Showing 10 of 69 results
$Z$ boson events at the Large Hadron Collider can be selected with high purity and are sensitive to a diverse range of QCD phenomena. As a result, these events are often used to probe the nature of the strong force, improve Monte Carlo event generators, and search for deviations from Standard Model predictions. All previous measurements of $Z$ boson production characterize the event properties using a small number of observables and present the results as differential cross sections in predetermined bins. In this analysis, a machine learning method called OmniFold is used to produce a simultaneous measurement of twenty-four $Z$+jets observables using $139$ fb$^{-1}$ of proton-proton collisions at $\sqrt{s}=13$ TeV collected with the ATLAS detector. Unlike any previous fiducial differential cross-section measurement, this result is presented unbinned as a dataset of particle-level events, allowing for flexible re-use in a variety of contexts and for new observables to be constructed from the twenty-four measured observables.
Differential cross-section in bins of dimuon $p_\text{T}$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>
Differential cross-section in bins of dimuon rapidity. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>
Differential cross-section in bins of leading muon $p_\mathrm{T]$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>
Differential cross-section in bins of subleading muon $p_\mathrm{T]$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>
Differential cross-section in bins of leading muon $\eta$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>
Differential cross-section in bins of subleading muon $\eta$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>
Differential cross-section in bins of leading muon $\phi$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>
Differential cross-section in bins of subleading muon $\phi$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>
Differential cross-section in bins of leading charged particle jet $p_\mathrm{T]$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>
Differential cross-section in bins of subleading charged particle jet $p_\mathrm{T]$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>
Differential cross-section in bins of leading charged particle jet rapidity. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>
Differential cross-section in bins of subleading charged particle jet rapidity. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>
Differential cross-section in bins of leading charged particle jet azimuth. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>
Differential cross-section in bins of subleading charged particle jet azimuth. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>
Differential cross-section in bins of leading charged particle jet mass. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>
Differential cross-section in bins of subleading charged particle jet mass. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>
Differential cross-section in bins of leading charged particle jet constituent multiplicity. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>
Differential cross-section in bins of subleading charged particle jet constituent multiplicity. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>
Differential cross-section in bins of leading charged particle jet $\tau_1$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>
Differential cross-section in bins of subleading charged particle jet $\tau_1$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>
Differential cross-section in bins of leading charged particle jet $\tau_2$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>
Differential cross-section in bins of subleading charged particle jet $\tau_2$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>
Differential cross-section in bins of leading charged particle jet $\tau_3$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>
Differential cross-section in bins of subleading charged particle jet $\tau_3$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>
Differential cross-section in bins of leading charged particle jet $\tau_{21}$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>
Differential cross-section in bins of $\Delta R$ between the leading charged particle jet and the dilepton system. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>
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.
Measurements of jet cross-section ratios between inclusive bins of jet multiplicity are performed in 140 fb$^{-1}$ of proton--proton collisions with $\sqrt{s}=13$ TeV center-of-mass energy, recorded with the ATLAS detector at CERN's Large Hadron Collider. Observables that are sensitive the energy-scale and angular distribution of radiation due to the strong interaction in the final state are measured double-differentially, in bins of jet multiplicity, and are unfolded to account for acceptance and detector-related effects. Additionally, the scalar sum of the two leading jets' transverse momenta is measured triple-differentially, in bins of the third jet's transverse momentum as well as bins of jet multiplicity. The measured distributions are used to construct ratios of the inclusive jet-multiplicity bins, which have been shown to be sensitive to the strong coupling $\alpha_{\textrm S}$ while being less sensitive than other observables to systematic uncertainties and parton distribution functions. The measured distributions are compared with state-of-the-art QCD calculations, including next-to-next-to-leading-order predictions. Studies leading to reduced jet energy scale uncertainties significantly improve the precision of this work, and are documented herein.
R32 for $H_{T2}$, 60 GeV < $p_{T,3}$
R32 for $H_{T2}$, 0.05 x $H_{T2} < $p_{T,3}$
R32 for $H_{T2}$, 0.1 x $H_{T2} < $p_{T,3}$
R32 for $H_{T2}$, 0.2 x $H_{T2} < $p_{T,3}$
R32 for $H_{T2}$, 0.3 x $H_{T2} < $p_{T,3}$
R32 for $H_{T2}$, pT,jet
R32 for delta y
R32 for delta y max
R32 for $m_{jj}$
R32 for $m_{jj, max}$
R43 for $H_{T2}$, 60 GeV < $p_{T,3}$
R43 for $H_{T2}$, 0.1 x $H_{T2} < $p_{T,3}$
R43 for $H_{T2}$, 0.3 x $H_{T2} < $p_{T,3}$
R43 for $H_{T2}$, pT,jet
R43 for $Delta y_{jj}$
R43 for $Delta y_{jj, max}$
R43 for $m_{jj}$
R43 for $m_{jj, max}$
R54 for $H_{T2}$, 60 GeV < $p_{T,3}$
R54 for $H_{T2}$, 0.1 x $H_{T2} < $p_{T,3}$
R54 for $H_{T2}$, 0.3 x $H_{T2} < $p_{T,3}$
R54 for $Delta y_{jj}$
R54 for $Delta y_{jj, max}$
R54 for $m_{jj}$
R54 for $m_{jj, max}$
R42 for $H_{T2}$, 60 GeV < $p_{T,3}$
R42 for $H_{T2}$, 0.1 x $H_{T2} < $p_{T,3}$
R42 for $H_{T2}$, 0.3 x $H_{T2} < $p_{T,3}$
R42, pT,jet
R42 for $Delta y_{jj}$
R42 for $Delta y_{jj, max}$
R42 for $m_{jj}$
R42 for $m_{jj}$
HT2, $p_{T,3}$ > 60 GeV, $N_{jet}$ >= 2
HT2, $p_{T,3}$ > 60 GeV, $N_{jet}$ >=3
HT2, $p_{T,3}$ > 60 GeV, $N_{jet}$ >=4
HT2, $p_{T,3}$ > 60 GeV, $N_{jet}$ >= 5
HT2, $p_{T,3}$/HT2 > 0.05, $N_{jet}$ >= 2
HT2, $p_{T,3}$/HT2 > 0.05, $N_{jet}$ >=3
HT2, $p_{T,3}$/HT2 > 0.05, $N_{jet}$ >=4
HT2, $p_{T,3}$/HT2 > 0.05, $N_{jet}$ >= 5
HT2, $p_{T,3}$/HT2 > 0.10, $N_{jet}$ >= 2
HT2, $p_{T,3}$/HT2 > 0.10, $N_{jet}$ >=3
HT2, $p_{T,3}$/HT2 > 0.10, $N_{jet}$ >=4
HT2, $p_{T,3}$/HT2 > 0.10, $N_{jet}$ >= 5
HT2, $p_{T,3}$/HT2 > 0.20, $N_{jet}$ >= 2
HT2, $p_{T,3}$/HT2 > 0.20, $N_{jet}$ >=3
HT2, $p_{T,3}$/HT2 > 0.20, $N_{jet}$ >=4
HT2, $p_{T,3}$/HT2 > 0.20, $N_{jet}$ >= 5
HT2, $p_{T,3}$/HT2 > 0.30, $N_{jet}$ >= 2
HT2, $p_{T,3}$/HT2 > 0.30, $N_{jet}$ >=3
HT2, $p_{T,3}$/HT2 > 0.30, $N_{jet}$ >=4
HT2, $p_{T,3}$/HT2 > 0.30, $N_{jet}$ >= 5
pTnincl
pTnincl
pTnincl
mjj max, $N_{jet}$ >= 2
mjj max, $N_{jet}$ >= 3
mjj max, $N_{jet}$ >= 4
mjj max, $N_{jet}$ >= 5
$m_{jj}$ $N_{jet}$ >= 2
$m_{jj}$ $N_{jet}$ >= 3
$m_{jj}$ $N_{jet}$ >= 4
$m_{jj}$ $N_{jet}$ >= 5
$Delta y_{jj}$ $N_{jet}$ >= 2
$Delta y_{jj}$ $N_{jet}$ >= 3
$Delta y_{jj}$ $N_{jet}$ >= 4
$Delta y_{jj}$ $N_{jet}$ >= 5
$Delta y_{jj, max}$, $N_{jet}$ >= 2
$Delta y_{jj, max}$, $N_{jet}$ >= 3
$Delta y_{jj, max}$, $N_{jet}$ >= 4
$Delta y_{jj, max}$, $N_{jet}$ >= 5
R32 for $H_{T2}$, 60 GeV < $p_{T,3}$
R32 for $H_{T2}$, 0.05 x $H_{T2} < $p_{T,3}$
R32 for $H_{T2}$, 0.1 x $H_{T2} < $p_{T,3}$
R32 for $H_{T2}$, 0.2 x $H_{T2} < $p_{T,3}$
R32 for $H_{T2}$, 0.3 x $H_{T2} < $p_{T,3}$
Properties of the underlying-event in $pp$ interactions are investigated primarily via the strange hadrons $K_{S}^{0}$, $\Lambda$ and $\bar\Lambda$, as reconstructed using the ATLAS detector at the LHC in minimum-bias $pp$ collision data at $\sqrt{s} = 13$ TeV. The hadrons are reconstructed via the identification of the displaced two-particle vertices corresponding to the decay modes $K_{S}^{0}\rightarrow\pi^+\pi^-$, $\Lambda\rightarrow\pi^-p$ and $\bar\Lambda\rightarrow\pi^+\bar{p}$. These are used in the construction of underlying-event observables in azimuthal regions computed relative to the leading charged-particle jet in the event. None of the hadronisation and underlying-event physics models considered can describe the data over the full kinematic range considered. Events with a leading charged-particle jet in the range of $10 < p_T \leq 40$ GeV are studied using the number of prompt charged particles in the transverse region. The ratio $N(\Lambda + \bar\Lambda)/N(K_{S}^{0})$ as a function of the number of such charged particles varies only slightly over this range. This disagrees with the expectations of some of the considered Monte Carlo models.
Mean multiplicity of $K^{0}_{S}$ per unit $(\eta, \phi)$ in the away region vs. leading-jet $p_{T}$
Mean multiplicity of $K^{0}_{S}$ per unit $(\eta, \phi)$ in the towards region vs. leading-jet $p_{T}$
Mean multiplicity of $K^{0}_{S}$ per unit $(\eta, \phi)$ in the transverse region vs. leading-jet $p_{T}$
Mean scalar sum-$p_{T}$ of $K^{0}_{S}$ per unit $(\eta, \phi)$ in the away region vs. leading-jet $p_{T}$
Mean scalar sum-$p_{T}$ of $K^{0}_{S}$ per unit $(\eta, \phi)$ in the towards region vs. leading-jet $p_{T}$
Mean scalar sum-$p_{T}$ of $K^{0}_{S}$ per unit $(\eta, \phi)$ in the transverse region vs. leading-jet $p_{T}$
Ratio of the multiplicity of $K^{0}_{S}$ to prompt charged particles in the away region vs. leading-jet $p_{T}$
Ratio of the multiplicity of $K^{0}_{S}$ to prompt charged particles in the towards region vs. leading-jet $p_{T}$
Ratio of the multiplicity of $K^{0}_{S}$ to prompt charged particles in the transverse region vs. leading-jet $p_{T}$
Ratio of the scalar sum-pt of $K^{0}_{S}$ to prompt charged particles in the away region vs. leading-jet $p_{T}$
Ratio of the scalar sum-pt of $K^{0}_{S}$ to prompt charged particles in the towards region vs. leading-jet $p_{T}$
Ratio of the scalar sum-pt of $K^{0}_{S}$ to prompt charged particles in the transverse region vs. leading-jet $p_{T}$
Mean-$p_{T}$ of $K^{0}_{S}$ in the away region vs. leading-jet $p_{T}$
Mean-$p_{T}$ of $K^{0}_{S}$ in the towards region vs. leading-jet $p_{T}$
Mean-$p_{T}$ of $K^{0}_{S}$ in the transverse region vs. leading-jet $p_{T}$
Mean multiplicity of $\Lambda$ and $\bar{\Lambda}$ per unit $(\eta, \phi)$ in the away region vs. leading-jet $p_{T}$
Mean multiplicity of $\Lambda$ and $\bar{\Lambda}$ per unit $(\eta, \phi)$ in the towards region vs. leading-jet $p_{T}$
Mean multiplicity of $\Lambda$ and $\bar{\Lambda}$ per unit $(\eta, \phi)$ in the transverse region vs. leading-jet $p_{T}$
Mean scalar sum-$p_{T}$ of $\Lambda$ and $\bar{\Lambda}$ per unit $(\eta, \phi)$ in the away region vs. leading-jet $p_{T}$
Mean scalar sum-$p_{T}$ of $\Lambda$ and $\bar{\Lambda}$ per unit $(\eta, \phi)$ in the towards region vs. leading-jet $p_{T}$
Mean scalar sum-$p_{T}$ of $\Lambda$ and $\bar{\Lambda}$ per unit $(\eta, \phi)$ in the transverse region vs. leading-jet $p_{T}$
Ratio of the multiplicity of $\Lambda$ and $\bar{\Lambda}$ to prompt charged particles in the away region vs. leading-jet $p_{T}$
Ratio of the multiplicity of $\Lambda$ and $\bar{\Lambda}$ to prompt charged particles in the towards region vs. leading-jet $p_{T}$
Ratio of the multiplicity of $\Lambda$ and $\bar{\Lambda}$ to prompt charged particles in the transverse region vs. leading-jet $p_{T}$
Ratio of the scalar sum-pt of $\Lambda$ and $\bar{\Lambda}$ to prompt charged particles in the away region vs. leading-jet $p_{T}$
Ratio of the scalar sum-pt of $\Lambda$ and $\bar{\Lambda}$ to prompt charged particles in the towards region vs. leading-jet $p_{T}$
Ratio of the scalar sum-pt of $\Lambda$ and $\bar{\Lambda}$ to prompt charged particles in the transverse region vs. leading-jet $p_{T}$
Ratio of the multiplicity of $\Lambda$ and $\bar{\Lambda}$ to $K^{0}_{S}$ in the away region vs. leading-jet $p_{T}$
Ratio of the multiplicity of $\Lambda$ and $\bar{\Lambda}$ to $K^{0}_{S}$ in the towards region vs. leading-jet $p_{T}$
Ratio of the multiplicity of $\Lambda$ and $\bar{\Lambda}$ to $K^{0}_{S}$ in the transverse region vs. leading-jet $p_{T}$
Ratio of the scalar sum-pt of $\Lambda$ and $\bar{\Lambda}$ to $K^{0}_{S}$ in the away region vs. leading-jet $p_{T}$
Ratio of the scalar sum-pt of $\Lambda$ and $\bar{\Lambda}$ to $K^{0}_{S}$ in the towards region vs. leading-jet $p_{T}$
Ratio of the scalar sum-pt of $\Lambda$ and $\bar{\Lambda}$ to $K^{0}_{S}$ in the transverse region vs. leading-jet $p_{T}$
Mean-$p_{T}$ of $\Lambda$ and $\bar{\Lambda}$ in the away region vs. leading-jet $p_{T}$
Mean-$p_{T}$ of $\Lambda$ and $\bar{\Lambda}$ in the towards region vs. leading-jet $p_{T}$
Mean-$p_{T}$ of $\Lambda$ and $\bar{\Lambda}$ in the transverse region vs. leading-jet $p_{T}$
Mean multiplicity of $K^{0}_{S}$ per unit $(\eta, \phi)$ in the away region vs. $N_\textrm{ch,trans}$
Mean multiplicity of $K^{0}_{S}$ per unit $(\eta, \phi)$ in the towards region vs. $N_\textrm{ch,trans}$
Mean multiplicity of $K^{0}_{S}$ per unit $(\eta, \phi)$ in the transverse region vs. $N_\textrm{ch,trans}$
Mean scalar sum-$p_{T}$ of $K^{0}_{S}$ per unit $(\eta, \phi)$ in the away region vs. $N_\textrm{ch,trans}$
Mean scalar sum-$p_{T}$ of $K^{0}_{S}$ per unit $(\eta, \phi)$ in the towards region vs. $N_\textrm{ch,trans}$
Mean scalar sum-$p_{T}$ of $K^{0}_{S}$ per unit $(\eta, \phi)$ in the transverse region vs. $N_\textrm{ch,trans}$
Ratio of the multiplicity of $K^{0}_{S}$ to prompt charged particles in the away region vs. $N_\textrm{ch,trans}$
Ratio of the multiplicity of $K^{0}_{S}$ to prompt charged particles in the towards region vs. $N_\textrm{ch,trans}$
Ratio of the multiplicity of $K^{0}_{S}$ to prompt charged particles in the transverse region vs. $N_\textrm{ch,trans}$
Ratio of the scalar sum-pt of $K^{0}_{S}$ to prompt charged particles in the away region vs. $N_\textrm{ch,trans}$
Ratio of the scalar sum-pt of $K^{0}_{S}$ to prompt charged particles in the towards region vs. $N_\textrm{ch,trans}$
Ratio of the scalar sum-pt of $K^{0}_{S}$ to prompt charged particles in the transverse region vs. $N_\textrm{ch,trans}$
Mean-$p_{T}$ of $K^{0}_{S}$ in the away region vs. $N_\textrm{ch,trans}$
Mean-$p_{T}$ of $K^{0}_{S}$ in the towards region vs. $N_\textrm{ch,trans}$
Mean-$p_{T}$ of $K^{0}_{S}$ in the transverse region vs. $N_\textrm{ch,trans}$
Mean multiplicity of $\Lambda$ and $\bar{\Lambda}$ per unit $(\eta, \phi)$ in the away region vs. $N_\textrm{ch,trans}$
Mean multiplicity of $\Lambda$ and $\bar{\Lambda}$ per unit $(\eta, \phi)$ in the towards region vs. $N_\textrm{ch,trans}$
Mean multiplicity of $\Lambda$ and $\bar{\Lambda}$ per unit $(\eta, \phi)$ in the transverse region vs. $N_\textrm{ch,trans}$
Mean scalar sum-$p_{T}$ of $\Lambda$ and $\bar{\Lambda}$ per unit $(\eta, \phi)$ in the away region vs. $N_\textrm{ch,trans}$
Mean scalar sum-$p_{T}$ of $\Lambda$ and $\bar{\Lambda}$ per unit $(\eta, \phi)$ in the towards region vs. $N_\textrm{ch,trans}$
Mean scalar sum-$p_{T}$ of $\Lambda$ and $\bar{\Lambda}$ per unit $(\eta, \phi)$ in the transverse region vs. $N_\textrm{ch,trans}$
Ratio of the multiplicity of $\Lambda$ and $\bar{\Lambda}$ to prompt charged particles in the away region vs. $N_\textrm{ch,trans}$
Ratio of the multiplicity of $\Lambda$ and $\bar{\Lambda}$ to prompt charged particles in the towards region vs. $N_\textrm{ch,trans}$
Ratio of the multiplicity of $\Lambda$ and $\bar{\Lambda}$ to prompt charged particles in the transverse region vs. $N_\textrm{ch,trans}$
Ratio of the scalar sum-pt of $\Lambda$ and $\bar{\Lambda}$ to prompt charged particles in the away region vs. $N_\textrm{ch,trans}$
Ratio of the scalar sum-pt of $\Lambda$ and $\bar{\Lambda}$ to prompt charged particles in the towards region vs. $N_\textrm{ch,trans}$
Ratio of the scalar sum-pt of $\Lambda$ and $\bar{\Lambda}$ to prompt charged particles in the transverse region vs. $N_\textrm{ch,trans}$
Ratio of the multiplicity of $\Lambda$ and $\bar{\Lambda}$ to $K^{0}_{S}$ in the away region vs. $N_\textrm{ch,trans}$
Ratio of the multiplicity of $\Lambda$ and $\bar{\Lambda}$ to $K^{0}_{S}$ in the towards region vs. $N_\textrm{ch,trans}$
Ratio of the multiplicity of $\Lambda$ and $\bar{\Lambda}$ to $K^{0}_{S}$ in the transverse region vs. $N_\textrm{ch,trans}$
Ratio of the scalar sum-pt of $\Lambda$ and $\bar{\Lambda}$ to $K^{0}_{S}$ in the away region vs. $N_\textrm{ch,trans}$
Ratio of the scalar sum-pt of $\Lambda$ and $\bar{\Lambda}$ to $K^{0}_{S}$ in the towards region vs. $N_\textrm{ch,trans}$
Ratio of the scalar sum-pt of $\Lambda$ and $\bar{\Lambda}$ to $K^{0}_{S}$ in the transverse region vs. $N_\textrm{ch,trans}$
Mean-$p_{T}$ of $\Lambda$ and $\bar{\Lambda}$ in the away region vs. $N_\textrm{ch,trans}$
Mean-$p_{T}$ of $\Lambda$ and $\bar{\Lambda}$ in the towards region vs. $N_\textrm{ch,trans}$
Mean-$p_{T}$ of $\Lambda$ and $\bar{\Lambda}$ in the transverse region vs. $N_\textrm{ch,trans}$
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.
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
This paper presents a measurement of the production cross-section of a $Z$ boson in association with $b$- or $c$-jets, in proton-proton collisions at $\sqrt{s} = 13$ TeV with the ATLAS experiment at the Large Hadron Collider using data corresponding to an integrated luminosity of 140 fb$^{-1}$. Inclusive and differential cross-sections are measured for events containing a $Z$ boson decaying into electrons or muons and produced in association with at least one $b$-jet, at least one $c$-jet, or at least two $b$-jets with transverse momentum $p_\textrm{T} > 20$ GeV and rapidity $|y| < 2.5$. Predictions from several Monte Carlo generators based on next-to-leading-order matrix elements interfaced with a parton-shower simulation, with different choices of flavour schemes for initial-state partons, are compared with the measured cross-sections. The results are also compared with novel predictions, based on infrared and collinear safe jet flavour dressing algorithms. Selected $Z + \ge 1 c$-jet observables, optimized for sensitivity to intrinsic-charm, are compared with benchmark models with different intrinsic-charm fractions.
Figure 6(left) of the article. Measured fiducial cross sections for events with $Z \left( \rightarrow \ell \ell \right) \geq 1 b$-jet. The thin inner band corresponds to the statistical uncertainty of the data, and the outer band to statistical and systematic uncertainties of the data, added in quadrature.
Figure 6(right) of the article. Measured fiducial cross sections for events with $Z \left( \rightarrow \ell \ell \right) \geq 2 b$-jets. The thin inner band corresponds to the statistical uncertainty of the data, and the outer band to statistical and systematic uncertainties of the data, added in quadrature.
Figure 7 of the article. Measured fiducial cross sections for events with $Z \left( \rightarrow \ell \ell \right) \geq 1 c$-jet. The thin inner band corresponds to the statistical uncertainty of the data, and the outer band to statistical and systematic uncertainties of the data, added in quadrature.
Figure 8(left) of the article. Differential fiducial cross-section of the Z boson $p_T$ in events with $Z \left( \rightarrow \ell\ell \right) + 1 b$-jet. The thin inner band corresponds to the statistical uncertainty of the data, and the outer band to statistical and systematic uncertainties of the data, added in quadrature.
Figure 8(right) of the article. Differential fiducial cross-section of the leading $b$-jet $p_T$ in events with $Z \left( \rightarrow \ell\ell \right) + 1 b$-jet. The thin inner band corresponds to the statistical uncertainty of the data, and the outer band to statistical and systematic uncertainties of the data, added in quadrature.
Figure 9 of the article. Differential fiducial cross-section of the $\Delta R$ between the $Z$ boson and the leading $b$-jet in events with $Z \left( \rightarrow \ell\ell \right) + 1 b$-jet. The thin inner band corresponds to the statistical uncertainty of the data, and the outer band to statistical and systematic uncertainties of the data, added in quadrature.
Figure 10(left) of the article. Differential fiducial cross-section of the $\Delta \phi$ between the leading and sub-leading $b$-jets in events with $Z \left( \rightarrow \ell\ell \right) + 2 b$-jets. The thin inner band corresponds to the statistical uncertainty of the data, and the outer band to statistical and systematic uncertainties of the data, added in quadrature.
Figure 10(right) of the article. Differential fiducial cross-section of the invariant mass of the leading and sub-leading $b$-jets in events with $Z \left( \rightarrow \ell\ell \right) + 2 b$-jets. The thin inner band corresponds to the statistical uncertainty of the data, and the outer band to statistical and systematic uncertainties of the data, added in quadrature.
Figure 11(left) of the article. Differential fiducial cross-section of the Z boson $p_T$ in events with $Z \left( \rightarrow \ell\ell \right) + 1 c$-jet. The thin inner band corresponds to the statistical uncertainty of the data, and the outer band to statistical and systematic uncertainties of the data, added in quadrature.
Figure 11(right) of the article. Differential fiducial cross-section of the leading $c$-jet $p_T$ in events with $Z \left( \rightarrow \ell\ell ight) + 1 c$-jet. The thin inner band corresponds to the statistical uncertainty of the data, and the outer band to statistical and systematic uncertainties of the data, added in quadrature.
Figure 12 of the article. Differential fiducial cross-section of the leading $c$-jet $x_F$ in events with $Z \left( \rightarrow \ell\ell \right) + 1 c$-jet. The thin inner band corresponds to the statistical uncertainty of the data, and the outer band to statistical and systematic uncertainties of the data, added in quadrature.
Inclusive and differential cross-sections are measured at particle level for the associated production of a top quark pair and a photon ($t\bar{t}\gamma$). The analysis is performed using an integrated luminosity of 140 fb$^{-1}$ of proton-proton collisions at a centre-of-mass energy of 13 TeV collected by the ATLAS detector. The measurements are performed in the single-lepton and dilepton top quark pair decay channels focusing on $t\bar{t}\gamma$ topologies where the photon is radiated from an initial-state parton or one of the top quarks. The absolute and normalised differential cross-sections are measured for several variables characterising the photon, lepton and jet kinematics as well as the angular separation between those objects. The observables are found to be in good agreement with the Monte Carlo predictions. The photon transverse momentum differential distribution is used to set limits on effective field theory parameters related to the electroweak dipole moments of the top quark. The combined limits using the photon and the $Z$ boson transverse momentum measured in $t\bar{t}$ production in associations with a $Z$ boson are also set.
Absolute $t\bar{t}\gamma$ production differential cross-sections measured in fiducial phase space in the single-lepton channel as a function of the $\Delta R(\gamma,b)_{min}$. The last bin of the distribution includes the overflow events.
Normalised $t\bar{t}\gamma$ production differential cross-sections measured in fiducial phase space in the single-lepton channel as a function of the $\Delta R(\gamma,b)_{min}$. The last bin of the distribution includes the overflow events.
Absolute $t\bar{t}\gamma$ production differential cross-sections measured in fiducial phase space in the single-lepton channel as a function of the $\Delta R(\gamma,l)$. The last bin of the distribution includes the overflow events.
Normalised $t\bar{t}\gamma$ production differential cross-sections measured in fiducial phase space in the single-lepton channel as a function of the $\Delta R(\gamma,l)$. The last bin of the distribution includes the overflow events.
Absolute $t\bar{t}\gamma$ production differential cross-sections measured in fiducial phase space in the single-lepton channel as a function of the $\Delta R(l,j)_{min}$. The last bin of the distribution includes the overflow events.
Normalised $t\bar{t}\gamma$ production differential cross-sections measured in fiducial phase space in the single-lepton channel as a function of the $\Delta R(l,j)_{min}$. The last bin of the distribution includes the overflow events.
Absolute $t\bar{t}\gamma$ production differential cross-sections measured in fiducial phase space in the dilepton channel as a function of the $\Delta R(\gamma,b)_{min}$. The last bin of the distribution includes the overflow events.
Normalised $t\bar{t}\gamma$ production differential cross-sections measured in fiducial phase space in the dilepton channel as a function of the $\Delta R(\gamma,b)_{min}$. The last bin of the distribution includes the overflow events.
Absolute $t\bar{t}\gamma$ production differential cross-sections measured in fiducial phase space in the dilepton channel as a function of the $\Delta R(\gamma,l)_{min}$. The last bin of the distribution includes the overflow events.
Normalised $t\bar{t}\gamma$ production differential cross-sections measured in fiducial phase space in the dilepton channel as a function of the $\Delta R(\gamma,l)_{min}$. The last bin of the distribution includes the overflow events.
Absolute $t\bar{t}\gamma$ production differential cross-sections measured in fiducial phase space in the dilepton channel as a function of the $\Delta R(l,j)_{min}$. The last bin of the distribution includes the overflow events.
Normalised $t\bar{t}\gamma$ production differential cross-sections measured in fiducial phase space in the dilepton channel as a function of the $\Delta R(l,j)_{min}$. The last bin of the distribution includes the overflow events.
Absolute $t\bar{t}\gamma$ production differential cross-sections measured in the combined fiducial phase space of the single-lepton and dilepton channels as a function of the photon $p_T$. The last bin of the distributions includes the overflow events.
Normalised $t\bar{t}\gamma$ production differential cross-sections measured in the combined fiducial phase space of the single-lepton and dilepton channels as a function of the photon $p_T$. The last bin of the distributions includes the overflow events.
Absolute $t\bar{t}\gamma$ production differential cross-sections measured in the combined fiducial phase space of the single-lepton and dilepton channels as a function of the photon $|\eta|$.
Normalised $t\bar{t}\gamma$ production differential cross-sections measured in the combined fiducial phase space of the single-lepton and dilepton channels as a function of the photon $|\eta|$.
Absolute differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the single-lepton channel as a function of the $p_T(\gamma)$. The last bin of the distribution includes the overflow events.
Normalised differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the single-lepton channel as a function of the $p_T(\gamma)$. The last bin of the distribution includes the overflow events.
Absolute differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the single-lepton channel as a function of the $|\eta(\gamma)|$.
Normalised differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the single-lepton channel as a function of the $|\eta(\gamma)|$.
Absolute differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the single-lepton channel as a function of the $p_T(j_1)$. The last bin of the distribution includes the overflow events.
Normalised differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the single-lepton channel as a function of the $p_T(j_1)$. The last bin of the distribution includes the overflow events.
Absolute differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the single-lepton channel as a function of the $\Delta R(\gamma,b)_{min}$. The last bin of the distribution includes the overflow events.
Normalised differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the single-lepton channel as a function of the $\Delta R(\gamma,b)_{min}$. The last bin of the distribution includes the overflow events.
Absolute differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the single-lepton channel as a function of the $\Delta R(\gamma,l)$. The last bin of the distribution includes the overflow events.
Normalised differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the single-lepton channel as a function of the $\Delta R(\gamma,l)$. The last bin of the distribution includes the overflow events.
Absolute differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the single-lepton channel as a function of the $\Delta R(l,j)_{min}$. The last bin of the distribution includes the overflow events.
Normalised differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the single-lepton channel as a function of the $\Delta R(l,j)_{min}$. The last bin of the distribution includes the overflow events.
Absolute differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the dilepton channel as a function of the $|\Delta \eta(l,l)|$ . The last bin of the distribution includes the overflow events.
Normalised differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the dilepton channel as a function of the $|\Delta \eta(l,l)|$ . The last bin of the distribution includes the overflow events.
Absolute differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the dilepton channel as a function of the $\Delta \phi(l,l)$ . The last bin of the distribution includes the overflow events.
Normalised differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the dilepton channel as a function of the $\Delta \phi(l,l)$ . The last bin of the distribution includes the overflow events.
Absolute differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the dilepton channel as a function of the $p_T(l,l)$. The last bin of the distribution includes the overflow events.
Normalised differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the dilepton channel as a function of the $p_T(l,l)$. The last bin of the distribution includes the overflow events.
Absolute differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the dilepton channel as a function of the $\Delta R(\gamma,l_1)$. The last bin of the distribution includes the overflow events.
Normalised differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the dilepton channel as a function of the $\Delta R(\gamma,l_1)$. The last bin of the distribution includes the overflow events.
Absolute differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the dilepton channel as a function of the $\Delta R(\gamma,l_2)$. The last bin of the distribution includes the overflow events.
Normalised differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the dilepton channel as a function of the $\Delta R(\gamma,l_2)$. The last bin of the distribution includes the overflow events.
Absolute $t\bar{t}\gamma$ production differential cross-sections measured in fiducial phase space in the single-lepton channel as a function of the $p_T(\gamma)$. The last bin of the distribution includes the overflow events.
Normalised $t\bar{t}\gamma$ production differential cross-sections measured in fiducial phase space in the single-lepton channel as a function of the $p_T(\gamma)$. The last bin of the distribution includes the overflow events.
Absolute $t\bar{t}\gamma$ production differential cross-sections measured in fiducial phase space in the single-lepton channel as a function of the $|\eta(\gamma)|$.
Normalised $t\bar{t}\gamma$ production differential cross-sections measured in fiducial phase space in the single-lepton channel as a function of the $|\eta(\gamma)|$.
Absolute $t\bar{t}\gamma$ production differential cross-sections measured in fiducial phase space in the single-lepton channel as a function of the $p_T(j_1)$. The last bin of the distribution includes the overflow events.
Normalised $t\bar{t}\gamma$ production differential cross-sections measured in fiducial phase space in the single-lepton channel as a function of the $p_T(j_1)$. The last bin of the distribution includes the overflow events.
Absolute $t\bar{t}\gamma$ production differential cross-sections measured in fiducial phase space in the dilepton channel as a function of the $p_T(\gamma)$. The last bin of the distribution includes the overflow events.
Normalised $t\bar{t}\gamma$ production differential cross-sections measured in fiducial phase space in the dilepton channel as a function of the $p_T(\gamma)$. The last bin of the distribution includes the overflow events.
Absolute $t\bar{t}\gamma$ production differential cross-sections measured in fiducial phase space in the dilepton channel as a function of the $|\eta(\gamma)|$.
Normalised $t\bar{t}\gamma$ production differential cross-sections measured in fiducial phase space in the dilepton channel as a function of the $|\eta(\gamma)|$.
Absolute $t\bar{t}\gamma$ production differential cross-sections measured in fiducial phase space in the dilepton channel as a function of the $p_T(j_1)$. The last bin of the distribution includes the overflow events.
Normalised $t\bar{t}\gamma$ production differential cross-sections measured in fiducial phase space in the dilepton channel as a function of the $p_T(j_1)$. The last bin of the distribution includes the overflow events.
Absolute differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the dilepton channel as a function of the $p_T(\gamma)$. The last bin of the distribution includes the overflow events.
Normalised differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the dilepton channel as a function of the $p_T(\gamma)$. The last bin of the distribution includes the overflow events.
Absolute differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the dilepton channel as a function of the $|\eta(\gamma)|$.
Normalised differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the dilepton channel as a function of the $|\eta(\gamma)|$.
Absolute differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the dilepton channel as a function of the $p_T(j_1)$. The last bin of the distribution includes the overflow events.
Normalised differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the single-lepton channel as a function of the $p_T(j_1)$. The last bin of the distribution includes the overflow events.
