_{\mathrm{h}})$ in the muon channel. The results shown in this table are one of the inputs for the combined results.
Measured $t\bar{t}$ differential cross-section and relative uncertainty as a function of the pseudo-top-quark-pair $m(\hat{t}_{\mathrm{l}}\hat{t}_{\mathrm{h}})$ in the electron channel. The results shown in this table are one of the inputs for the combined results.
Measured $t\bar{t}$ differential cross-section and relative uncertainty as a function of the hadronic pseudo-top-quark $p_{\mathrm{T}}(\hat{t}_{\mathrm{h}})$ after the electron and muon channel combination. The results shown in this table correspond to the results presented in figure 11(a).
Measured $t\bar{t}$ differential cross-section and relative uncertainty as a function of the hadronic pseudo-top-quark $|y(\hat{t}_{\mathrm{h}})|$ after the electron and muon channel combination. The results shown in this table correspond to the results presentedin figure 12(a).
Measured $t\bar{t}$ differential cross-section and relative uncertainty as a function of theleptonic pseudo-top-quark $p_{\mathrm{T}}(\hat{t}_{\mathrm{l}})$ after the electron and muon channel combination.The results shown in this table correspond to the results presented in figure 11(b).
Measured $t\bar{t}$ differential cross-section and relative uncertaintyas a function of the leptonic pseudo-top-quark $|y(\hat{t}_{\mathrm{l}})|$ after the electron and muon channel combination.The results shown in this table correspond to the results presented in figure 12(b).
Measured $t\bar{t}$ differential cross-section and relative uncertainty as a function ofthe pseudo-top-quark-pair $p_{\mathrm{T}}(\hat{t}_{\mathrm{l}}\hat{t}_{\mathrm{h}})$ after the electron and muon channel combination.The results shown in this table correspond to the results presented in figure 13(a).
Measured $t\bar{t}$ differential cross-section and relative uncertainty as a function of the pseudo-top-quark-pair $|y(\hat{t}_{\mathrm{l}}\hat{t}_{\mathrm{h}})|$ after the electron and muon channel combination.The results shown in this table correspond to the results presented in figure 13(b).
Measured $t\bar{t}$ differential cross-section and relative uncertainty as a function of the pseudo-top-quark-pair $m(\hat{t}_{\mathrm{l}}\hat{t}_{\mathrm{h}})$after the electron and muon channel combination. The results shown in this table correspond to the results presented in figure 13(c).
This paper presents the measurement of charged-hadron and identified-hadron ($K^\mathrm{0}_\mathrm{S}$, $Λ$, $Ξ^\mathrm{-}$) yields in photo-nuclear collisions using 1.7 $\mathrm{nb^{-1}}$ of $\sqrt{s_\mathrm{NN}} = 5.02$ TeV Pb+Pb data collected in 2018 with the ATLAS detector at the Large Hadron Collider. Candidate photo-nuclear events are selected using a combination of tracking and calorimeter information, including the zero-degree calorimeter. The yields as a function of transverse momentum and rapidity are measured in these photo-nuclear collisions as a function of charged-particle multiplicity. These photo-nuclear results are compared with 0.1 $\mathrm{nb^{-1}}$ of $\sqrt{s_\mathrm{NN}} = 5.02$ TeV $p$+Pb data collected in 2016 by ATLAS using similar charged-particle multiplicity selections. These photo-nuclear measurements shed light on potential quark-gluon plasma formation in photo-nuclear collisions via observables sensitive to radial flow, enhanced baryon-to-meson ratios, and strangeness enhancement. The results are also compared with the Monte Carlo DPMJET-III generator and hydrodynamic calculations to test whether such photo-nuclear collisions may produce small droplets of quark-gluon plasma that flow collectively.
The multiplicity distribution (#it{N}_{ch}^{rec}) from Pb+Pb photo-nuclear collisions.
The multiplicity distribution (#it{N}_{ch}^{rec}) from p+Pb collisions.
The Charged-hadron yields as a function of pT in different y selections in Pb+Pb photo-nuclear collisions.
The Charged-hadron yields as a function of pT in different y selections in p+Pb collisions.
The K^{0}_{S} yields as a function of pT in different y selections in Pb+Pb photo-nuclear collisions.
The #Lambda yields as a function of pT in different y selections in Pb+Pb photo-nuclear collisions.
The #Xi^{-} yields as a function of pT in different y selections in Pb+Pb photo-nuclear collisions.
The K^{0}_{S} yields as a function of pT in different y selections in p+Pb collisions.
The #Lambda yields as a function of pT in different y selections in p+Pb collisions.
The #Xi^{-} yields as a function of pT in different y selections in p+Pb collisions.
The Charged-hadron and identified-hadron yields as a function of y in Pb+Pb photo-nuclear collisions.
