Author
Listed:
- Yan He
(Lanzhou University, School of Nuclear Science and Technology
RIKEN, High Energy Nuclear Physics Laboratory)
- Takehiko R. Saito
(Lanzhou University, School of Nuclear Science and Technology
RIKEN, High Energy Nuclear Physics Laboratory
Saitama University, Department of Physics
GSI Helmholtz Centre for Heavy Ion Research)
- Hiroyuki Ekawa
(RIKEN, High Energy Nuclear Physics Laboratory)
- Ayumi Kasagi
(RIKEN, High Energy Nuclear Physics Laboratory
Rikkyo University, Graduate School of Artificial Intelligence and Science)
- Yiming Gao
(RIKEN, High Energy Nuclear Physics Laboratory
Chinese Academy of Sciences, Institute of Modern Physics
University of Chinese Academy of Sciences)
- Enqiang Liu
(RIKEN, High Energy Nuclear Physics Laboratory
Chinese Academy of Sciences, Institute of Modern Physics
University of Chinese Academy of Sciences)
- Kazuma Nakazawa
(RIKEN, High Energy Nuclear Physics Laboratory
Gifu University, Faculty of Education
University of Fukui, The Research Institute of Nuclear Engineering)
- Christophe Rappold
(Instituto de Estructura de la Materia CSIC)
- Masato Taki
(Rikkyo University, Graduate School of Artificial Intelligence and Science)
- Yoshiki K. Tanaka
(RIKEN, High Energy Nuclear Physics Laboratory)
- He Wang
(RIKEN, High Energy Nuclear Physics Laboratory
University of Chinese Academy of Sciences
Chinese Academy of Sciences, State Key Laboratory of Heavy Ion Science and Technology, Institute of Modern Physics)
- Ayari Yanai
(RIKEN, High Energy Nuclear Physics Laboratory
Saitama University, Department of Physics)
- Junya Yoshida
(Tohoku University, International Center for Synchrotron Radiation Innovation Smart)
- Hongfei Zhang
(Lanzhou University, School of Nuclear Science and Technology
Xi’an Jiaotong University, School of Physics)
Abstract
Artificial intelligence (AI) is transforming not only our daily experiences but also the technological development landscape and scientific research. In this study, we pioneered the application of AI in double-strangeness hypernuclear studies. Studies that investigate quantum systems with strangeness via hyperon interactions provide insights into fundamental baryon-baryon interactions and contribute to our understanding of the nuclear force and composition of neutron star cores. Specifically, we report the observation of a double-Λ hypernucleus in nuclear emulsion achieved via innovative integration of machine learning techniques. The proposed methodology leverages generative AI and Monte Carlo simulations to produce training datasets combined with object detection AI for effective event identification. Based on the kinematic analysis and charge identification, the observed event was uniquely identified as the production and decay of $${13\atop \Lambda \Lambda }{{\rm{B}}}$$ 13 Λ Λ B , resulting from Ξ− capture by 14N in the nuclear emulsion. Assuming Ξ− capture in the atomic 3D state, the binding energy of the two Λ hyperons in $${13\atop \Lambda \Lambda }{{\rm{B}}}$$ 13 Λ Λ B , BΛΛ, was determined as 25.57 ± 1.18(stat.) ± 0.07(syst. ) MeV. The ΛΛ interaction energy ΔBΛΛ obtained was 2.83 ± 1.18(stat.) ± 0.14(syst. ) MeV.
Suggested Citation
Yan He & Takehiko R. Saito & Hiroyuki Ekawa & Ayumi Kasagi & Yiming Gao & Enqiang Liu & Kazuma Nakazawa & Christophe Rappold & Masato Taki & Yoshiki K. Tanaka & He Wang & Ayari Yanai & Junya Yoshida &, 2025.
"Artificial intelligence pioneers the double-strangeness factory,"
Nature Communications, Nature, vol. 16(1), pages 1-9, December.
Handle:
RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-66517-x
DOI: 10.1038/s41467-025-66517-x
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