cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17182/hepdata.88291.v1/t23
title: "Table 23" of "Nuclear modification of $\Upsilon$ states in pPb collisions at $\sqrt{s_\mathrm{NN}}$ = 5.02 TeV"

description: Nuclear modification factor of Y(2S) at forward and backward $y^{Y}_{CM}$ for 6 &lt; pT &lt; 30 GeV/c. The global uncertainty arises from the integrated luminosity uncertainties in pPb and pp collisions.
description: Production cross sections of $\Upsilon(1S)$, $\Upsilon(2S)$, and $\Upsilon(3S)$ states decaying into $\mu^{+}\mu^{-}$ in proton-lead (pPb) collisions are reported using data collected by the CMS experiment at $\sqrt{s_{_{\mathrm{NN}}}} = $ 5.02 TeV. A comparison is made with corresponding cross sections obtained with pp data measured at the same collision energy and scaled by the Pb nucleus mass number. The nuclear modification factor for $\Upsilon(1S)$ is found to be $R_{\mathrm{pPb}}(\Upsilon(1S)) = $ 0.806 $ \pm\ $ 0.024 (stat) $ \pm\ $ 0.059 (syst). Similar results for the excited states indicate a sequential suppression pattern, such that $R_{\mathrm{pPb}}(\Upsilon(1S)) &gt; R_{\mathrm{pPb}}(\Upsilon(2S)) &gt; R_{\mathrm{pPb}}(\Upsilon(3S))$. The suppression is much less pronounced in pPb than in PbPb collisions, and independent of transverse momentum $p^{\Upsilon}_{T}$ and center-of-mass rapidity $y^{\Upsilon}_{CM}$ of the individual $\Upsilon$ state in the studied range $p^{\Upsilon}_{T} &lt; $ 30 GeV/c and $|y^{\Upsilon}_{CM}| &lt; $ 1.93. Models that incorporate sequential suppression of bottomonia in pPb collisions are in better agreement with the data than those which only assume initial-state modifications.
DOI: 10.3535/9c3-8gl-223
title: Petrophora chlorosata (Scopoli, 1763)

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/kmj-nc6-bb7
title: Jodis putata (Linnaeus, 1758)

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.15468/dl.k4wp9g
title: Occurrence Download

description: A dataset containing 34431 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Belgium",
 "TaxonKey is one of (Crassula helmsii, Lithobates catesbeianus, Misgurnus mohoity, Myriophyllum aquaticum, Procambarus clarkii, Procambarus virginalis, Xenopus laevis, Zizania latifolia)",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 2000"
 ]
}

 The dataset includes 34431 records from 38 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036007-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17182/hepdata.116281.v1/t13
title: "Figure 4 - bottom left, low pt MVA updated Decay Mode WPs" of "Identification of hadronic tau lepton decays using a deep neural network"

description: Efficiency for quark and gluon jets to pass different tau identification discriminators versus the efficiency for genuine tau_h. The upper two plots are obtained with jets from the W+jets simulated sample and the lower two plots with jets from the tt sample. The left two plots include jets and genuine tau_h with pt &lt; 100 GeV, whereas the right two plots include those with pt &gt; 100 GeV. The working points are indicated as full circles. The efficiency for jets from the W+jets event sample, enriched in quark jets, to pass the discriminators is higher compared to jets from the tt event sample, which has a larger fraction of gluon and b-quark jets. The jet efficiency for a given tau_h efficiency is larger for jets and tau_h with pt &lt; 100 GeV than for those with pt &gt; 100 GeV. Compared with the previously used MVA discriminator, the DEEPTAU discriminator reduces the jet efficiency for a given tau_h efficiency by consistently more than a factor of 1.8, and by more at high tau_h efficiency. The additional gain at high pt comes from the inclusion of updated decay modes in the tau_h reconstruction, as illustrated by the curves for the previously used MVA discriminator but including reconstructed tau_h candidates with additional decay modes.
description: A new algorithm is presented to discriminate reconstructed hadronic decays of tau leptons (tau_h) that originate from genuine tau leptons in the CMS detector against tau_h candidates that originate from quark or gluon jets, electrons, or muons. The algorithm inputs information from all reconstructed particles in the vicinity of a tau_h candidate and employs a deep neural network with convolutional layers to efficiently process the inputs. This algorithm leads to a significantly improved performance compared with the previously used one. For example, the efficiency for a genuine tau_h to pass the discriminator against jets increases by 10-30% for a given efficiency for quark and gluon jets. Furthermore, a more efficient tau_h reconstruction is introduced that incorporates additional hadronic decay modes. The superior performance of the new algorithm to discriminate against jets, electrons, and muons and the improved tau_h reconstruction method are validated with LHC proton-proton collision data at sqrt(s) = 13 TeV.
DOI: 10.17182/hepdata.116281.v1/t14
title: "Figure 4 - bottom right, high pt DeepTau vs jet" of "Identification of hadronic tau lepton decays using a deep neural network"