The Charged-hadron and identified-hadron yields as a function of y in Pb+Pb photo-nuclear collisions.
The Charged-hadron and identified-hadron yields as a function of y in p+Pb collisions.
The Charged-hadron and identified-hadron yields as a function of y in p+Pb collisions.
The meanpT of charged hadrons and identified hadrons as a function of Nchrec in Pb+Pb photo-nuclear collisions.
The meanpT of charged hadrons and identified hadrons as a function of Nchrec in Pb+Pb photo-nuclear collisions.
The meanpT of charged hadrons and identified hadrons as a function of Nchrec in Pb+Pb photo-nuclear collisions.
The meanpT of charged hadrons and identified hadrons as a function of Nchrec in p+Pb collisions.
The meanpT of charged hadrons and identified hadrons as a function of Nchrec in p+Pb collisions.
The baryon to meson ratio as a function of pT in Pb+Pb photo-nuclear collisions.
The baryon to meson ratio as a function of pT in Pb+Pb photo-nuclear collisions.
The baryon to meson ratio as a function of pT in p+Pb collisions.
The baryon to meson ratio as a function of pT in p+Pb collisions.
The ratios of identified-strange-hadron yield to charged-hadron yields as a function of Nchrec in Pb+Pb photo-nuclear collisions.
The ratios of identified-strange-hadron yield to charged-hadron yields as a function of Nchrec in Pb+Pb photo-nuclear collisions.
The ratios of identified-strange-hadron yield to charged-hadron yields as a function of Nchrec in Pb+Pb photo-nuclear collisions.
The ratios of identified-strange-hadron yield to charged-hadron yields as a function of Nchrec in p+Pb collisions.
The ratios of identified-strange-hadron yield to charged-hadron yields as a function of Nchrec in p+Pb collisions.
Distributions sensitive to the underlying event are studied in events containing one or more charged-particle jets produced in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector at the Large Hadron Collider (LHC). These measurements reflect 800 inverse microbarns of data taken during 2010. Jets are reconstructed using the antikt algorithm with radius parameter R varying between 0.2 and 1.0. Distributions of the charged-particle multiplicity, the scalar sum of the transverse momentum of charged particles, and the average charged-particle pT are measured as functions of pT^JET in regions transverse to and opposite the leading jet for 4 GeV < pT^JET < 100 GeV. In addition, the R-dependence of the mean values of these observables is studied. In the transverse region, both the multiplicity and the scalar sum of the transverse momentum at fixed pT^JET vary significantly with R, while the average charged-particle transverse momentum has a minimal dependence on R. Predictions from several Monte Carlo tunes have been compared to the data; the predictions from Pythia 6, based on tunes that have been determined using LHC data, show reasonable agreement with the data, including the dependence on R. Comparisons with other generators indicate that additional tuning of soft-QCD parameters is necessary for these generators. The measurements presented here provide a testing ground for further development of the Monte Carlo models.
Mean value of N(C=CHARGED) v jet PT for R=0.2.
Mean value of N(C=CHARGED) v jet PT for R=0.4.
Mean value of N(C=CHARGED) v jet PT for R=0.6.
Mean value of N(C=CHARGED) v jet PT for R=0.8.
Mean value of N(C=CHARGED) v jet PT for R=1.0.
Mean value of PT(C=AVERAGE) v jet PT for R=0.2.
Mean value of PT(C=AVERAGE) v jet PT for R=0.4.
Mean value of PT(C=AVERAGE) v jet PT for R=0.6.
Mean value of PT(C=AVERAGE) v jet PT for R=0.8.
Mean value of PT(C=AVERAGE) v jet PT for R=1.0.
Mean value of SUM(PT) v jet PT for R=0.2.
Mean value of SUM(PT) v jet PT for R=0.4.
Mean value of SUM(PT) v jet PT for R=0.6.
Mean value of SUM(PT) v jet PT for R=0.8.
Mean value of SUM(PT) v jet PT for R=1.0.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.2 and jet PT in the range 4 to 5 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.2 and jet PT in the range 5 to 6 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.2 and jet PT in the range 6 to 8 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.2 and jet PT in the range 8 to 11 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.2 and jet PT in the range 11 to 14 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.2 and jet PT in the range 14 to 19 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.2 and jet PT in the range 19 to 24 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.2 and jet PT in the range 24 to 31 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.2 and jet PT in the range 31 to 50 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.2 and jet PT in the range 50 to 100 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.4 and jet PT in the range 4 to 5 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.4 and jet PT in the range 5 to 6 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.4 and jet PT in the range 6 to 8 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.4 and jet PT in the range 8 to 11 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.4 and jet PT in the range 11 to 14 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.4 and jet PT in the range 14 to 19 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.4 and jet PT in the range 19 to 24 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.4 and jet PT in the range 24 to 31 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.4 and jet PT in the range 31 to 50 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.4 and jet PT in the range 50 to 100 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.6 and jet PT in the range 4 to 5 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.6 and jet PT in the range 5 to 6 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.6 and jet PT in the range 6 to 8 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.6 and jet PT in the range 8 to 11 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.6 and jet PT in the range 11 to 14 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.6 and jet PT in the range 14 to 19 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.6 and jet PT in the range 19 to 24 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.6 and jet PT in the range 24 to 31 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.6 and jet PT in the range 31 to 50 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.6 and jet PT in the range 50 to 100 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.8 and jet PT in the range 4 to 5 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.8 and jet PT in the range 5 to 6 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.8 and jet PT in the range 6 to 8 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.8 and jet PT in the range 8 to 11 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.8 and jet PT in the range 11 to 14 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.8 and jet PT in the range 14 to 19 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.8 and jet PT in the range 19 to 24 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.8 and jet PT in the range 24 to 31 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.8 and jet PT in the range 31 to 50 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=0.8 and jet PT in the range 50 to 100 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=1.0 and jet PT in the range 4 to 5 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=1.0 and jet PT in the range 5 to 6 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=1.0 and jet PT in the range 6 to 8 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=1.0 and jet PT in the range 8 to 11 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=1.0 and jet PT in the range 11 to 14 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=1.0 and jet PT in the range 14 to 19 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=1.0 and jet PT in the range 19 to 24 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=1.0 and jet PT in the range 24 to 31 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=1.0 and jet PT in the range 31 to 50 GeV.
Distribution of the variable N(C=CHARGED) in the AWAY and TRANSVERSE regions for R=1.0 and jet PT in the range 50 to 100 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.2 and jet PT in the range 4 to 5 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.2 and jet PT in the range 5 to 6 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.2 and jet PT in the range 6 to 8 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.2 and jet PT in the range 8 to 11 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.2 and jet PT in the range 11 to 14 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.2 and jet PT in the range 14 to 19 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.2 and jet PT in the range 19 to 24 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.2 and jet PT in the range 24 to 31 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.2 and jet PT in the range 31 to 50 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.2 and jet PT in the range 50 to 100 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.4 and jet PT in the range 4 to 5 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.4 and jet PT in the range 5 to 6 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.4 and jet PT in the range 6 to 8 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.4 and jet PT in the range 8 to 11 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.4 and jet PT in the range 11 to 14 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.4 and jet PT in the range 14 to 19 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.4 and jet PT in the range 19 to 24 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.4 and jet PT in the range 24 to 31 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.4 and jet PT in the range 31 to 50 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.4 and jet PT in the range 50 to 100 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.6 and jet PT in the range 4 to 5 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.6 and jet PT in the range 5 to 6 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.6 and jet PT in the range 6 to 8 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.6 and jet PT in the range 8 to 11 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.6 and jet PT in the range 11 to 14 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.6 and jet PT in the range 14 to 19 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.6 and jet PT in the range 19 to 24 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.6 and jet PT in the range 24 to 31 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.6 and jet PT in the range 31 to 50 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.6 and jet PT in the range 50 to 100 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.8 and jet PT in the range 4 to 5 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.8 and jet PT in the range 5 to 6 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.8 and jet PT in the range 6 to 8 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.8 and jet PT in the range 8 to 11 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.8 and jet PT in the range 11 to 14 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.8 and jet PT in the range 14 to 19 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.8 and jet PT in the range 19 to 24 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.8 and jet PT in the range 24 to 31 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.8 and jet PT in the range 31 to 50 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=0.8 and jet PT in the range 50 to 100 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=1.0 and jet PT in the range 4 to 5 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=1.0 and jet PT in the range 5 to 6 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=1.0 and jet PT in the range 6 to 8 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=1.0 and jet PT in the range 8 to 11 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=1.0 and jet PT in the range 11 to 14 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=1.0 and jet PT in the range 14 to 19 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=1.0 and jet PT in the range 19 to 24 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=1.0 and jet PT in the range 24 to 31 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=1.0 and jet PT in the range 31 to 50 GeV.
