A new algorithm for the determination of the initial flavour of B0s mesons is presented. The algorithm is based on two neural networks and exploits the b hadron production mechanism at a hadron collider. The first network is trained to select charged kaons produced in association with the B0 s meson. The second network combines the kaon charges to assign the B0 s flavour and estimates the probability of a wrong assignment. The algorithm is calibrated using data corresponding to an integrated luminosity of 3 fb-1 collected by the LHCb experiment in protonproton collisions at 7 and 8 TeV centre-of-mass energies. The calibration is performed in two ways: by resolving the B0sB0s flavour oscillations in B0s →D-s φ+ decays, and by analysing flavour-specific B∗ s2 (5840)0→ B+K- decays. The tagging power measured in B0s → D-s φ+ decays is found to be (1:80 ± 0:19 (stat) ± 0:18 (syst))%, which is an improvement of about 50% compared to a similar algorithm previously used in the LHCb experiment.

A new algorithm for identifying the flavour of B0s mesons at LHCb

Lusardi N.;
2016-01-01

Abstract

A new algorithm for the determination of the initial flavour of B0s mesons is presented. The algorithm is based on two neural networks and exploits the b hadron production mechanism at a hadron collider. The first network is trained to select charged kaons produced in association with the B0 s meson. The second network combines the kaon charges to assign the B0 s flavour and estimates the probability of a wrong assignment. The algorithm is calibrated using data corresponding to an integrated luminosity of 3 fb-1 collected by the LHCb experiment in protonproton collisions at 7 and 8 TeV centre-of-mass energies. The calibration is performed in two ways: by resolving the B0sB0s flavour oscillations in B0s →D-s φ+ decays, and by analysing flavour-specific B∗ s2 (5840)0→ B+K- decays. The tagging power measured in B0s → D-s φ+ decays is found to be (1:80 ± 0:19 (stat) ± 0:18 (syst))%, which is an improvement of about 50% compared to a similar algorithm previously used in the LHCb experiment.
2016
Analysis and statistical methods
Calibration and fitting methods
Cluster finding
Particle identification methods
Pattern recognition
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1204635
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