Absolute differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the dilepton channel as a function of the $\Delta R(\gamma,b)_{min}$. The last bin of the distribution includes the overflow events.
Normalised differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the dilepton channel as a function of the $\Delta R(\gamma,b)_{min}$. The last bin of the distribution includes the overflow events.
Absolute differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the dilepton channel as a function of the $\Delta R(\gamma,l)_{min}$. The last bin of the distribution includes the overflow events.
Normalised differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the dilepton channel as a function of the $\Delta R(\gamma,l)_{min}$. The last bin of the distribution includes the overflow events.
Absolute differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the dilepton channel as a function of the $\Delta R(l,j)_{min}$. The last bin of the distribution includes the overflow events.
Normalised differential cross-section of the total $t\bar{t}\gamma$ production and decay measured in fiducial phase space in the dilepton channel as a function of the $\Delta R(l,j)_{min}$. The last bin of the distribution includes the overflow events.
The mass of the top quark is measured using top-antitop-quark pair events with high transverse momentum top quarks. The dataset, collected with the ATLAS detector in proton--proton collisions at $\sqrt{s}=13$ TeV delivered by the Large Hadron Collider, corresponds to an integrated luminosity of 140 fb$^{-1}$. The analysis targets events in the lepton-plus-jets decay channel, with an electron or muon from a semi-leptonically decaying top quark and a hadronically decaying top quark that is sufficiently energetic to be reconstructed as a single large-radius jet. The mean of the invariant mass of the reconstructed large-radius jet provides the sensitivity to the top quark mass and is simultaneously fitted with two additional observables to reduce the impact of the systematic uncertainties. The top quark mass is measured to be $m_t = 172.95 \pm 0.53$ GeV, which is the most precise ATLAS measurement from a single channel.
Measurements of both the inclusive and differential production cross sections of a top-quark-top-antiquark pair in association with a $Z$ boson ($t\bar{t}Z$) are presented. Final states with two, three or four isolated leptons (electrons or muons) are targeted. The measurements use the data recorded by the ATLAS detector in $pp$ collisions at $\sqrt{s}=13$ TeV at the Large Hadron Collider during the years 2015-2018, corresponding to an integrated luminosity of $140$ fb$^{-1}$. The inclusive cross section is measured to be $\sigma_{t\bar{t}Z}= 0.86 \pm 0.04~\mathrm{(stat.)} \pm 0.04~\mathrm{(syst.)}~$pb and found to be in agreement with the most advanced Standard Model predictions. The differential measurements are presented as a function of a number of observables that probe the kinematics of the $t\bar{t}Z$ system. Both the absolute and normalised differential cross-section measurements are performed at particle level and parton level for specific fiducial volumes, and are compared with NLO+NNLL theoretical predictions. The results are interpreted in the framework of Standard Model effective field theory and used to set limits on a large number of dimension-6 operators involving the top quark. The first measurement of spin correlations in $t\bar{t}Z$ events is presented: the results are in agreement with the Standard Model expectations, and the null hypothesis of no spin correlations is disfavoured with a significance of $1.8$ standard deviations.
Pre-fit distribution of the number of $b$-jets in 2L-$e\mu$-6j2b, this distribution is not used in the fit.
Pre-fit distribution of the DNN output 2L-$e\mu$-6j1b, this distribution is not used in the fit.
Pre-fit distribution of the DNN output 2L-$e\mu$-5j2b, this distribution is not used in the fit.
Pre-fit distribution of the DNN output 2L-$e\mu$-6j2b, this distribution is not used in the fit.
Pre-fit distribution of jet multiplicity in CR-$t\bar{t}$-e region.
Pre-fit distribution of loose lepton transverse momentum in CR-$t\bar{t}$-$\mu$ region.
Pre-fit distribution of the transverse mass of the trailing lepton and the missing transverse momentum in CR-Z-e region.
Post-fit distribution of jet multiplicity in CR-$t\bar{t}$-e region
Post-fit distribution of loose lepton transverse momentum in CR-$t\bar{t}$-$\mu$ region
Post-fit distribution of the transverse mass of the trailing lepton and the missing transverse momentum in CR-Z-e region
Post-fit distribution of NN output in SR-2L-5j2b region.
Post-fit distribution of NN output in SR-2L-6j1b region.
Post-fit distribution of NN output in SR-2L-6j2b region.
Post-fit distribution of DNN-$t\bar{t}Z$ output in 3L-SR-ttZ region.
Post-fit distribution of DNN-$t\bar{t}Z$ outputt in 3L-SR-tZq region.
Post fit events yields in 3L-SR-WZ region.
Post-fit distribution of NN output in 4L-SR-SF region.
Post-fit distribution of NN output in 4L-SR-DF region.
Post-fit distribution of b-tagger output for leading b-jet in 4L-CR-ZZ region.
Measured values of the background normalizations obtained from the combined fit. The uncertainties include statistical and systematic sources.
Measured $\sigma_{t\bar{t}\text{Z}}$ cross sections obtained from the fits in the different lepton channels. The uncertainties include statistical and systematic sources.
Grouped impact of systematic uncertainties in the combined inclusive fit to data.
Unfolded absolute cross section as a function of $p^{Z}_{T}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 8 top-left).
Unfolded absolute cross section as a function of $p^{Z}_{T}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 8 top-right).
Unfolded normalized cross section as a function of $p^{Z}_{T}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 8 bottom-left).
Unfolded normalized cross section as a function of $p^{Z}_{T}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 8 bottom-right).
Unfolded absolute cross section as a function of $|y^{Z}$| in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 17 top-left and Figure 11 top-left).
Unfolded absolute cross section as a function of $|y^{Z}$| in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 17 top-right).
Unfolded normalized cross section as a function of $|y^{Z}$| in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 17 bottom-left).
Unfolded normalized cross section as a function of $|y^{Z}$| in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 17 bottom-right).
Unfolded absolute cross section as a function of cos $\theta_{Z}^{*}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 18 top-left and Figure 11 top-right).
Unfolded absolute cross section as a function of cos $\theta_{Z}^{*}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 18 top-right).
Unfolded normalized cross section as a function of cos $\theta_{Z}^{*}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 18 bottom-left).
Unfolded normalized cross section as a function of cos $\theta_{Z}^{*}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 18 bottom-right).
Unfolded absolute cross section as a function of $p_{T}^{\mathrm{top}}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 19 top-left and Figure 11 bottom-left).
Unfolded absolute cross section as a function of $p_{T}^{\mathrm{top}}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 19, top-right).
Unfolded normalized cross section as a function of $p_{T}^{\mathrm{top}}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 19, bottom-left).
Unfolded normalized cross section as a function of $p_{T}^{\mathrm{top}}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 19, bottom-right).
Unfolded absolute cross section as a function of $p_{T}^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 20 top-left and Figure 11 bottom-right).
Unfolded absolute cross section as a function of $p_{T}^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 20, top-right).
Unfolded normalized cross section as a function of $p_{T}^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 20, bottom-left)
Unfolded normalized cross section as a function of $p_{T}^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 20, bottom-right)
Unfolded absolute cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 21 top-left and Figure 12 top-left).
Unfolded absolute cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 21, top-right).
Unfolded normalized cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 21, bottom-left).
Unfolded normalized cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 21, top-right).
Unfolded absolute cross section as a function of $m^{t\bar{t}Z}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 22 top-left and Figure 12 bottom-left).
Unfolded absolute cross section as a function of $m^{t\bar{t}Z}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 22, top-right).
Unfolded normalized cross section as a function of $m^{t\bar{t}Z}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 22, bottom-left).
Unfolded normalized cross section as a function of $m^{t\bar{t}Z}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 22, bottom-right).
Unfolded absolute cross section as a function of $m^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 23 top-left and Figure 12 bottom-right).
Unfolded absolute cross section as a function of $m^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 23, top-right).
Unfolded normalized cross section as a function of $m^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 23, bottom-left).
Unfolded normalized cross section as a function of $m^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 23, bottom-right).
Unfolded absolute cross section as a function of $|y^{t\bar{t}Z}|$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 24 top-left and Figure 12 top-right).
Unfolded absolute cross section as a function of $|y^{t\bar{t}Z}|$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 24, top-right).
Unfolded normalized cross section as a function of $|y^{t\bar{t}Z}|$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 24, bottom-left).
Unfolded normalized cross section as a function of $|y^{t\bar{t}Z}|$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 24, bottom-right).
Unfolded absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at particle-level (Figure 25 top-left and Figure 9 top-left).
Unfolded absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at parton-level (Figure 25 top-right).
Unfolded normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at particle-level (Figure 25 bottom-left).
Unfolded normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at parton-level (Figure 25 bottom-right).
Unfolded absolute cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ in the trilepton channel at particle-level (Figure 26 top-left and Figure 10 bottom-left).
Unfolded absolute cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ in the trilepton channel at parton-level (Figure 26 top-right).
Unfolded normalized cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ in the trilepton channel at particle-level (Figure 26 bottom-left).