Distribution of the variable PT(C=AVERAGE) in the AWAY and TRANSVERSE regions for R=1.0 and jet PT in the range 50 to 100 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.2 and jet PT in the range 4 to 5 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.2 and jet PT in the range 5 to 6 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.2 and jet PT in the range 6 to 8 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.2 and jet PT in the range 8 to 11 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.2 and jet PT in the range 11 to 14 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.2 and jet PT in the range 14 to 19 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.2 and jet PT in the range 19 to 24 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.2 and jet PT in the range 24 to 31 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.2 and jet PT in the range 31 to 50 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.2 and jet PT in the range 50 to 100 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.4 and jet PT in the range 4 to 5 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.4 and jet PT in the range 5 to 6 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.4 and jet PT in the range 6 to 8 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.4 and jet PT in the range 8 to 11 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.4 and jet PT in the range 11 to 14 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.4 and jet PT in the range 14 to 19 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.4 and jet PT in the range 19 to 24 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.4 and jet PT in the range 24 to 31 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.4 and jet PT in the range 31 to 50 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.4 and jet PT in the range 50 to 100 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.6 and jet PT in the range 4 to 5 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.6 and jet PT in the range 5 to 6 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.6 and jet PT in the range 6 to 8 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.6 and jet PT in the range 8 to 11 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.6 and jet PT in the range 11 to 14 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.6 and jet PT in the range 14 to 19 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.6 and jet PT in the range 19 to 24 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.6 and jet PT in the range 24 to 31 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.6 and jet PT in the range 31 to 50 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.6 and jet PT in the range 50 to 100 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.8 and jet PT in the range 4 to 5 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.8 and jet PT in the range 5 to 6 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.8 and jet PT in the range 6 to 8 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.8 and jet PT in the range 8 to 11 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.8 and jet PT in the range 11 to 14 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.8 and jet PT in the range 14 to 19 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.8 and jet PT in the range 19 to 24 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.8 and jet PT in the range 24 to 31 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.8 and jet PT in the range 31 to 50 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=0.8 and jet PT in the range 50 to 100 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=1.0 and jet PT in the range 4 to 5 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=1.0 and jet PT in the range 5 to 6 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=1.0 and jet PT in the range 6 to 8 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=1.0 and jet PT in the range 8 to 11 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=1.0 and jet PT in the range 11 to 14 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=1.0 and jet PT in the range 14 to 19 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=1.0 and jet PT in the range 19 to 24 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=1.0 and jet PT in the range 24 to 31 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=1.0 and jet PT in the range 31 to 50 GeV.
Distribution of the variable SUM(PT) in the AWAY and TRANSVERSE regions for R=1.0 and jet PT in the range 50 to 100 GeV.
High-energy nuclear collisions create a quark-gluon plasma, whose initial condition and subsequent expansion vary from event to event, impacting the distribution of the event-wise average transverse momentum ($P([p_{\mathrm{T}}])$). Distinguishing between contributions from fluctuations in the size of the nuclear overlap area (geometrical component) and other sources at fixed size (intrinsic component) presents a challenge. Here, these two components are distinguished by measuring the mean, variance, and skewness of $P([p_{\mathrm{T}}])$ in $^{208}$Pb+$^{208}$Pb and $^{129}$Xe+$^{129}$Xe collisions at $\sqrt{s_{{\mathrm{NN}}}} = 5.02$ and 5.44 TeV, respectively, using the ATLAS detector at the LHC. All observables show distinct changes in behavior in ultra-central collisions, where the geometrical variations are suppressed as the overlap area reaches its maximum. These results demonstrate a new technique to disentangle geometrical and intrinsic fluctuations, enabling constraints on initial condition and properties of the quark-gluon plasma, such as the speed of sound.
Data from Figure 1, panel a, $\left\langle[p_{T}]\right\rangle$ vs $N_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5
Data from Figure 1, panel b, $\left\langle[p_{T}]\right\rangle$ vs $N_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5
Data from Figure 1, panel b, $\left\langle[p_{T}]\right\rangle$ vs $N_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5
Data from Figure 1, panel c, $k_{2}$ vs $N_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5
Data from Figure 1, panel c, $k_{2}$ vs $N_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5
Data from Figure 1, panel d, $k_{3}$ vs $N_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5
Data from Figure 1, panel d, $k_{3}$ vs $N_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5
