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We report a search for a heavy neutral lepton (HNL) that mixes predominantly with${\nu }_{\tau }$. The search utilizes data collected with the Belle detector at the KEKB asymmetric energy$e^{+}{e}^{-}$collider. The data sample was collected at and just below the center-of-mass energies of the$\mathrm{\Upsilon }(4S)$and$\mathrm{\Upsilon }(5S)$resonances and has an integrated luminosity of$915{\mathrm{fb}}^{-1}$, corresponding to$(836\pm 12)\times {10}^6$$e^{+}{e}^{-}\to {\tau }^{+}{\tau }^{-}$events. We search for production of the HNL (denoted$N$) in the decay${\tau }^{-}\to {\pi }^{-}N$followed by its decay via$N\to {\mu }^{+}{\mu }^{-}{\nu }_{\tau }$. The search focuses on the parameter-space region in which the HNL is long-lived, so that the${\mu }^{+}{\mu }^{-}$originate from a common vertex that is significantly displaced from the collision point of the KEKB beams. Consistent with the expected background yield, one event is observed in the data sample after application of all the event-selection criteria. We report limits on the mixing parameter of the HNL with the$\tau$neutrino as a function of the HNL mass.

Published by the American Physical Society2024 

This paper introduces a novel LiDAR point cloud data encoding solution that is compact, flexible, and fully supports distributed data storage within the Hadoop distributed computing environment. The proposed data encoding solution is developed based on Sequence File and Google Protocol Buffers. Sequence File is a generic splittable binary file format built in the Hadoop framework for storage of arbitrary binary data. The key challenge in adopting the Sequence File format for LiDAR data is in the strategy for effectively encoding the LiDAR data as binary sequences in a way that the data can be represented compactly, while allowing necessary mutation. For that purpose, a data encoding solution, based on Google Protocol Buffers (a language-neutral, cross-platform, extensible data serialisation framework) was developed and evaluated. Since neither of the underlying technologies is sufficient to completely and efficiently represent all necessary point formats for distributed computing, an innovative fusion of them was required to provide a viable data storage solution. This paper presents the details of such a data encoding implementation and rigorously evaluates the efficiency of the proposed data encoding solution. Benchmarking was done against a straightforward, naive text encoding implementation using a high-density aerial LiDAR scan of a portion of Dublin, Ireland. The results demonstrated a 6-times reduction in data volume, a 4-times reduction in database ingestion time, and up to a 5 times reduction in querying time. 

We report a search for the charged-lepton flavor violation in Υ(2S) →ℓ^∓τ^±(ℓ=e, μ) decays using a 25 fb⁻¹Υ(2S) sample collected by the Belle detector at the KEKBe⁺e⁻asymmetric-energy collider. We find no evidence for a signal and set upper limits on the branching fractions ($$ \mathcal{B} $$$B$) at 90% confidence level. We obtain the most stringent upper limits:$$ \mathcal{B} $$$B$(Υ(2S)→ μ^∓τ^±)<0.23×10⁻⁶and$$ \mathcal{B} $$$B$(Υ(2S)→ e^∓τ^±)<1.12×10⁻⁶.