| Issue |
EPJ Web Conf.
Volume 337, 2025
27th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2024)
|
|
|---|---|---|
| Article Number | 01139 | |
| Number of page(s) | 9 | |
| DOI | https://doi.org/10.1051/epjconf/202533701139 | |
| Published online | 07 October 2025 | |
https://doi.org/10.1051/epjconf/202533701139
Reconstruction of Full Decays using Transformers and Hyperbolic Embedding at Belle II
LMU Munich, Germany
* e-mail: Boyang.Yu@physik.uni-muenchen.de
Published online: 7 October 2025
In analyses conducted at Belle II, it is often beneficial to reconstruct the entire decay chain of both B mesons produced in an electron-positron collision event using the information gathered from detectors. The currently used reconstruction algorithm, starting from the final state particles, consists of multiple stages that necessitate manual configurations and suffers from low efficiency and a high number of wrongly reconstructed candidates.
Within the Hypertagging project, we are developing software with the goal of automatically reconstructing B decays at Belle II with both high efficiency and accuracy. The trained models should be capable of accommodating rare decays with very small branching ratios, or even those that are unseen during the training phase.
To ensure optimal performance, the project is divided into the steps embedding of particles, particle reconstruction, and link prediction. Transformers and hyperbolic embedding are employed as fundamental components, with metric learning serving as the primary training technique.
In this paper, we present a proof-of-concept evaluation of the Hypertagging on a toy dataset.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.

