Optimization of laser-driven quantum beam generation and the applications with artificial intelligence-Reference-Cited by-同舟云学术

Optimization of laser-driven quantum beam generation and the applications with artificial intelligence

Published:2024-05-01 Issue:5 Volume:31 Page:
ISSN:1070-664X
Container-title:Physics of Plasmas
language:en
Short-container-title:

Author:

Kuramitsu Y.¹²³^ORCID,Taguchi T.¹,Nikaido F.¹^ORCID,Minami T.¹³^ORCID,Hihara T.¹,Suzuki S.¹,Oda K.¹,Kuramoto K.¹^ORCID,Yasui T.¹^ORCID,Abe Y.¹^ORCID,Ibano K.¹^ORCID,Takabe H.¹^ORCID,Chu C. M.⁴,Wu K. T.⁴^ORCID,Woon W. Y.⁴^ORCID,Chen S. H.⁴^ORCID,Jao C. S.⁵^ORCID,Chen Y. C.⁶^ORCID,Liu Y. L.⁷^ORCID,Morace A.²^ORCID,Yogo A.²^ORCID,Arikawa Y.²^ORCID,Kohri H.⁸^ORCID,Tokiyasu A.⁹^ORCID,Kodaira S.¹⁰^ORCID,Kusumoto T.¹⁰^ORCID,Kanasaki M.¹¹^ORCID,Asai T.¹³,Fukuda Y.³^ORCID,Kondo K.³,Kiriyama H.³,Hayakawa T.³^ORCID,Tanaka S. J.¹^ORCID,Isayama S.¹²^ORCID,Watamura N.¹³,Suzuki H.¹³^ORCID,Kumar H. S.¹⁴^ORCID,Ohnishi N.¹⁴^ORCID,Pikuz T.¹⁵^ORCID,Filippov E.¹⁶^ORCID,Sakai K.¹^ORCID,Yasuhara R.¹⁷^ORCID,Nakata M.¹^ORCID,Ishikawa R.¹⁷^ORCID,Hoshi T.¹⁷^ORCID,Mizuta A.¹⁸^ORCID,Bolouki N.¹⁹^ORCID,Saura N.²⁰^ORCID,Benkadda S.²⁰^ORCID,Koenig M.¹²^ORCID,Hamaguchi S.¹^ORCID

Affiliation:

1. Graduate School of Engineering, Osaka University 1 , 2-1 Yamadaoka, Suita, Osaka 565-0871, Japan

2. Institute of Laser Engineering, Osaka University 2 , 2-6 Yamadaoka, Suita, Osaka 565-0871, Japan

3. Kansai Institute for Photon Science (KPSI), National Institutes for Quantum Science and Technology (QST) 3 , 8-1-7 Umemidai, Kizugawa, Kyoto 619-0215, Japan

4. Department of Physics, National Central University 4 , No. 300, Jhongda Rd., Jhongli, Taoyuan 320, Taiwan

5. Department of Physics, National Cheng Kung University 5 , Tainan 701, Taiwan

6. National Center for High-Performance Computing, National Applied Research Laboratories 6 , Tainan City 711010, Taiwan

7. Institute of Space and Plasma Sciences, National Cheng Kung University 7 , Tainan 701, Taiwan

8. Research Center for Nuclear Physics, Osaka University 8 , 10-1 Mihogaoka, Ibaraki, Osaka 567-0047, Japan

9. Research Center for Accelerator and Radioisotope Science, Tohoku University 9 , 1-2-1 Mikamine, Taihaku-ku, Sendai, Miyagi 982-0826, Japan

10. Institute for Radiological Science (NIRS), National Institutes for Quantum and Radiological Science and Technology (QST) 10 , