cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17182/hepdata.104860.v1/t15
title: "Distribution: 15" of "Search for R-parity violating supersymmetry in a final state containing leptons and many jets with the ATLAS experiment using $\sqrt{s} = 13$ TeV proton-proton collision data"

description: The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 20 GeV jet $p_{\mathrm{T}}$ threshold regions defined for the EWK analysis in the $2\ell^{\mathrm{sc}}$ category for 6 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
description: CERN-LHC.

A search for R-parity violating supersymmetry in final states characterised by high jet multiplicity, at least one isolated light lepton and either zero or at least three $b$-tagged jets is presented. The search uses 139 fb$^{-1}$ of $\sqrt{s} = 13$ TeV proton-proton collision data collected by the ATLAS experiment during Run 2 of the Large Hadron Collider. The results are interpreted in the context of R-parity-violating supersymmetry models that feature gluino production, top-squark production, or electroweakino production. The dominant sources of background are estimated using a data-driven model, based on observables at medium jet multiplicity, to predict the $b$-tagged jet multiplicity distribution at the higher jet multiplicities used in the search. Machine learning techniques are used to reach sensitivity to electroweakino production, extending the data-driven background estimation to the shape of the machine learning discriminant. No significant excess over the Standard Model expectation is observed and exclusion limits at the 95% confidence-level are extracted, reaching as high as 2.4 TeV in gluino mass, 1.35 TeV in top-squark mass, and 320 (365) GeV in higgsino (wino) mass.
DOI: 10.17182/hepdata.104860.v1/t16
title: "Distribution: 16" of "Search for R-parity violating supersymmetry in a final state containing leptons and many jets with the ATLAS experiment using $\sqrt{s} = 13$ TeV proton-proton collision data"

description: The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 20 GeV jet $p_{\mathrm{T}}$ threshold regions defined for the EWK analysis in the $2\ell^{\mathrm{sc}}$ category for 7 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
description: CERN-LHC.

A search for R-parity violating supersymmetry in final states characterised by high jet multiplicity, at least one isolated light lepton and either zero or at least three $b$-tagged jets is presented. The search uses 139 fb$^{-1}$ of $\sqrt{s} = 13$ TeV proton-proton collision data collected by the ATLAS experiment during Run 2 of the Large Hadron Collider. The results are interpreted in the context of R-parity-violating supersymmetry models that feature gluino production, top-squark production, or electroweakino production. The dominant sources of background are estimated using a data-driven model, based on observables at medium jet multiplicity, to predict the $b$-tagged jet multiplicity distribution at the higher jet multiplicities used in the search. Machine learning techniques are used to reach sensitivity to electroweakino production, extending the data-driven background estimation to the shape of the machine learning discriminant. No significant excess over the Standard Model expectation is observed and exclusion limits at the 95% confidence-level are extracted, reaching as high as 2.4 TeV in gluino mass, 1.35 TeV in top-squark mass, and 320 (365) GeV in higgsino (wino) mass.
DOI: 10.17182/hepdata.104860.v1/t17
title: "Distribution: 17" of "Search for R-parity violating supersymmetry in a final state containing leptons and many jets with the ATLAS experiment using $\sqrt{s} = 13$ TeV proton-proton collision data"

description: The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 20 GeV jet $p_{\mathrm{T}}$ threshold regions defined for the EWK analysis in the $2\ell^{\mathrm{sc}}$ category for 8 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
description: CERN-LHC.

A search for R-parity violating supersymmetry in final states characterised by high jet multiplicity, at least one isolated light lepton and either zero or at least three $b$-tagged jets is presented. The search uses 139 fb$^{-1}$ of $\sqrt{s} = 13$ TeV proton-proton collision data collected by the ATLAS experiment during Run 2 of the Large Hadron Collider. The results are interpreted in the context of R-parity-violating supersymmetry models that feature gluino production, top-squark production, or electroweakino production. The dominant sources of background are estimated using a data-driven model, based on observables at medium jet multiplicity, to predict the $b$-tagged jet multiplicity distribution at the higher jet multiplicities used in the search. Machine learning techniques are used to reach sensitivity to electroweakino production, extending the data-driven background estimation to the shape of the machine learning discriminant. No significant excess over the Standard Model expectation is observed and exclusion limits at the 95% confidence-level are extracted, reaching as high as 2.4 TeV in gluino mass, 1.35 TeV in top-squark mass, and 320 (365) GeV in higgsino (wino) mass.
DOI: 10.17182/hepdata.104860.v1/t18
title: "Distribution: 18" of "Search for R-parity violating supersymmetry in a final state containing leptons and many jets with the ATLAS experiment using $\sqrt{s} = 13$ TeV proton-proton collision data"

description: The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 20 GeV jet $p_{\mathrm{T}}$ threshold regions defined for the EWK analysis in the $2\ell^{\mathrm{sc}}$ category for 9 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
description: CERN-LHC.

