A new algorithm for the determination of the initial flavour of B
0
s 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
0
s meson. The second network combines the kaon charges to assign the B
0
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 B
0
s–B
0
s flavour oscillations in B
0
s → D
−
s π
+ decays, and by analysing flavour-specific
B
∗
s2
(5840)
0→ B
+K
− decays. The tagging power measured in B
0
s → D
−
s π
+ 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.