Data from Figure 2, panel a, $N_{ch}k_{2}$ vs $N_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5
Data from Figure 2, panel a, $N_{ch}k_{2}$ vs $N_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5
Data from Figure 2, panel b, $N^{2}_{ch}k_{3}$ vs $N_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5
Data from Figure 2, panel b, $N^{2}_{ch}k_{3}$ vs $N_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5
Data from Figure 2, panel c, $\Gamma$ vs $N_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5
Data from Figure 2, panel c, $\Gamma$ vs $N_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5
Data from Figure 3, panel a, $\left\langle[p_{T}]\right\rangle / \left\langle[p_{T}]\right\rangle^{5\%}$ vs $N_{ch}/N^{5\%}_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5
Data from Figure 3, panel a, $\left\langle[p_{T}]\right\rangle / \left\langle[p_{T}]\right\rangle^{5\%}$ vs $N_{ch}/N^{5\%}_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5
Data from Figure 3, panel b, $k_{2}/k^{5\%}_{2} vs N_{ch}/N^{5\%}_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5
Data from Figure 3, panel b, $k_{2}/k^{5\%}_{2} vs N_{ch}/N^{5\%}_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5
Data from Figure 3, panel c, $k_{3}/k^{5\%}_{3} vs N_{ch}/N^{5\%}_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5
Data from Figure 3, panel c, $k_{3}/k^{5\%}_{3} vs N_{ch}/N^{5\%}_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5
Data from Figure 3, panel d, $\Gamma/\Gamma^{5\%}$ vs $N_{ch}/N^{5\%}_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5
Data from Figure 3, panel d, $\Gamma/\Gamma^{5\%}$ vs $N_{ch}/N^{5\%}_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5
Data from Figure 4, $\Delta p_{T}/\left\langle[p_{T}]\right\rangle_{0-1\%}$ vs $\Delta N_{ch}/\left\langle N_{ch}\right\rangle_{0-1\%}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5
Data from Figure 4, $\Delta p_{T}/\left\langle[p_{T}]\right\rangle_{0-1\%}$ vs $\Delta N_{ch}/\left\langle N_{ch}\right\rangle_{0-1\%}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5
Data from Figure 4, $\Delta p_{T}/\left\langle[p_{T}]\right\rangle_{0-1\%}$ vs $\Delta N_{ch}/\left\langle N_{ch}\right\rangle_{0-1\%}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 2 GeV/c, $|\eta|< $ 2.5
Data from Figure 4, $\Delta p_{T}/\left\langle[p_{T}]\right\rangle_{0-1\%}$ vs $\Delta N_{ch}/\left\langle N_{ch}\right\rangle_{0-1\%}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 2 GeV/c, $|\eta|< $ 2.5
Data from Second Supplementary Figure, Fig 6, panel a, Correlation between FCal $\Sigma E_{T}$ and $N_{ch}$ in Pb+Pb collisions
Data from Second Supplementary Figure, Fig 6, panel b, Correlation between $[p_{T}]$ - $\left\langle[p_{T}]\right\rangle_{0-1\%}$ vs $\Delta N_{ch}$/$\left\langle N_{ch}\right\rangle_{0-1\%}$ in Pb+Pb collisions
Data from Third Supplementary Figure, Fig 7, Normalized Event distribution of $N_{ch}$ /$N^{5\%}_{ch}$ for Pb+Pb collisions
Data from Third Supplementary Figure, Fig 7, Normalized Event distribution of $N_{ch}$ / $N^{5\%}_{ch}$ for Xe+Xe collisions
Data from Fourth Supplementary Figure, Fig 8, panel a, $\gamma$ vs $N_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5
Data from Fourth Supplementary Figure, Fig 8, panel a, $\gamma$ vs $N_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5
Data from Fourth Supplementary Figure, Fig 8, panel b, $\gamma/\gamma^{5\%}$ vs $N_{ch}/N^{5\%}_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5
Data from Fourth Supplementary Figure, Fig 8, panel b, $\gamma/\gamma^{5\%}$ vs $N_{ch}/N^{5\%}_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5
Data from Auxiliary Fig 1 panel a, Correlation between FCal $\Sigma E_{T}$ and $N_{ch}$ in Xe+Xe collisions
Data from Auxiliary Fig 1 panel b, Correlation between $[p_{T}]$ - $\left\langle[p_{T}]\right\rangle_{0-1\%}$ vs $\Delta N_{ch}$/$\left\langle N_{ch}\right\rangle_{0-1\%}$ in Xe+Xe collisions
Data from Auxiliary Fig 2 panel b, $N_{ch}$ /$N^{5\%}_{ch}$ vs Centrality [\%] for Pb+Pb collisions
Data from Auxiliary Fig 2 panel b, $N_{ch}$ /$N^{5\%}_{ch}$ vs Centrality [\%] for Xe+Xe collisions
Data from Auxiliary Fig 3 panel b, $[p_{T}]$ vs $N_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5
Data from Auxiliary Figure 4, $\Delta p_{T}/\left\langle[p_{T}]\right\rangle_{0-0.5\%}$ vs $\Delta N_{ch}/\left\langle N_{ch}\right\rangle_{0-0.5\%}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5
Data from Auxiliary Figure 4, $\Delta p_{T}/\left\langle[p_{T}]\right\rangle_{0-0.5\%}$ vs $\Delta N_{ch}/\left\langle N_{ch}\right\rangle_{0-0.5\%}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5
Data from Auxiliary Figure 4, $\Delta p_{T}/\left\langle[p_{T}]\right\rangle_{0-0.5\%}$ vs $\Delta N_{ch}/\left\langle N_{ch}\right\rangle_{0-0.5\%}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 2 GeV/c, $|\eta|< $ 2.5
Data from Auxiliary Figure 4, $\Delta p_{T}/\left\langle[p_{T}]\right\rangle_{0-0.5\%}$ vs $\Delta N_{ch}/\left\langle N_{ch}\right\rangle_{0-0.5\%}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 2 GeV/c, $|\eta|< $ 2.5
Distributions sensitive to the underlying event in QCD jet events have been measured with the ATLAS detector at the LHC, based on 37/pb of proton-proton collision data collected at a centre-of-mass energy of 7 TeV. Charged-particle mean $p_T$ and densities of all-particle $E_T$ and charged-particle multiplicity and $p_T$ have been measured in regions azimuthally transverse to the hardest jet in each event. These are presented both as one-dimensional distributions and with their mean values as functions of the leading-jet transverse momentum from 20 GeV to 800 GeV. The correlation of charged-particle mean $p_T$ with charged-particle multiplicity is also studied, and the $E_T$ densities include the forward rapidity region; these features provide extra data constraints for Monte Carlo modelling of colour reconnection and beam-remnant effects respectively. For the first time, underlying event observables have been computed separately for inclusive jet and exclusive dijet event selections, allowing more detailed study of the interplay of multiple partonic scattering and QCD radiation contributions to the underlying event. Comparisons to the predictions of different Monte Carlo models show a need for further model tuning, but the standard approach is found to generally reproduce the features of the underlying event in both types of event selection.