description: Efficiency for quark and gluon jets to pass different tau identification discriminators versus the efficiency for genuine tau_h. The upper two plots are obtained with jets from the W+jets simulated sample and the lower two plots with jets from the tt sample. The left two plots include jets and genuine tau_h with pt &lt; 100 GeV, whereas the right two plots include those with pt &gt; 100 GeV. The working points are indicated as full circles. The efficiency for jets from the W+jets event sample, enriched in quark jets, to pass the discriminators is higher compared to jets from the tt event sample, which has a larger fraction of gluon and b-quark jets. The jet efficiency for a given tau_h efficiency is larger for jets and tau_h with pt &lt; 100 GeV than for those with pt &gt; 100 GeV. Compared with the previously used MVA discriminator, the DEEPTAU discriminator reduces the jet efficiency for a given tau_h efficiency by consistently more than a factor of 1.8, and by more at high tau_h efficiency. The additional gain at high pt comes from the inclusion of updated decay modes in the tau_h reconstruction, as illustrated by the curves for the previously used MVA discriminator but including reconstructed tau_h candidates with additional decay modes.
description: A new algorithm is presented to discriminate reconstructed hadronic decays of tau leptons (tau_h) that originate from genuine tau leptons in the CMS detector against tau_h candidates that originate from quark or gluon jets, electrons, or muons. The algorithm inputs information from all reconstructed particles in the vicinity of a tau_h candidate and employs a deep neural network with convolutional layers to efficiently process the inputs. This algorithm leads to a significantly improved performance compared with the previously used one. For example, the efficiency for a genuine tau_h to pass the discriminator against jets increases by 10-30% for a given efficiency for quark and gluon jets. Furthermore, a more efficient tau_h reconstruction is introduced that incorporates additional hadronic decay modes. The superior performance of the new algorithm to discriminate against jets, electrons, and muons and the improved tau_h reconstruction method are validated with LHC proton-proton collision data at sqrt(s) = 13 TeV.
DOI: 10.17182/hepdata.116281.v1/t15
title: "Figure 4 - bottom right, high pt DeepTau vs jet WPs" of "Identification of hadronic tau lepton decays using a deep neural network"

description: Efficiency for quark and gluon jets to pass different tau identification discriminators versus the efficiency for genuine tau_h. The upper two plots are obtained with jets from the W+jets simulated sample and the lower two plots with jets from the tt sample. The left two plots include jets and genuine tau_h with pt &lt; 100 GeV, whereas the right two plots include those with pt &gt; 100 GeV. The working points are indicated as full circles. The efficiency for jets from the W+jets event sample, enriched in quark jets, to pass the discriminators is higher compared to jets from the tt event sample, which has a larger fraction of gluon and b-quark jets. The jet efficiency for a given tau_h efficiency is larger for jets and tau_h with pt &lt; 100 GeV than for those with pt &gt; 100 GeV. Compared with the previously used MVA discriminator, the DEEPTAU discriminator reduces the jet efficiency for a given tau_h efficiency by consistently more than a factor of 1.8, and by more at high tau_h efficiency. The additional gain at high pt comes from the inclusion of updated decay modes in the tau_h reconstruction, as illustrated by the curves for the previously used MVA discriminator but including reconstructed tau_h candidates with additional decay modes.
description: A new algorithm is presented to discriminate reconstructed hadronic decays of tau leptons (tau_h) that originate from genuine tau leptons in the CMS detector against tau_h candidates that originate from quark or gluon jets, electrons, or muons. The algorithm inputs information from all reconstructed particles in the vicinity of a tau_h candidate and employs a deep neural network with convolutional layers to efficiently process the inputs. This algorithm leads to a significantly improved performance compared with the previously used one. For example, the efficiency for a genuine tau_h to pass the discriminator against jets increases by 10-30% for a given efficiency for quark and gluon jets. Furthermore, a more efficient tau_h reconstruction is introduced that incorporates additional hadronic decay modes. The superior performance of the new algorithm to discriminate against jets, electrons, and muons and the improved tau_h reconstruction method are validated with LHC proton-proton collision data at sqrt(s) = 13 TeV.
DOI: 10.17182/hepdata.116281.v1/t16
title: "Figure 4 - bottom right, high pt MVA WPs" of "Identification of hadronic tau lepton decays using a deep neural network"