Unfolded normalized cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ in the trilepton channel at parton-level (Figure 26 bottom-right).
Unfolded absolute cross section as a function of $|\Delta y(Z, t_{lep})|$ in the trilepton channel at particle-level (Figure 27 top-left and Figure 10 bottom-right).
Unfolded absolute cross section as a function of $|\Delta y(Z, t_{lep})|$ in the trilepton channel at parton-level (Figure 27 top-right).
Unfolded normalized cross section as a function of $|\Delta y(Z, t_{lep})|$ in the trilepton channel at particle-level (Figure 27 bottom-left).
Unfolded normalized cross section as a function of $|\Delta y(Z, t_{lep})|$ in the trilepton channel at parton-level (Figure 27 bottom-right).
Unfolded absolute cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ in the trilepton channel at particle-level (Figure 28 top-left and Figure 10 top-left).
Unfolded absolute cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ in the trilepton channel at parton-level (Figure 28 top-right).
Unfolded normalized cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ in the trilepton channel at particle-level (Figure 28 bottom-left).
Unfolded normalized cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ in the trilepton channel at parton-level (Figure 28 bottom-right).
Unfolded absolute cross section as a function of $N_{\text{jets}}$ in the trilepton channel at particle-level (Figure 29 left and Figure 9 bottom-left).
Unfolded normalized cross section as a function of $N_{\text{jets}}$ in the trilepton channel at particle-level (Figure 29 right).
Unfolded absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ in the tetralepton channel at particle-level (Figure 30 top-left and Figure 9 top-right).
Unfolded absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ in the tetralepton channel at parton-level (Figure 30 top-right).
Unfolded normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ in the tetralepton channel at particle-level (Figure 30 bottom-left).
Unfolded normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ in the tetralepton channel at parton-level (Figure 30 bottom-right).
Unfolded absolute cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the tetralepton channel at particle-level (Figure 31 top-left and Figure 10 top-right).
Unfolded absolute cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the tetralepton channel at parton-level (Figure 31 top-right).
Unfolded normalized cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the tetralepton channel at particle-level (Figure 31 bottom-left).
Unfolded normalized cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the tetralepton channel at parton-level (Figure 31 bottom-right).
Unfolded absolute cross section as a function of $N_{\text{jets}}$ in the tetralepton channel at particle-level (Figure 32 left and Figure 9 bottom-right).
Unfolded normalized cross section as a function of $N_{\text{jets}}$ in the tetralepton channel at particle-level (Figure 32 right).
Bootstrap replicas (0-499) for data in all regions used in inclusive cross section measurement. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data in all regions used in inclusive cross section measurement. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $|\Delta\Phi(t\bar{t}, Z)|/\pi$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $|\Delta\Phi(t\bar{t}, Z)|/\pi$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $|\Delta\Phi(Z, t_{lep})|/\pi$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $|\Delta\Phi(Z, t_{lep})|/\pi$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $m^{t\bar{t}}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $m^{t\bar{t}}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $N_{\text{jets}}$ in $3\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $N_{\text{jets}}$ in $3\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $|y^{t\bar{t}Z}|$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $|y^{t\bar{t}Z}|$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $H_{\text{T}}^{\text{l}}$ in $3\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $H_{\text{T}}^{\text{l}}$ in $3\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $y^{Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $y^{Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $p_{T}^{\mathrm{top}}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $p_{T}^{\mathrm{top}}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable cos $\theta^{*}_{Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable cos $\theta^{*}_{Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $p_{\text{T}}^{\ell, non-Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $p_{\text{T}}^{\ell, non-Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $H_{\text{T}}^{\text{l}}$ in $4\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $H_{\text{T}}^{\text{l}}$ in $4\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $m^{t\bar{t}Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $m^{t\bar{t}Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $N_{\text{jets}}$ in $4\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $N_{\text{jets}}$ in $4\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $|\Delta y(Z, t_{lep})|$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $|\Delta y(Z, t_{lep})|$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $p^{Z}_{T}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $p^{Z}_{T}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (0-499) for data, variable $p_{T}^{t\bar{t}}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Bootstrap replicas (500-999) for data, variable $p_{T}^{t\bar{t}}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).
Parton-level acceptance and selection efficiency histograms for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable.
Parton-level acceptance and selection efficiency histograms for $|\Delta y(Z, t_{lep})|$ variable.
Parton-level acceptance and selection efficiency histograms for $H_{\text{T}}^{\text{ l}}$ variable.
Parton-level acceptance and selection efficiency histograms for $p_{\text{T}}^{\ell, non-Z}$ variable.
Parton-level acceptance and selection efficiency histograms for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable.
Parton-level acceptance and selection efficiency histograms for $H_{\text{T}}^{\text{ l}}$ variable.
Parton-level acceptance and selection efficiency histograms for cos $\theta_{Z}^{*}$ variable.
Parton-level acceptance and selection efficiency histograms for $p^{Z}_{T}$ variable.
Parton-level acceptance and selection efficiency histograms for $|y^{Z}$| variable.
Parton-level acceptance and selection efficiency histograms for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable.
Parton-level acceptance and selection efficiency histograms for $m^{t\bar{t}}$ variable.
Parton-level acceptance and selection efficiency histograms for $m^{t\bar{t}Z}$ variable.
Parton-level acceptance and selection efficiency histograms for $p_{T}^{\mathrm{top}}$ variable.
Parton-level acceptance and selection efficiency histograms for $p_{T}^{t\bar{t}}$ variable.
Parton-level acceptance and selection efficiency histograms for $|y^{t\bar{t}Z}|$ variable.
Particle-level acceptance and selection efficiency histograms for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable.
Particle-level acceptance and selection efficiency histograms for $|\Delta y(Z, t_{lep})|$ variable.
Particle-level acceptance and selection efficiency histograms for $H_{\text{T}}^{\text{ l}}$ variable.
Particle-level acceptance and selection efficiency histograms for $N_{\text{jets}}$ variable.
Particle-level acceptance and selection efficiency histograms for $p_{\text{T}}^{\ell, non-Z}$ variable.
Particle-level acceptance and selection efficiency histograms for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable.
Particle-level acceptance and selection efficiency histograms for $H_{\text{T}}^{\text{ l}}$ variable.
Particle-level acceptance and selection efficiency histograms for $N_{\text{jets}}$ variable.
Particle-level acceptance and selection efficiency histograms for cos $\theta_{Z}^{*}$ variable.
Particle-level acceptance and selection efficiency histograms for $p^{Z}_{T}$ variable.
Particle-level acceptance and selection efficiency histograms for $|y^{Z}$| variable.
Particle-level acceptance and selection efficiency histograms for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable.
Particle-level acceptance and selection efficiency histograms for $m^{t\bar{t}}$ variable.
Particle-level acceptance and selection efficiency histograms for $m^{t\bar{t}Z}$ variable.
Particle-level acceptance and selection efficiency histograms for $p_{T}^{\mathrm{top}}$ variable.
Particle-level acceptance and selection efficiency histograms for $p_{T}^{t\bar{t}}$ variable.
Particle-level acceptance and selection efficiency histograms for $|y^{t\bar{t}Z}|$ variable.
Migration matrix for cos $\theta_{Z}^{*}$ variable at particle-level in region SR-3L-ttZ.
Migration matrix for cos $\theta_{Z}^{*}$ variable at particle-level in region SR-3L-tZq.
Migration matrix for cos $\theta_{Z}^{*}$ variable at particle-level in region SR-3L-WZ.
Migration matrix for cos $\theta_{Z}^{*}$ variable at particle-level in region SR-4L-DF.
Migration matrix for cos $\theta_{Z}^{*}$ variable at particle-level in region SR-4L-SF.
Migration matrix for cos $\theta_{Z}^{*}$ variable at particle-level in region CR-4L-ZZ.
Migration matrix for cos $\theta_{Z}^{*}$ variable at parton-level in region SR-3L-ttZ.
Migration matrix for cos $\theta_{Z}^{*}$ variable at parton-level in region SR-3L-tZq.
Migration matrix for cos $\theta_{Z}^{*}$ variable at parton-level in region SR-3L-WZ.
Migration matrix for cos $\theta_{Z}^{*}$ variable at parton-level in region SR-4L-DF.
Migration matrix for cos $\theta_{Z}^{*}$ variable at parton-level in region SR-4L-SF.
Migration matrix for cos $\theta_{Z}^{*}$ variable at parton-level in region CR-4L-ZZ.
Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at particle-level in region SR-3L-ttZ.
Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at particle-level in region SR-3L-tZq.
Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at particle-level in region SR-3L-WZ.
Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at particle-level in region SR-4L-DF.
Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at particle-level in region SR-4L-SF.
Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at particle-level in region CR-4L-ZZ.
Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at parton-level in region SR-3L-ttZ.
Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at parton-level in region SR-3L-tZq.
Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at parton-level in region SR-3L-WZ.
Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at parton-level in region SR-4L-DF.
Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at parton-level in region SR-4L-SF.
Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at parton-level in region CR-4L-ZZ.
Migration matrix for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable at particle-level in region SR-4L-DF.
Migration matrix for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable at particle-level in region SR-4L-SF.
Migration matrix for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable at particle-level in region CR-4L-ZZ.
Migration matrix for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable at parton-level in region SR-4L-DF.
Migration matrix for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable at parton-level in region SR-4L-SF.
Migration matrix for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable at parton-level in region CR-4L-ZZ.
Migration matrix for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable at particle-level in region SR-3L-ttZ.
Migration matrix for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable at particle-level in region SR-3L-tZq.
Migration matrix for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable at particle-level in region SR-3L-WZ.
Migration matrix for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable at parton-level in region SR-3L-ttZ.
Migration matrix for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable at parton-level in region SR-3L-tZq.
Migration matrix for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable at parton-level in region SR-3L-WZ.
Migration matrix for $|\Delta y(Z, t_{lep})|$ variable at particle-level in region SR-3L-ttZ.
Migration matrix for $|\Delta y(Z, t_{lep})|$ variable at particle-level in region SR-3L-tZq.
Migration matrix for $|\Delta y(Z, t_{lep})|$ variable at particle-level in region SR-3L-WZ.
Migration matrix for $|\Delta y(Z, t_{lep})|$ variable at parton-level in region SR-3L-ttZ.
Migration matrix for $|\Delta y(Z, t_{lep})|$ variable at parton-level in region SR-3L-tZq.
Migration matrix for $|\Delta y(Z, t_{lep})|$ variable at parton-level in region SR-3L-WZ.
Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at particle-level in region SR-4L-DF.
Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at particle-level in region SR-4L-SF.
Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at particle-level in region CR-4L-ZZ.
Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at parton-level in region SR-4L-DF.
Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at parton-level in region SR-4L-SF.
Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at parton-level in region CR-4L-ZZ.
Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at particle-level in region SR-3L-ttZ.
Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at particle-level in region SR-3L-tZq.
Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at particle-level in region SR-3L-WZ.
Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at parton-level in region SR-3L-ttZ.
Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at parton-level in region SR-3L-tZq.
Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at parton-level in region SR-3L-WZ.
Migration matrix for $m^{t\bar{t}Z}$ variable at particle-level in region SR-3L-ttZ.
Migration matrix for $m^{t\bar{t}Z}$ variable at particle-level in region SR-3L-tZq.
Migration matrix for $m^{t\bar{t}Z}$ variable at particle-level in region SR-3L-WZ.
Migration matrix for $m^{t\bar{t}Z}$ variable at particle-level in region SR-4L-DF.
Migration matrix for $m^{t\bar{t}Z}$ variable at particle-level in region SR-4L-SF.
Migration matrix for $m^{t\bar{t}Z}$ variable at particle-level in region CR-4L-ZZ.
Migration matrix for $m^{t\bar{t}Z}$ variable at parton-level in region SR-3L-ttZ.
Migration matrix for $m^{t\bar{t}Z}$ variable at parton-level in region SR-3L-tZq.
Migration matrix for $m^{t\bar{t}Z}$ variable at parton-level in region SR-3L-WZ.
Migration matrix for $m^{t\bar{t}Z}$ variable at parton-level in region SR-4L-DF.
Migration matrix for $m^{t\bar{t}Z}$ variable at parton-level in region SR-4L-SF.
Migration matrix for $m^{t\bar{t}Z}$ variable at parton-level in region CR-4L-ZZ.
Migration matrix for $m^{t\bar{t}}$ variable at particle-level in region SR-3L-ttZ.
Migration matrix for $m^{t\bar{t}}$ variable at particle-level in region SR-3L-tZq.
Migration matrix for $m^{t\bar{t}}$ variable at particle-level in region SR-3L-WZ.
Migration matrix for $m^{t\bar{t}}$ variable at particle-level in region SR-4L-DF.
Migration matrix for $m^{t\bar{t}}$ variable at particle-level in region SR-4L-SF.
Migration matrix for $m^{t\bar{t}}$ variable at particle-level in region CR-4L-ZZ.
Migration matrix for $m^{t\bar{t}}$ variable at parton-level in region SR-3L-ttZ.
Migration matrix for $m^{t\bar{t}}$ variable at parton-level in region SR-3L-tZq.
Migration matrix for $m^{t\bar{t}}$ variable at parton-level in region SR-3L-WZ.
Migration matrix for $m^{t\bar{t}}$ variable at parton-level in region SR-4L-DF.
Migration matrix for $m^{t\bar{t}}$ variable at parton-level in region SR-4L-SF.
Migration matrix for $m^{t\bar{t}}$ variable at parton-level in region CR-4L-ZZ.
Migration matrix for $N_{\text{jets}}$ variable at particle-level in region SR-4L-DF.
Migration matrix for $N_{\text{jets}}$ variable at particle-level in region SR-4L-SF.
Migration matrix for $N_{\text{jets}}$ variable at particle-level in region CR-4L-ZZ.
Migration matrix for $N_{\text{jets}}$ variable at particle-level in region SR-3L-ttZ.
Migration matrix for $N_{\text{jets}}$ variable at particle-level in region SR-3L-tZq.
Migration matrix for $N_{\text{jets}}$ variable at particle-level in region SR-3L-WZ.
Migration matrix for $p^{Z}_{T}$ variable at particle-level in region SR-3L-ttZ.
Migration matrix for $p^{Z}_{T}$ variable at particle-level in region SR-3L-tZq.
Migration matrix for $p^{Z}_{T}$ variable at particle-level in region SR-3L-WZ.
Migration matrix for $p^{Z}_{T}$ variable at particle-level in region SR-4L-DF.
Migration matrix for $p^{Z}_{T}$ variable at particle-level in region SR-4L-SF.
Migration matrix for $p^{Z}_{T}$ variable at particle-level in region CR-4L-ZZ.
Migration matrix for $p^{Z}_{T}$ variable at parton-level in region SR-3L-ttZ.
Migration matrix for $p^{Z}_{T}$ variable at parton-level in region SR-3L-tZq.
Migration matrix for $p^{Z}_{T}$ variable at parton-level in region SR-3L-WZ.
Migration matrix for $p^{Z}_{T}$ variable at parton-level in region SR-4L-DF.
Migration matrix for $p^{Z}_{T}$ variable at parton-level in region SR-4L-SF.
Migration matrix for $p^{Z}_{T}$ variable at parton-level in region CR-4L-ZZ.
Migration matrix for $p_{T}^{\mathrm{top}}$ variable at particle-level in region SR-3L-ttZ.
Migration matrix for $p_{T}^{\mathrm{top}}$ variable at particle-level in region SR-3L-tZq.
Migration matrix for $p_{T}^{\mathrm{top}}$ variable at particle-level in region SR-3L-WZ.
Migration matrix for $p_{T}^{\mathrm{top}}$ variable at particle-level in region SR-4L-DF.
Migration matrix for $p_{T}^{\mathrm{top}}$ variable at particle-level in region SR-4L-SF.
Migration matrix for $p_{T}^{\mathrm{top}}$ variable at particle-level in region CR-4L-ZZ.
Migration matrix for $p_{T}^{\mathrm{top}}$ variable at parton-level in region SR-3L-ttZ.
Migration matrix for $p_{T}^{\mathrm{top}}$ variable at parton-level in region SR-3L-tZq.
Migration matrix for $p_{T}^{\mathrm{top}}$ variable at parton-level in region SR-3L-WZ.
Migration matrix for $p_{T}^{\mathrm{top}}$ variable at parton-level in region SR-4L-DF.
Migration matrix for $p_{T}^{\mathrm{top}}$ variable at parton-level in region SR-4L-SF.
Migration matrix for $p_{T}^{\mathrm{top}}$ variable at parton-level in region CR-4L-ZZ.
Migration matrix for $p_{T}^{t\bar{t}}$ variable at particle-level in region SR-3L-ttZ.
Migration matrix for $p_{T}^{t\bar{t}}$ variable at particle-level in region SR-3L-tZq.
Migration matrix for $p_{T}^{t\bar{t}}$ variable at particle-level in region SR-3L-WZ.
Migration matrix for $p_{T}^{t\bar{t}}$ variable at particle-level in region SR-4L-DF.
Migration matrix for $p_{T}^{t\bar{t}}$ variable at particle-level in region SR-4L-SF.
Migration matrix for $p_{T}^{t\bar{t}}$ variable at particle-level in region CR-4L-ZZ.
Migration matrix for $p_{T}^{t\bar{t}}$ variable at parton-level in region SR-3L-ttZ.
Migration matrix for $p_{T}^{t\bar{t}}$ variable at parton-level in region SR-3L-tZq.
Migration matrix for $p_{T}^{t\bar{t}}$ variable at parton-level in region SR-3L-WZ.
Migration matrix for $p_{T}^{t\bar{t}}$ variable at parton-level in region SR-4L-DF.