A search for R-parity violating supersymmetry in final states characterised by high jet multiplicity, at least one isolated light lepton and either zero or at least three $b$-tagged jets is presented. The search uses 139 fb$^{-1}$ of $\sqrt{s} = 13$ TeV proton-proton collision data collected by the ATLAS experiment during Run 2 of the Large Hadron Collider. The results are interpreted in the context of R-parity-violating supersymmetry models that feature gluino production, top-squark production, or electroweakino production. The dominant sources of background are estimated using a data-driven model, based on observables at medium jet multiplicity, to predict the $b$-tagged jet multiplicity distribution at the higher jet multiplicities used in the search. Machine learning techniques are used to reach sensitivity to electroweakino production, extending the data-driven background estimation to the shape of the machine learning discriminant. No significant excess over the Standard Model expectation is observed and exclusion limits at the 95% confidence-level are extracted, reaching as high as 2.4 TeV in gluino mass, 1.35 TeV in top-squark mass, and 320 (365) GeV in higgsino (wino) mass.
DOI: 10.17182/hepdata.104860.v1/t19
title: "Distribution: 19" of "Search for R-parity violating supersymmetry in a final state containing leptons and many jets with the ATLAS experiment using $\sqrt{s} = 13$ TeV proton-proton collision data"

description: The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 20 GeV jet $p_{\mathrm{T}}$ threshold regions defined for the EWK analysis in the $2\ell^{\mathrm{sc}}$ category for at least 10 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
description: CERN-LHC.

A search for R-parity violating supersymmetry in final states characterised by high jet multiplicity, at least one isolated light lepton and either zero or at least three $b$-tagged jets is presented. The search uses 139 fb$^{-1}$ of $\sqrt{s} = 13$ TeV proton-proton collision data collected by the ATLAS experiment during Run 2 of the Large Hadron Collider. The results are interpreted in the context of R-parity-violating supersymmetry models that feature gluino production, top-squark production, or electroweakino production. The dominant sources of background are estimated using a data-driven model, based on observables at medium jet multiplicity, to predict the $b$-tagged jet multiplicity distribution at the higher jet multiplicities used in the search. Machine learning techniques are used to reach sensitivity to electroweakino production, extending the data-driven background estimation to the shape of the machine learning discriminant. No significant excess over the Standard Model expectation is observed and exclusion limits at the 95% confidence-level are extracted, reaching as high as 2.4 TeV in gluino mass, 1.35 TeV in top-squark mass, and 320 (365) GeV in higgsino (wino) mass.
DOI: 10.17182/hepdata.104860.v1/t21
title: "Distribution: 21" of "Search for R-parity violating supersymmetry in a final state containing leptons and many jets with the ATLAS experiment using $\sqrt{s} = 13$ TeV proton-proton collision data"

description: The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 40 GeV jet $p_{\mathrm{T}}$ threshold region in the $1\ell$ category for at least 12 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
description: CERN-LHC.

A search for R-parity violating supersymmetry in final states characterised by high jet multiplicity, at least one isolated light lepton and either zero or at least three $b$-tagged jets is presented. The search uses 139 fb$^{-1}$ of $\sqrt{s} = 13$ TeV proton-proton collision data collected by the ATLAS experiment during Run 2 of the Large Hadron Collider. The results are interpreted in the context of R-parity-violating supersymmetry models that feature gluino production, top-squark production, or electroweakino production. The dominant sources of background are estimated using a data-driven model, based on observables at medium jet multiplicity, to predict the $b$-tagged jet multiplicity distribution at the higher jet multiplicities used in the search. Machine learning techniques are used to reach sensitivity to electroweakino production, extending the data-driven background estimation to the shape of the machine learning discriminant. No significant excess over the Standard Model expectation is observed and exclusion limits at the 95% confidence-level are extracted, reaching as high as 2.4 TeV in gluino mass, 1.35 TeV in top-squark mass, and 320 (365) GeV in higgsino (wino) mass.
DOI: 10.17182/hepdata.104860.v1/t22
title: "Distribution: 22" of "Search for R-parity violating supersymmetry in a final state containing leptons and many jets with the ATLAS experiment using $\sqrt{s} = 13$ TeV proton-proton collision data"

description: The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 60 GeV jet $p_{\mathrm{T}}$ threshold region in the $1\ell$ category for at least 11 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
description: CERN-LHC.