A measurement of charged-particle distributions sensitive to the properties of the underlying event is presented for an inclusive sample of events containing a Z-boson , decaying to an electron or muon pair. The measurement is based on data collected using the ATLAS detector at the LHC in proton-proton collisions at a centre-of-mass energy of 7 TeV with an integrated luminosity of $4.6$ fb$^{-1}$. Distributions of the charged particle multiplicity and of the charged particle transverse momentum are measured in regions of azimuthal angle defined with respect to the Z-boson direction. The measured distributions are compared to similar distributions measured in jet events, and to the predictions of various Monte Carlo generators implementing different underlying event models.
Towards scalar pT sum density vs Z-boson pT, Born leptons : Statistical and systematic errors are added in quadrature.
Transverse scalar pT sum density vs Z-boson pT, Born leptons : Statistical and systematic errors are added in quadrature.
Away scalar pT sum density vs Z-boson pT, Born leptons : Statistical and systematic errors are added in quadrature.
Trans.min. scalar pT sum density vs Z-boson pT, Born leptons : Statistical and systematic errors are added in quadrature.
Trans.max. scalar pT sum density vs Z-boson pT, Born leptons : Statistical and systematic errors are added in quadrature.
Towards charged multiplicity density vs Z-boson pT, Born leptons : Statistical and systematic errors are added in quadrature.
Transverse charged multiplicity density vs Z-boson pT, Born leptons : Statistical and systematic errors are added in quadrature.
Away charged multiplicity density vs Z-boson pT, Born leptons : Statistical and systematic errors are added in quadrature.
Trans.min. charged multiplicity density vs Z-boson pT, Born leptons : Statistical and systematic errors are added in quadrature.
Towards scalar pT sum distribution, Z-boson pT = 0 - 5 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Towards scalar pT sum distribution, Z-boson pT = 5 - 10 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Towards scalar pT sum distribution, Z-boson pT = 10 - 20 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Towards scalar pT sum distribution, Z-boson pT = 20 - 50 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Towards scalar pT sum distribution, Z-boson pT = 50 - 110 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Towards scalar pT sum distribution, Z-boson pT = 110 - 500 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Trans.max. charged multiplicity density vs Z-boson pT, Born leptons : Statistical and systematic errors are added in quadrature.