Migration matrix for $p_{T}^{t\bar{t}}$ variable at parton-level in region SR-4L-SF.
Migration matrix for $p_{T}^{t\bar{t}}$ variable at parton-level in region CR-4L-ZZ.
Migration matrix for $p_{\text{T}}^{\ell, non-Z}$ variable at particle-level in region SR-3L-ttZ.
Migration matrix for $p_{\text{T}}^{\ell, non-Z}$ variable at particle-level in region SR-3L-tZq.
Migration matrix for $p_{\text{T}}^{\ell, non-Z}$ variable at particle-level in region SR-3L-WZ.
Migration matrix for $p_{\text{T}}^{\ell, non-Z}$ variable at parton-level in region SR-3L-ttZ.
Migration matrix for $p_{\text{T}}^{\ell, non-Z}$ variable at parton-level in region SR-3L-tZq.
Migration matrix for $p_{\text{T}}^{\ell, non-Z}$ variable at parton-level in region SR-3L-WZ.
Migration matrix for $|y^{Z}$| variable at particle-level in region SR-3L-ttZ.
Migration matrix for $|y^{Z}$| variable at particle-level in region SR-3L-tZq.
Migration matrix for $|y^{Z}$| variable at particle-level in region SR-3L-WZ.
Migration matrix for $|y^{Z}$| variable at particle-level in region SR-4L-DF.
Migration matrix for $|y^{Z}$| variable at particle-level in region SR-4L-SF.
Migration matrix for $|y^{Z}$| variable at particle-level in region CR-4L-ZZ.
Migration matrix for $|y^{Z}$| variable at parton-level in region SR-3L-ttZ.
Migration matrix for $|y^{Z}$| variable at parton-level in region SR-3L-tZq.
Migration matrix for $|y^{Z}$| variable at parton-level in region SR-3L-WZ.
Migration matrix for $|y^{Z}$| variable at parton-level in region SR-4L-DF.
Migration matrix for $|y^{Z}$| variable at parton-level in region SR-4L-SF.
Migration matrix for $|y^{Z}$| variable at parton-level in region CR-4L-ZZ.
Migration matrix for $|y^{t\bar{t}Z}|$ variable at particle-level in region SR-3L-ttZ.
Migration matrix for $|y^{t\bar{t}Z}|$ variable at particle-level in region SR-3L-tZq.
Migration matrix for $|y^{t\bar{t}Z}|$ variable at particle-level in region SR-3L-WZ.
Migration matrix for $|y^{t\bar{t}Z}|$ variable at particle-level in region SR-4L-DF.
Migration matrix for $|y^{t\bar{t}Z}|$ variable at particle-level in region SR-4L-SF.
Migration matrix for $|y^{t\bar{t}Z}|$ variable at particle-level in region CR-4L-ZZ.
Migration matrix for $|y^{t\bar{t}Z}|$ variable at parton-level in region SR-3L-ttZ.
Migration matrix for $|y^{t\bar{t}Z}|$ variable at parton-level in region SR-3L-tZq.
Migration matrix for $|y^{t\bar{t}Z}|$ variable at parton-level in region SR-3L-WZ.
Migration matrix for $|y^{t\bar{t}Z}|$ variable at parton-level in region SR-4L-DF.
Migration matrix for $|y^{t\bar{t}Z}|$ variable at parton-level in region SR-4L-SF.
Migration matrix for $|y^{t\bar{t}Z}|$ variable at parton-level in region CR-4L-ZZ.
Covariance matrix for absolute cross section as a function of $p_{T}^{\mathrm{top}}$ at particle-level.
Covariance matrix for normalized cross section as a function of $p_{T}^{\mathrm{top}}$ at particle-level.
Covariance matrix for absolute cross section as a function of $p_{T}^{\mathrm{top}}$ at parton-level.
Covariance matrix for normalized cross section as a function of $p_{T}^{\mathrm{top}}$ at parton-level.
Covariance matrix for absolute cross section as a function of $p_{T}^{t\bar{t}}$ at particle-level.
Covariance matrix for normalized cross section as a function of $p_{T}^{t\bar{t}}$ at particle-level.
Covariance matrix for absolute cross section as a function of $p_{T}^{t\bar{t}}$ at parton-level.
Covariance matrix for normalized cross section as a function of $p_{T}^{t\bar{t}}$ at parton-level.
Covariance matrix for absolute cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ at particle-level.
Covariance matrix for normalized cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ at particle-level.
Covariance matrix for absolute cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ at parton-level.
Covariance matrix for normalized cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ at parton-level.
Covariance matrix for absolute cross section as a function of $m^{t\bar{t}Z}$ at particle-level.
Covariance matrix for normalized cross section as a function of $m^{t\bar{t}Z}$ at particle-level.
Covariance matrix for absolute cross section as a function of $m^{t\bar{t}Z}$ at parton-level.
Covariance matrix for normalized cross section as a function of $m^{t\bar{t}Z}$ at parton-level.
Covariance matrix for absolute cross section as a function of $m^{t\bar{t}}$ at particle-level.
Covariance matrix for normalized cross section as a function of $m^{t\bar{t}}$ at particle-level.
Covariance matrix for absolute cross section as a function of $m^{t\bar{t}}$ at parton-level.
Covariance matrix for normalized cross section as a function of $m^{t\bar{t}}$ at parton-level.
Covariance matrix for absolute cross section as a function of $|y^{t\bar{t}Z}|$ at particle-level.
Covariance matrix for normalized cross section as a function of $|y^{t\bar{t}Z}|$ at particle-level.
Covariance matrix for absolute cross section as a function of $|y^{t\bar{t}Z}|$ at parton-level.
Covariance matrix for normalized cross section as a function of $|y^{t\bar{t}Z}|$ at parton-level.
Covariance matrix for absolute cross section as a function of cos $\theta_{Z}^{*}$ at particle-level.
Covariance matrix for normalized cross section as a function of cos $\theta_{Z}^{*}$ at particle-level.
Covariance matrix for absolute cross section as a function of cos $\theta_{Z}^{*}$ at parton-level.
Covariance matrix for normalized cross section as a function of cos $\theta_{Z}^{*}$ at parton-level.
Covariance matrix for absolute cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ at particle-level.
Covariance matrix for normalized cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ at particle-level.
Covariance matrix for absolute cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ at parton-level.
Covariance matrix for normalized cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ at parton-level.
Covariance matrix for absolute cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ at particle-level.
Covariance matrix for normalized cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ at particle-level.
Covariance matrix for absolute cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ at parton-level.
Covariance matrix for normalized cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ at parton-level.
Covariance matrix for absolute cross section as a function of $|\Delta y(Z, t_{lep})|$ at particle-level.
Covariance matrix for normalized cross section as a function of $|\Delta y(Z, t_{lep})|$ at particle-level.
Covariance matrix for absolute cross section as a function of $|\Delta y(Z, t_{lep})|$ at parton-level.
Covariance matrix for normalized cross section as a function of $|\Delta y(Z, t_{lep})|$ at parton-level.
Covariance matrix for absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ at in the tetralepton channel particle-level.
Covariance matrix for normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ at in the tetralepton channel particle-level.
Covariance matrix for absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ at in the tetralepton channel parton-level.
Covariance matrix for normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ in the tetralepton channel at parton-level.
Covariance matrix for absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at particle-level.
Covariance matrix for normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at particle-level.
Covariance matrix for absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at parton-level.
Covariance matrix for normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at parton-level.
Covariance matrix for absolute cross section as a function of $N_{\text{jets}}$ in the tetralepton channel at particle-level.
Covariance matrix for normalized cross section as a function of $N_{\text{jets}}$ in the tetralepton channel at particle-level.
Covariance matrix for absolute cross section as a function of $N_{\text{jets}}$ in the trilepton channel at particle-level.
Covariance matrix for normalized cross section as a function of $N_{\text{jets}}$ in the trilepton channel at particle-level.
Covariance matrix for absolute cross section as a function of $p^{Z}_{T}$ at particle-level.
Covariance matrix for normalized cross section as a function of $p^{Z}_{T}$ at particle-level.
Covariance matrix for absolute cross section as a function of $p^{Z}_{T}$ at parton-level.
Covariance matrix for normalized cross section as a function of $p^{Z}_{T}$ at parton-level.
Covariance matrix for absolute cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ at particle-level.
Covariance matrix for normalized cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ at particle-level.
Covariance matrix for absolute cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ at parton-level.
Covariance matrix for normalized cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ at parton-level.
Covariance matrix for absolute cross section as a function of $|y^{Z}$| at particle-level.
Covariance matrix for normalized cross section as a function of $|y^{Z}$| at particle-level.
Covariance matrix for absolute cross section as a function of $|y^{Z}$| at parton-level.
Covariance matrix for normalized cross section as a function of $|y^{Z}$| at parton-level.
Ranking of nuisance parameters and background normalizations on signal strength for inclusive cross section measurement in combination of all channels
Correlation matrix of the input particle-level observables used in the EFT fit.
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