A search for R-parity violating supersymmetry in final states characterised by high jet multiplicity, at least one isolated light lepton and either zero or at least three $b$-tagged jets is presented. The search uses 139 fb$^{-1}$ of $\sqrt{s} = 13$ TeV proton-proton collision data collected by the ATLAS experiment during Run 2 of the Large Hadron Collider. The results are interpreted in the context of R-parity-violating supersymmetry models that feature gluino production, top-squark production, or electroweakino production. The dominant sources of background are estimated using a data-driven model, based on observables at medium jet multiplicity, to predict the $b$-tagged jet multiplicity distribution at the higher jet multiplicities used in the search. Machine learning techniques are used to reach sensitivity to electroweakino production, extending the data-driven background estimation to the shape of the machine learning discriminant. No significant excess over the Standard Model expectation is observed and exclusion limits at the 95% confidence-level are extracted, reaching as high as 2.4 TeV in gluino mass, 1.35 TeV in top-squark mass, and 320 (365) GeV in higgsino (wino) mass.
DOI: 10.17182/hepdata.104860.v1/t23
title: "Distribution: 23" of "Search for R-parity violating supersymmetry in a final state containing leptons and many jets with the ATLAS experiment using $\sqrt{s} = 13$ TeV proton-proton collision data"

description: The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 80 GeV jet $p_{\mathrm{T}}$ threshold region in the $1\ell$ category for at least 10 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
description: CERN-LHC.

A search for R-parity violating supersymmetry in final states characterised by high jet multiplicity, at least one isolated light lepton and either zero or at least three $b$-tagged jets is presented. The search uses 139 fb$^{-1}$ of $\sqrt{s} = 13$ TeV proton-proton collision data collected by the ATLAS experiment during Run 2 of the Large Hadron Collider. The results are interpreted in the context of R-parity-violating supersymmetry models that feature gluino production, top-squark production, or electroweakino production. The dominant sources of background are estimated using a data-driven model, based on observables at medium jet multiplicity, to predict the $b$-tagged jet multiplicity distribution at the higher jet multiplicities used in the search. Machine learning techniques are used to reach sensitivity to electroweakino production, extending the data-driven background estimation to the shape of the machine learning discriminant. No significant excess over the Standard Model expectation is observed and exclusion limits at the 95% confidence-level are extracted, reaching as high as 2.4 TeV in gluino mass, 1.35 TeV in top-squark mass, and 320 (365) GeV in higgsino (wino) mass.
DOI: 10.17182/hepdata.104860.v1/t25
title: "Distribution: 25" of "Search for R-parity violating supersymmetry in a final state containing leptons and many jets with the ATLAS experiment using $\sqrt{s} = 13$ TeV proton-proton collision data"

description: The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 20 GeV jet $p_{\mathrm{T}}$ threshold region in the $2\ell^{\mathrm{sc}}$ category for at least 10 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
description: CERN-LHC.

A search for R-parity violating supersymmetry in final states characterised by high jet multiplicity, at least one isolated light lepton and either zero or at least three $b$-tagged jets is presented. The search uses 139 fb$^{-1}$ of $\sqrt{s} = 13$ TeV proton-proton collision data collected by the ATLAS experiment during Run 2 of the Large Hadron Collider. The results are interpreted in the context of R-parity-violating supersymmetry models that feature gluino production, top-squark production, or electroweakino production. The dominant sources of background are estimated using a data-driven model, based on observables at medium jet multiplicity, to predict the $b$-tagged jet multiplicity distribution at the higher jet multiplicities used in the search. Machine learning techniques are used to reach sensitivity to electroweakino production, extending the data-driven background estimation to the shape of the machine learning discriminant. No significant excess over the Standard Model expectation is observed and exclusion limits at the 95% confidence-level are extracted, reaching as high as 2.4 TeV in gluino mass, 1.35 TeV in top-squark mass, and 320 (365) GeV in higgsino (wino) mass.
DOI: 10.17182/hepdata.104860.v1/t26
title: "Distribution: 26" of "Search for R-parity violating supersymmetry in a final state containing leptons and many jets with the ATLAS experiment using $\sqrt{s} = 13$ TeV proton-proton collision data"

description: The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 40 GeV jet $p_{\mathrm{T}}$ threshold region in the $2\ell^{\mathrm{sc}}$ category for at least 8 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
description: CERN-LHC.