description: Efficiency for quark and gluon jets to pass different tau identification discriminators versus the efficiency for genuine tau_h. The upper two plots are obtained with jets from the W+jets simulated sample and the lower two plots with jets from the tt sample. The left two plots include jets and genuine tau_h with pt &lt; 100 GeV, whereas the right two plots include those with pt &gt; 100 GeV. The working points are indicated as full circles. The efficiency for jets from the W+jets event sample, enriched in quark jets, to pass the discriminators is higher compared to jets from the tt event sample, which has a larger fraction of gluon and b-quark jets. The jet efficiency for a given tau_h efficiency is larger for jets and tau_h with pt &lt; 100 GeV than for those with pt &gt; 100 GeV. Compared with the previously used MVA discriminator, the DEEPTAU discriminator reduces the jet efficiency for a given tau_h efficiency by consistently more than a factor of 1.8, and by more at high tau_h efficiency. The additional gain at high pt comes from the inclusion of updated decay modes in the tau_h reconstruction, as illustrated by the curves for the previously used MVA discriminator but including reconstructed tau_h candidates with additional decay modes.
description: A new algorithm is presented to discriminate reconstructed hadronic decays of tau leptons (tau_h) that originate from genuine tau leptons in the CMS detector against tau_h candidates that originate from quark or gluon jets, electrons, or muons. The algorithm inputs information from all reconstructed particles in the vicinity of a tau_h candidate and employs a deep neural network with convolutional layers to efficiently process the inputs. This algorithm leads to a significantly improved performance compared with the previously used one. For example, the efficiency for a genuine tau_h to pass the discriminator against jets increases by 10-30% for a given efficiency for quark and gluon jets. Furthermore, a more efficient tau_h reconstruction is introduced that incorporates additional hadronic decay modes. The superior performance of the new algorithm to discriminate against jets, electrons, and muons and the improved tau_h reconstruction method are validated with LHC proton-proton collision data at sqrt(s) = 13 TeV.
DOI: 10.17182/hepdata.88291.v1/t24
title: "Table 24" of "Nuclear modification of $\Upsilon$ states in pPb collisions at $\sqrt{s_\mathrm{NN}}$ = 5.02 TeV"

description: Nuclear modification factor of Y(3S) at forward and backward $y^{Y}_{CM}$ for 6 &lt; pT &lt; 30 GeV/c. The global uncertainty arises from the integrated luminosity uncertainties in pPb and pp collisions.
description: Production cross sections of $\Upsilon(1S)$, $\Upsilon(2S)$, and $\Upsilon(3S)$ states decaying into $\mu^{+}\mu^{-}$ in proton-lead (pPb) collisions are reported using data collected by the CMS experiment at $\sqrt{s_{_{\mathrm{NN}}}} = $ 5.02 TeV. A comparison is made with corresponding cross sections obtained with pp data measured at the same collision energy and scaled by the Pb nucleus mass number. The nuclear modification factor for $\Upsilon(1S)$ is found to be $R_{\mathrm{pPb}}(\Upsilon(1S)) = $ 0.806 $ \pm\ $ 0.024 (stat) $ \pm\ $ 0.059 (syst). Similar results for the excited states indicate a sequential suppression pattern, such that $R_{\mathrm{pPb}}(\Upsilon(1S)) &gt; R_{\mathrm{pPb}}(\Upsilon(2S)) &gt; R_{\mathrm{pPb}}(\Upsilon(3S))$. The suppression is much less pronounced in pPb than in PbPb collisions, and independent of transverse momentum $p^{\Upsilon}_{T}$ and center-of-mass rapidity $y^{\Upsilon}_{CM}$ of the individual $\Upsilon$ state in the studied range $p^{\Upsilon}_{T} &lt; $ 30 GeV/c and $|y^{\Upsilon}_{CM}| &lt; $ 1.93. Models that incorporate sequential suppression of bottomonia in pPb collisions are in better agreement with the data than those which only assume initial-state modifications.
DOI: 10.17182/hepdata.88291.v1/t25
title: "Table 25" of "Nuclear modification of $\Upsilon$ states in pPb collisions at $\sqrt{s_\mathrm{NN}}$ = 5.02 TeV"

