Neural Networks for Particle Reconstruction in High Energy Physics Detectors
The core of the Particle Flow (PFlow) algorithms in High Energy Physics experiments lies in reconstructing the intrinsic nature and kinematic properties of both charged and neutral particles, utilizing the data provided by detectors. Through effective trajectory analysis methods for various particle
Authors
- Bo Hu (ORCID: https://orcid.org/0000-0003-2995-2358)
- X. Y. Niu (ORCID: https://orcid.org/0000-0001-6039-7976)
- Xiaobin Xu (ORCID: https://orcid.org/0009-0000-8310-1509)
- K. Yue (ORCID: https://orcid.org/0009-0003-3957-9304)
- Tiansheng Dai
Publication Details
- Published
- 2025-01-01
- DOI
- https://doi.org/10.4108/eai.21-11-2024.2354620
- Primary Topic
- Particle Detector Development and Performance
- Type
- article
- Field-Weighted Citation Impact
- 0.00