2019
DOI: 10.1007/s41781-019-0021-8
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The Full Event Interpretation

Abstract: The full event interpretation is presented: a new exclusive tagging algorithm used by the high-energy physics experiment Belle II. The experimental setup of Belle II allows the precise measurement of otherwise inaccessible B meson decay modes. The Full Event Interpretation algorithm enables many of these measurements. The algorithm relies on machine learning to automatically identify plausible B meson decay chains based on the data recorded by the detector. Compared to similar algorithms employed by previous e… Show more

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Cited by 72 publications
(45 citation statements)
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“…The discovery prospects for this decay at Belle II are excellent: the improved tracking capabilities, better calorimeter electronics, and the continuous development of modern tagging algorithms such as Ref. [235] will help improving the sensitivity. Extrapolating from the central value and uncertainty of the currently most precise limit of Eq.…”
Section: Experimental Status and Prospects Of B → ν γmentioning
confidence: 99%
“…The discovery prospects for this decay at Belle II are excellent: the improved tracking capabilities, better calorimeter electronics, and the continuous development of modern tagging algorithms such as Ref. [235] will help improving the sensitivity. Extrapolating from the central value and uncertainty of the currently most precise limit of Eq.…”
Section: Experimental Status and Prospects Of B → ν γmentioning
confidence: 99%
“…In the future, improvements of these limits by 1 to 2 orders of magnitudes are foreseen by Belle II and LHCb. Tauonic modes will particularly benefit from an improved tagging method at Belle II [62], and improved trigger and tracking efficiency from the LHCb upgrade.…”
Section: Search For Lepton Flavour/number Violating Decaysmentioning
confidence: 99%
“…This feature is exploited by using a boosted decision tree (BDT) to classify each input hit in a signal or background category and not process hits in the background category further. This procedure is very fast as the runtime scales almost linearly with the amount of input hits, contrary to the downstream pattern recognition steps, and the performance-optimized FastBDT [4] library is used. The benefits include a greatly reduced combinatorial complexity for later track finding stages, which results in a faster runtime and lower fake rate.…”
Section: Cdc Track Findingmentioning
confidence: 99%