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Jet Flavour Classification Using DeepJet
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Jet Flavour Classification Using DeepJet
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Jet flavour classification is of paramount importance for a broad range of applications in modern-day high-energy-physics experiments, particularly at the LHC. In this paper we propose a novel architecture for this task that exploits modern deep learning techniques. This new model, called DeepJet, overcomes the limitations in input size that affected previous approaches. As a result, the heavy flavour classification performance improves, and the model is extended to also perform quark-gluon tagging.
Forward citations
Cited by 6 Pith papers
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Combination of searches for heavy vector boson resonances in proton-proton collisions at $\sqrt{s}$ = 13 TeV
A CMS combination of searches finds no heavy vector boson resonance and excludes HVT W′/Z′ bosons below 5.5 TeV (weak coupling), 4.8 TeV (strong coupling), and 2.0 TeV for VBF production at 95% CL.
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Search for the pair production of long-lived supersymmetric partners of the tau lepton in proton-proton collisions at $\sqrt{s}$ = 13 TeV
No long-lived staus are observed; CMS excludes stau masses up to 425 GeV at 50 mm lifetime (mass-degenerate) and decay lengths 21-94 mm / 6-333 mm at 200 GeV.
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Search for dark matter produced in association with a Higgs boson decaying to bottom quarks in proton-proton collisions at $\sqrt{s}$ = 13 TeV
A CMS search with 138 fb^-1 of 13 TeV data finds no dark matter produced with a Higgs boson decaying to bottom quarks, and sets 95% CL exclusions on Z' and 2HDM+a model parameters.
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Search for a boosted Higgs boson decaying to bottom quark pairs in association with a W or Z boson in proton-proton collisions at $\sqrt{s}$ = 13 TeV
In 138 fb^-1 of 13 TeV proton collisions, CMS measures the boosted VH, H->bb signal strength as mu=0.72^{+0.75}_{-0.71}, consistent with the Standard Model.
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Measurement of the Higgs boson total decay width using the H $\to$ WW $\to$ e$\nu\mu\nu$ decay channel in proton-proton collisions at $\sqrt{s}$ = 13 TeV
CMS measures the Higgs total width as 3.9 +2.7 -2.2 MeV from the ratio of off-shell to on-shell H→WW production, consistent with the Standard Model.
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Deep-learning jet flavor tagging for precision hadronic Higgs measurements at future $e^+e^-$ Higgs factories
The two-stage deep-learning tagger pipeline projects CEPC statistical precisions of 0.18% (bb), 1.07% (cc), 0.52% (gg) and 78% (ss) for sigma(ZH)xBr(H->X) at 20 ab^-1, improving cc/gg benchmarks by ~42%/26%.
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