A new algorithm for identifying the flavour of B_s<SUP>0</SUP> mesons at LHCb

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JA, Waldi, R, Wallace, C, Wallace, R, Walsh, J, Wang, J, Ward, DR, Watson, NK, Websdale, D, Weiden, A, Whitehead, M, Wicht, J, Wilkinson, G, Wilkinson, M, Williams, M, Williams, MP, Williams, M, Williams, T, Wilson, FF, Wimberley, J, Wishahi, J, Wislicki, W, Witek, M, Wormser, G, Wotton, SA, Wraight, K, Wright, S, Wyllie, K, Xie, Y, Xu, Z, Yang, Z, Yu, J, Yuan, X, Yushchenko, O, Zangoli, M, Zavertyaev, M, Zhang, L, Zhang, Y, Zhelezov, A, Zhokhov, A, Zhong, L, Zhukov, V and Zucchelli, S (2016) A new algorithm for identifying the flavour of B_s<SUP>0</SUP> mesons at LHCb. JOURNAL OF INSTRUMENTATION, 11 (05). P05010-.

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Abstract

A new algorithm for the determination of the initial flavour of $B_s^0$ 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 $B_s^0$ meson. The second network combines the kaon charges to assign the $B_s^0$ 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 proton-proton collisions at 7 and 8 TeV centre-of-mass energies. The calibration is performed in two ways: by resolving the $B_s^0$-$\bar{B}_s^0$ flavour oscillations in $B_s^0 \to D_s^- \pi^+$ decays, and by analysing flavour-specific $B_{s 2}^{*}(5840)^0 \to B^+ K^-$ decays. The tagging power measured in $B_s^0 \to D_s^- \pi^+$ decays is found to be $(1.80 \pm 0.19({\rm stat}) \pm 0.18({\rm syst}))$\%, which is an improvement of about 50\% compared to a similar algorithm previously used in the LHCb experiment.

Item Type:	Article
Additional Information:	All figures and tables, along with any supplementary material and additional information, are available at https://lhcbproject.web.cern.ch/lhcbproject/Publications/LHCbProjectPublic/LHCb-PAPER-2015-056.html
Uncontrolled Keywords:	Analysis and statistical methods, Particle identification methods, Pattern recognition, cluster finding, calibration and fitting methods
Depositing User:	Symplectic Admin
Date Deposited:	07 Jun 2016 11:18
Last Modified:	18 Oct 2023 01:22
DOI:	10.1088/1748-0221/11/05/P05010
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3001575