description: RFB of Y(1S) versus $N^{|\eta_{lab}|&lt;2.4}_{tracks}$.
description: Production cross sections of $\Upsilon(1S)$, $\Upsilon(2S)$, and $\Upsilon(3S)$ states decaying into $\mu^{+}\mu^{-}$ in proton-lead (pPb) collisions are reported using data collected by the CMS experiment at $\sqrt{s_{_{\mathrm{NN}}}} = $ 5.02 TeV. A comparison is made with corresponding cross sections obtained with pp data measured at the same collision energy and scaled by the Pb nucleus mass number. The nuclear modification factor for $\Upsilon(1S)$ is found to be $R_{\mathrm{pPb}}(\Upsilon(1S)) = $ 0.806 $ \pm\ $ 0.024 (stat) $ \pm\ $ 0.059 (syst). Similar results for the excited states indicate a sequential suppression pattern, such that $R_{\mathrm{pPb}}(\Upsilon(1S)) &gt; R_{\mathrm{pPb}}(\Upsilon(2S)) &gt; R_{\mathrm{pPb}}(\Upsilon(3S))$. The suppression is much less pronounced in pPb than in PbPb collisions, and independent of transverse momentum $p^{\Upsilon}_{T}$ and center-of-mass rapidity $y^{\Upsilon}_{CM}$ of the individual $\Upsilon$ state in the studied range $p^{\Upsilon}_{T} &lt; $ 30 GeV/c and $|y^{\Upsilon}_{CM}| &lt; $ 1.93. Models that incorporate sequential suppression of bottomonia in pPb collisions are in better agreement with the data than those which only assume initial-state modifications.
DOI: 10.17182/hepdata.88291.v1/t26
title: "Table 26" of "Nuclear modification of $\Upsilon$ states in pPb collisions at $\sqrt{s_\mathrm{NN}}$ = 5.02 TeV"

description: RFB of Y(2S) versus $N^{|\eta_{lab}|&lt;2.4}_{tracks}$.
description: Production cross sections of $\Upsilon(1S)$, $\Upsilon(2S)$, and $\Upsilon(3S)$ states decaying into $\mu^{+}\mu^{-}$ in proton-lead (pPb) collisions are reported using data collected by the CMS experiment at $\sqrt{s_{_{\mathrm{NN}}}} = $ 5.02 TeV. A comparison is made with corresponding cross sections obtained with pp data measured at the same collision energy and scaled by the Pb nucleus mass number. The nuclear modification factor for $\Upsilon(1S)$ is found to be $R_{\mathrm{pPb}}(\Upsilon(1S)) = $ 0.806 $ \pm\ $ 0.024 (stat) $ \pm\ $ 0.059 (syst). Similar results for the excited states indicate a sequential suppression pattern, such that $R_{\mathrm{pPb}}(\Upsilon(1S)) &gt; R_{\mathrm{pPb}}(\Upsilon(2S)) &gt; R_{\mathrm{pPb}}(\Upsilon(3S))$. The suppression is much less pronounced in pPb than in PbPb collisions, and independent of transverse momentum $p^{\Upsilon}_{T}$ and center-of-mass rapidity $y^{\Upsilon}_{CM}$ of the individual $\Upsilon$ state in the studied range $p^{\Upsilon}_{T} &lt; $ 30 GeV/c and $|y^{\Upsilon}_{CM}| &lt; $ 1.93. Models that incorporate sequential suppression of bottomonia in pPb collisions are in better agreement with the data than those which only assume initial-state modifications.
DOI: 10.3535/x19-sax-0dh
title: Chlorissa viridata (Linnaeus, 1758)

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/yep-de0-vve
title: Petrophora chlorosata (Scopoli, 1763)

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.17182/hepdata.116281.v1/t17
title: "Figure 4 - bottom right, high pt MVA updated Decay Mode WPs" of "Identification of hadronic tau lepton decays using a deep neural network"