Towards charged multiplicity distribution, Z-boson pT = 0 - 5 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Towards charged multiplicity distribution, Z-boson pT = 5 - 10 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Towards charged multiplicity distribution, Z-boson pT = 10 - 20 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Towards charged multiplicity distribution, Z-boson pT = 20 - 50 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Towards charged multiplicity distribution, Z-boson pT = 50 - 110 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Towards charged multiplicity distribution, Z-boson pT = 110 - 500 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Transverse charged multiplicity distribution, Z-boson pT = 0 - 5 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Transverse charged multiplicity distribution, Z-boson pT = 5 - 10 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Transverse charged multiplicity distribution, Z-boson pT = 10 - 20 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Transverse charged multiplicity distribution, Z-boson pT = 20 - 50 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Transverse charged multiplicity distribution, Z-boson pT = 50 - 110 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Transverse charged multiplicity distribution, Z-boson pT = 110 - 500 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Trans.min. charged multiplicity distribution, Z-boson pT = 0 - 5 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Trans.min. charged multiplicity distribution, Z-boson pT = 5 - 10 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Trans.min. charged multiplicity distribution, Z-boson pT = 10 - 20 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Trans.min. charged multiplicity distribution, Z-boson pT = 20 - 50 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Trans.min. charged multiplicity distribution, Z-boson pT = 50 - 110 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Trans.min. charged multiplicity distribution, Z-boson pT = 110 - 500 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Trans.max. charged multiplicity distribution, Z-boson pT = 0 - 5 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Trans.max. charged multiplicity distribution, Z-boson pT = 5 - 10 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Trans.max. charged multiplicity distribution, Z-boson pT = 10 - 20 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Trans.max. charged multiplicity distribution, Z-boson pT = 20 - 50 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Trans.max. charged multiplicity distribution, Z-boson pT = 50 - 110 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Trans.max. charged multiplicity distribution, Z-boson pT = 110 - 500 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Transverse scalar pT sum distribution, Z-boson pT = 0 - 5 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Transverse scalar pT sum distribution, Z-boson pT = 5 - 10 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Transverse scalar pT sum distribution, Z-boson pT = 10 - 20 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Transverse scalar pT sum distribution, Z-boson pT = 20 - 50 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Transverse scalar pT sum distribution, Z-boson pT = 50 - 110 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Transverse scalar pT sum distribution, Z-boson pT = 110 - 500 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Towards <mean pT(charged)> vs Z-boson pT, Born leptons : Statistical and systematic errors are added in quadrature.
Transverse <mean pT(charged)> vs Z-boson pT, Born leptons : Statistical and systematic errors are added in quadrature.
Away <mean pT(charged)> vs Z-boson pT, Born leptons : Statistical and systematic errors are added in quadrature.
Towards <mean pT(charged)> vs charged multiplicity, Born leptons : Statistical and systematic errors are added in quadrature.
Transverse <mean pT(charged)> vs charged multiplicity, Born leptons : Statistical and systematic errors are added in quadrature.
Away <mean pT(charged)> vs charged multiplicity, Born leptons : Statistical and systematic errors are added in quadrature.
Trans.min. scalar pT sum distribution, Z-boson pT = 0 - 5 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Trans.min. scalar pT sum distribution, Z-boson pT = 5 - 10 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Trans.min. scalar pT sum distribution, Z-boson pT = 10 - 20 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Trans.min. scalar pT sum distribution, Z-boson pT = 20 - 50 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Trans.min. scalar pT sum distribution, Z-boson pT = 50 - 110 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Trans.min. scalar pT sum distribution, Z-boson pT = 110 - 500 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Trans.diff. scalar pT sum density vs Z-boson pT, Born leptons : Statistical and systematic errors are added in quadrature.
Trans.diff. charged multiplicity density vs Z-boson pT, Born leptons : Statistical and systematic errors are added in quadrature.
Trans.max. scalar pT sum distribution, Z-boson pT = 0 - 5 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Trans.max. scalar pT sum distribution, Z-boson pT = 5 - 10 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Trans.max. scalar pT sum distribution, Z-boson pT = 10 - 20 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Trans.max. scalar pT sum distribution, Z-boson pT = 20 - 50 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Trans.max. scalar pT sum distribution, Z-boson pT = 50 - 110 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Trans.max. scalar pT sum distribution, Z-boson pT = 110 - 500 GeV, Born leptons : Statistical and systematic errors are added in quadrature.
Towards scalar pT sum density vs Z-boson pT, Dressed leptons : Statistical and systematic errors are added in quadrature.
Transverse scalar pT sum density vs Z-boson pT, Dressed leptons : Statistical and systematic errors are added in quadrature.
Away scalar pT sum density vs Z-boson pT, Dressed leptons : Statistical and systematic errors are added in quadrature.
Trans.min. scalar pT sum density vs Z-boson pT, Dressed leptons : Statistical and systematic errors are added in quadrature.
Trans.max. scalar pT sum density vs Z-boson pT, Dressed leptons : Statistical and systematic errors are added in quadrature.
Towards charged multiplicity density vs Z-boson pT, Dressed leptons : Statistical and systematic errors are added in quadrature.
Transverse charged multiplicity density vs Z-boson pT, Dressed leptons : Statistical and systematic errors are added in quadrature.
Away charged multiplicity density vs Z-boson pT, Dressed leptons : Statistical and systematic errors are added in quadrature.
Trans.min. charged multiplicity density vs Z-boson pT, Dressed leptons : Statistical and systematic errors are added in quadrature.
Towards scalar pT sum distribution, Z-boson pT = 0 - 5 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Towards scalar pT sum distribution, Z-boson pT = 5 - 10 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Towards scalar pT sum distribution, Z-boson pT = 10 - 20 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Towards scalar pT sum distribution, Z-boson pT = 20 - 50 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Towards scalar pT sum distribution, Z-boson pT = 50 - 110 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Towards scalar pT sum distribution, Z-boson pT = 110 - 500 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Trans.max. charged multiplicity density vs Z-boson pT, Dressed leptons : Statistical and systematic errors are added in quadrature.
