Back to Search
Start Over
Hypernuclear event detection in the nuclear emulsion with Monte Carlo simulation and machine learning.
- Source :
-
Nuclear Instruments & Methods in Physics Research Section A . Nov2023, Vol. 1056, pN.PAG-N.PAG. 1p. - Publication Year :
- 2023
-
Abstract
- This study developed a novel method for detecting hypernuclear events recorded in nuclear emulsion sheets using machine learning techniques. The artificial neural network-based object detection model was trained on surrogate images created through Monte Carlo simulations and image-style transformations using generative adversarial networks. The performance of the proposed model was evaluated using α -decay events obtained from the J-PARC E07 emulsion data. The model achieved approximately twice the detection efficiency of conventional image processing and reduced the time spent on manual visual inspection by approximately 1/17. The established method was successfully applied to the detection of hypernuclear events. This approach is a state-of-the-art tool for discovering rare events recorded in nuclear emulsion sheets without any real data for training. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01689002
- Volume :
- 1056
- Database :
- Academic Search Index
- Journal :
- Nuclear Instruments & Methods in Physics Research Section A
- Publication Type :
- Academic Journal
- Accession number :
- 172974897
- Full Text :
- https://doi.org/10.1016/j.nima.2023.168663