description: Efficiency for quark and gluon jets to pass different tau identification discriminators versus the efficiency for genuine tau_h. The upper two plots are obtained with jets from the W+jets simulated sample and the lower two plots with jets from the tt sample. The left two plots include jets and genuine tau_h with pt &lt; 100 GeV, whereas the right two plots include those with pt &gt; 100 GeV. The working points are indicated as full circles. The efficiency for jets from the W+jets event sample, enriched in quark jets, to pass the discriminators is higher compared to jets from the tt event sample, which has a larger fraction of gluon and b-quark jets. The jet efficiency for a given tau_h efficiency is larger for jets and tau_h with pt &lt; 100 GeV than for those with pt &gt; 100 GeV. Compared with the previously used MVA discriminator, the DEEPTAU discriminator reduces the jet efficiency for a given tau_h efficiency by consistently more than a factor of 1.8, and by more at high tau_h efficiency. The additional gain at high pt comes from the inclusion of updated decay modes in the tau_h reconstruction, as illustrated by the curves for the previously used MVA discriminator but including reconstructed tau_h candidates with additional decay modes.
description: A new algorithm is presented to discriminate reconstructed hadronic decays of tau leptons (tau_h) that originate from genuine tau leptons in the CMS detector against tau_h candidates that originate from quark or gluon jets, electrons, or muons. The algorithm inputs information from all reconstructed particles in the vicinity of a tau_h candidate and employs a deep neural network with convolutional layers to efficiently process the inputs. This algorithm leads to a significantly improved performance compared with the previously used one. For example, the efficiency for a genuine tau_h to pass the discriminator against jets increases by 10-30% for a given efficiency for quark and gluon jets. Furthermore, a more efficient tau_h reconstruction is introduced that incorporates additional hadronic decay modes. The superior performance of the new algorithm to discriminate against jets, electrons, and muons and the improved tau_h reconstruction method are validated with LHC proton-proton collision data at sqrt(s) = 13 TeV.
DOI: 10.17182/hepdata.116281.v1/t18
title: "Figure 5" of "Identification of hadronic tau lepton decays using a deep neural network"

description: Efficiencies for simulated tau_h decays with |eta| &lt; 2.3 to pass the following reconstruction and identification requirements: to be reconstructed in any decay mode with pt &gt; 20 GeV and |eta| &lt; 2.3 (black dashed line), to be reconstructed in a decay mode except for those with missing charged hadrons (labelled ''2-prong'' and shown as full black line), and to be reconstructed in a decay mode except the 2-prong ones and to pass the Loose, Medium, or Tight working point of the Djet discriminator (blue lines), obtained with a Z to tau tau event sample. The efficiencies are shown as a function of the visible genuine tau_h pt obtained from simulated decay products.
description: A new algorithm is presented to discriminate reconstructed hadronic decays of tau leptons (tau_h) that originate from genuine tau leptons in the CMS detector against tau_h candidates that originate from quark or gluon jets, electrons, or muons. The algorithm inputs information from all reconstructed particles in the vicinity of a tau_h candidate and employs a deep neural network with convolutional layers to efficiently process the inputs. This algorithm leads to a significantly improved performance compared with the previously used one. For example, the efficiency for a genuine tau_h to pass the discriminator against jets increases by 10-30% for a given efficiency for quark and gluon jets. Furthermore, a more efficient tau_h reconstruction is introduced that incorporates additional hadronic decay modes. The superior performance of the new algorithm to discriminate against jets, electrons, and muons and the improved tau_h reconstruction method are validated with LHC proton-proton collision data at sqrt(s) = 13 TeV.
DOI: 10.17182/hepdata.116281.v1/t19
title: "Figure 6 - left, low pt DeepTau vs ele" of "Identification of hadronic tau lepton decays using a deep neural network"

description: Efficiency for electrons against efficiency for genuine tau_h to pass the MVA and De discriminators, separately for electrons and tau_h with 20 &lt; pt &lt; 100 GeV (left) and pt &gt; 100 GeV (right). Vertical bars correspond to the statistical uncertainties. The tau_h candidates are reconstructed in one of the tau_h decay modes without missing charged hadrons. Compared with the MVA discriminator, the De discriminator reduces the electron efficiency by more than a factor of two for a tau_h efficiency of 70% and by more than a factor of 10 for τh efficiencies larger than 88%. Furthermore, working points (indicated as full circles) are now provided for previously inaccessible tau_h efficiencies larger than 90%, for a misidentification efficiency between 0.3 and 8%.
description: A new algorithm is presented to discriminate reconstructed hadronic decays of tau leptons (tau_h) that originate from genuine tau leptons in the CMS detector against tau_h candidates that originate from quark or gluon jets, electrons, or muons. The algorithm inputs information from all reconstructed particles in the vicinity of a tau_h candidate and employs a deep neural network with convolutional layers to efficiently process the inputs. This algorithm leads to a significantly improved performance compared with the previously used one. For example, the efficiency for a genuine tau_h to pass the discriminator against jets increases by 10-30% for a given efficiency for quark and gluon jets. Furthermore, a more efficient tau_h reconstruction is introduced that incorporates additional hadronic decay modes. The superior performance of the new algorithm to discriminate against jets, electrons, and muons and the improved tau_h reconstruction method are validated with LHC proton-proton collision data at sqrt(s) = 13 TeV.