A search for R-parity violating supersymmetry in final states characterised by high jet multiplicity, at least one isolated light lepton and either zero or at least three $b$-tagged jets is presented. The search uses 139 fb$^{-1}$ of $\sqrt{s} = 13$ TeV proton-proton collision data collected by the ATLAS experiment during Run 2 of the Large Hadron Collider. The results are interpreted in the context of R-parity-violating supersymmetry models that feature gluino production, top-squark production, or electroweakino production. The dominant sources of background are estimated using a data-driven model, based on observables at medium jet multiplicity, to predict the $b$-tagged jet multiplicity distribution at the higher jet multiplicities used in the search. Machine learning techniques are used to reach sensitivity to electroweakino production, extending the data-driven background estimation to the shape of the machine learning discriminant. No significant excess over the Standard Model expectation is observed and exclusion limits at the 95% confidence-level are extracted, reaching as high as 2.4 TeV in gluino mass, 1.35 TeV in top-squark mass, and 320 (365) GeV in higgsino (wino) mass.
DOI: 10.17182/hepdata.104860.v1/t27
title: "Distribution: 27" of "Search for R-parity violating supersymmetry in a final state containing leptons and many jets with the ATLAS experiment using $\sqrt{s} = 13$ TeV proton-proton collision data"

description: The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 60 GeV jet $p_{\mathrm{T}}$ threshold region in the $2\ell^{\mathrm{sc}}$ category for at least 7 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
description: CERN-LHC.

A search for R-parity violating supersymmetry in final states characterised by high jet multiplicity, at least one isolated light lepton and either zero or at least three $b$-tagged jets is presented. The search uses 139 fb$^{-1}$ of $\sqrt{s} = 13$ TeV proton-proton collision data collected by the ATLAS experiment during Run 2 of the Large Hadron Collider. The results are interpreted in the context of R-parity-violating supersymmetry models that feature gluino production, top-squark production, or electroweakino production. The dominant sources of background are estimated using a data-driven model, based on observables at medium jet multiplicity, to predict the $b$-tagged jet multiplicity distribution at the higher jet multiplicities used in the search. Machine learning techniques are used to reach sensitivity to electroweakino production, extending the data-driven background estimation to the shape of the machine learning discriminant. No significant excess over the Standard Model expectation is observed and exclusion limits at the 95% confidence-level are extracted, reaching as high as 2.4 TeV in gluino mass, 1.35 TeV in top-squark mass, and 320 (365) GeV in higgsino (wino) mass.
DOI: 10.17182/hepdata.104860.v1/t20
title: "Distribution: 20" of "Search for R-parity violating supersymmetry in a final state containing leptons and many jets with the ATLAS experiment using $\sqrt{s} = 13$ TeV proton-proton collision data"

description: The observed data event yields and the corresponding estimates for the backgrounds in the different $b$-jet multiplicity bins for the 20 GeV jet $p_{\mathrm{T}}$ threshold region in the $1\ell$ category for at least 15 jets. The background is estimated by including all bins in the fit. All uncertainties, which may be correlated across the bins, are included in the total background uncertainty.
description: CERN-LHC.

A search for R-parity violating supersymmetry in final states characterised by high jet multiplicity, at least one isolated light lepton and either zero or at least three $b$-tagged jets is presented. The search uses 139 fb$^{-1}$ of $\sqrt{s} = 13$ TeV proton-proton collision data collected by the ATLAS experiment during Run 2 of the Large Hadron Collider. The results are interpreted in the context of R-parity-violating supersymmetry models that feature gluino production, top-squark production, or electroweakino production. The dominant sources of background are estimated using a data-driven model, based on observables at medium jet multiplicity, to predict the $b$-tagged jet multiplicity distribution at the higher jet multiplicities used in the search. Machine learning techniques are used to reach sensitivity to electroweakino production, extending the data-driven background estimation to the shape of the machine learning discriminant. No significant excess over the Standard Model expectation is observed and exclusion limits at the 95% confidence-level are extracted, reaching as high as 2.4 TeV in gluino mass, 1.35 TeV in top-squark mass, and 320 (365) GeV in higgsino (wino) mass.