Towards charged multiplicity distribution, Z-boson pT = 0 - 5 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Towards charged multiplicity distribution, Z-boson pT = 5 - 10 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Towards charged multiplicity distribution, Z-boson pT = 10 - 20 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Towards charged multiplicity distribution, Z-boson pT = 20 - 50 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Towards charged multiplicity distribution, Z-boson pT = 50 - 110 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Towards charged multiplicity distribution, Z-boson pT = 110 - 500 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Transverse charged multiplicity distribution, Z-boson pT = 0 - 5 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Transverse charged multiplicity distribution, Z-boson pT = 5 - 10 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Transverse charged multiplicity distribution, Z-boson pT = 10 - 20 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Transverse charged multiplicity distribution, Z-boson pT = 20 - 50 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Transverse charged multiplicity distribution, Z-boson pT = 50 - 110 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Transverse charged multiplicity distribution, Z-boson pT = 110 - 500 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Trans.min. charged multiplicity distribution, Z-boson pT = 0 - 5 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Trans.min. charged multiplicity distribution, Z-boson pT = 5 - 10 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Trans.min. charged multiplicity distribution, Z-boson pT = 10 - 20 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Trans.min. charged multiplicity distribution, Z-boson pT = 20 - 50 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Trans.min. charged multiplicity distribution, Z-boson pT = 50 - 110 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Trans.min. charged multiplicity distribution, Z-boson pT = 110 - 500 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Trans.max. charged multiplicity distribution, Z-boson pT = 0 - 5 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Trans.max. charged multiplicity distribution, Z-boson pT = 5 - 10 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Trans.max. charged multiplicity distribution, Z-boson pT = 10 - 20 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Trans.max. charged multiplicity distribution, Z-boson pT = 20 - 50 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Trans.max. charged multiplicity distribution, Z-boson pT = 50 - 110 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Trans.max. charged multiplicity distribution, Z-boson pT = 110 - 500 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Transverse scalar pT sum distribution, Z-boson pT = 0 - 5 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Transverse scalar pT sum distribution, Z-boson pT = 5 - 10 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Transverse scalar pT sum distribution, Z-boson pT = 10 - 20 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Transverse scalar pT sum distribution, Z-boson pT = 20 - 50 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Transverse scalar pT sum distribution, Z-boson pT = 50 - 110 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Transverse scalar pT sum distribution, Z-boson pT = 110 - 500 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Towards <mean pT(charged)> vs Z-boson pT, Dressed leptons : Statistical and systematic errors are added in quadrature.
Transverse <mean pT(charged)> vs Z-boson pT, Dressed leptons : Statistical and systematic errors are added in quadrature.
Away <mean pT(charged)> vs Z-boson pT, Dressed leptons : Statistical and systematic errors are added in quadrature.
Towards <mean pT(charged)> vs charged multiplicity, dressed leptons : Statistical and systematic errors are added in quadrature.
Transverse <mean pT(charged)> vs charged multiplicity, dressed leptons : Statistical and systematic errors are added in quadrature.
Away <mean pT(charged)> vs charged multiplicity, dressed leptons : Statistical and systematic errors are added in quadrature.
Trans.min. scalar pT sum distribution, Z-boson pT = 0 - 5 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Trans.min. scalar pT sum distribution, Z-boson pT = 5 - 10 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Trans.min. scalar pT sum distribution, Z-boson pT = 10 - 20 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Trans.min. scalar pT sum distribution, Z-boson pT = 20 - 50 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Trans.min. scalar pT sum distribution, Z-boson pT = 50 - 110 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Trans.min. scalar pT sum distribution, Z-boson pT = 110 - 500 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Trans.diff. scalar pT sum density vs Z-boson pT, Dressed leptons : Statistical and systematic errors are added in quadrature.
Trans.diff. charged multiplicity density vs Z-boson pT, Dressed leptons : Statistical and systematic errors are added in quadrature.
Trans.max. scalar pT sum distribution, Z-boson pT = 0 - 5 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Trans.max. scalar pT sum distribution, Z-boson pT = 5 - 10 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Trans.max. scalar pT sum distribution, Z-boson pT = 10 - 20 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Trans.max. scalar pT sum distribution, Z-boson pT = 20 - 50 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Trans.max. scalar pT sum distribution, Z-boson pT = 50 - 110 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
Trans.max. scalar pT sum distribution, Z-boson pT = 110 - 500 GeV, Dressed leptons : Statistical and systematic errors are added in quadrature.
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