Identification of beauty and charm quark jets at LHCb

The paper is available here.

arXiv:1504.07670, LHCb-PAPER-015-016

More detailed information: ANA note 2014-074-

Abstract

Identification of jets originating from beauty and charm quarks is important for measuring Standard Model processes and for searching for new physics. The performance of algorithms developed to select b- and c-quark jets is measured using data recorded by LHCb from proton-proton collisions at √s = 7 TeV in 2011 and at √s = 8 TeV in 2012. The efficiency for identifying a b(c) jet is about 65%(25%) with a probability for misidentifying a light-parton jet of 0.3% for jets with transverse momentum pT > 20 GeV and pseudorapidity 2.2 < η < 4.2. The dependence of the performance on the pT and η of the jet is also measured.

Figures

(Note, eps versions are available under attachments).

Caption Figure
Figure 1: SV-tagger algorithm BDT(b|c) versus BDT(bc|udsg) distributions obtained from simulation for (red) b, (green) c and (blue) light-parton jets. Fig1a.png
Fig1b.pngFig1c.png
Figure 2: Efficiencies and mistag probabilities obtained from simulation for the SV-tagger and TOPO algorithms for (red) b, (green) c and (blue) light-parton jets. The first plots show the dependence on pT for 2.2 < η < 4.2, while the second plots show the dependence on η for pT > 20 GeV (see text for details). The “loose” label for the TOPO refers to the BDT requirement used in the trigger for SVs that contain muon candidates. Fig2a.png Fig2b.png
Fig2c.pngFig2d.png Fig2e.pngFig2f.png
Figure 3: Efficiencies for SV-tagging a (b, c)-jet versus mistag probability for a light-parton jet from simulation. Fig3.png
Figure 4: SV-tagger BDT fit results for the B+jet data sample with 10 < pT(jet) < 100 GeV: (top) distribution in data; (bottom) two-dimensional template-fit result. Fig4a.png Fig4b.png
Figure 4 (cont): SV-tagger BDT fit results for the B+jet data sample with 10 < p(jet) < 100 GeV: projections of the fit result with the b, c, and light-parton contributions shown as stacked histograms. Fig4c.pngFig4d.png
Figure 5: SV-tagger BDT fit results for the D+jet data sample with 10 < pT(jet) < 100 GeV: (top) distribution in data; (bottom) two-dimensional template-fit result. Fig5a.png Fig5b.png
Figure 5 (cont): SV-tagger BDT fit results for the D+jet data sample with 10 < pT(jet) < 100 GeV: projections of the fit result with the b, c, and light-parton contributions shown as stacked histograms. Fig5c.pngFig5d.png
Figure 6: SV-tagger BDT fit results for the μ(b, c)+jet data sample with 10 < pT(jet) < 100 GeV: (top) distribution in data; (bottom) two-dimensional template-fit result. Fig6a.png Fig6b.png
Figure 6 (cont): SV-tagger BDT fit results for the μ(b, c)+jet data sample with 10 < pT(jet) < 100 GeV: projections of the fit result with the b, c, and light-parton contributions shown as stacked histograms. Fig6c.pngFig6d.png
Figure 7: Two-dimensional Mcor versus SV track multiplicity fit results for B+jet data samples. The top plot shows the projection onto the Mcor axis, while the bottom plot shows the projection onto the track multiplicity. The highest M cor bin includes candidates with Mcor > 10 GeV. Fig7a.png Fig7b.png
Figure 7 cont: Two-dimensional Mcor versus SV track multiplicity fit results for D+jet data samples. The top plot shows the projection onto the Mcor axis, while the bottom plot show sthe projection onto the track multiplicity. The highest M cor bin includes candidates with Mcor > 10 GeV. Fig7c.png Fig7d.png
Figure 7 cont: Two-dimensional Mcor versus SV track multiplicity fit results for μ(b, c)+jet data samples. The top plot shows the projection onto the Mcor axis, while the bottom plot shows the projection onto the track multiplicity. The highest Mcor bin includes candidates with Mcor > 10 GeV. Fig7e.png Fig7f.png
Figure 8: Fits to the TOPO BDT distribution in (top) B+jet, (middle) D+jet and (bottom) μ(b, c)+jet data samples with 10 < pT (jet) < 100 GeV. Fig8a.png Fig8b.pngFig8c.png
Figure 9: Results of χ2IP calibration using W+jet data for 10 < pT(jet) < 100 GeV. The tail out to large χ2IP values in the light-parton-jet sample is largely due to strange particle decays. Fig9.png
Figure 10: Fits to the χ2IP distribution in (top ) B+jet, (middle) D+jet and (bottom) μ(b, c)+jet data samples. Fig10a.png Fig10b.pngFig10c.png
Figure 11: SV-tagger two dimensional BDT fit results projected onto the (top) BDT(bc|udsg) and (middle) BDT(b|c) axes and (bottom) χ2IP fit results for the B+muon-jet subsample with 10 < pT(jet) < 100 GeV. Fig11a.png Fig11b.pngFig11c.png
Figure 12: SV-tagger two dimensional BDT fit results projected onto the (top) BDT(bc|udsg) and (middle) BDT(b|c) axes and (bottom) χ2IP fit results for the D+muon-jet subsample with 10 < pT(jet) < 100 GeV. Fig12a.png Fig12b.pngFig12c.png
Figure 13: SV-tagger two dimensional BDT fit results projected onto the (top) BDT(bc|udsg) and (middle) BDT(b|c) axes and (bottom) χ2IP fit results for the μ(b, c)+muon-jet subsample with 10 < pT(jet) < 100 GeV. Fig13a.png Fig13b.pngFig13c.png
Figure 14: Efficiencies of the SV-tagger algorithm measured in data relative to those obtained from simulation for 2.2 < η < 4.2: (top ) results from the (closed markers) highest-pT track and (open markers) muon-jet samples; (bottom) the combined results assuming the scale factors are the same for semileptonic and inclusive (b, c)-hadron decays. The absolute efficiencies corresponding to the combined (b, c)-jet results (bottom right). Fig14a.png Fig14b.png
Figure 14 cont: Efficiencies of the SV-tagger algorithm measured in data relative to those obtained from simulation for 2.2 < η < 4.2: (top) the combined results for (b, c)-jet using the highest-pT-track approach assuming the scale factors are the same for b and c jets. The absolute efficiencies corresponding to the combined (b, c)-jet results (bottom). Fig14c.pngFig14d.png
Figure 15: TOPO algorithm (b, c)-tagging efficiencies, using the “loose” BDT requirement, in data relative to those obtained in simulation. Fig15.png
Figure 16: SV-tagger algorithm BDT distributions for backward and too-long-lived SVs in the W+jet data sample: (top) distribution in data; (bottom) two-dimensional template-fit result. Fig16a.png Fig16b.png
Figure 16 cont: SV-tagger algorithm BDT distributions for backward and too-long-lived SVs in the W+jet data sample: projections of the fit result with the b, c, and light-parton contributions shown as stacked histograms. Fig16c.pngFig16d.png
Figure 17: Ratio of light-parton-jet mistag probabilities observed in data to those in simulation for the (left) SV-tagger and (right) TOPO algorithms. Fig17a.png Fig17b.png

-- KatharinaMueller - 2015-06-04

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