Abstract
Neutron tagging algorithm is under development for Hyper-Kamiokande. The algorithm aims to distinguish neutron capture events from the background due to random coincidence of dark noise hits. The tagging efficiency of neutron capture events and the misidentification of the background are evaluated in the detectors with different dark rates. In this baseline design with 8.4 kHz dark rate, the tagging efficiency is found to be 54% (49%) with 10% contamination of dark noise background if the true (reconstructed) vertex position is used, while the efficiency reaches 71% if the dark rate is suppressed to 3.0 kHz.
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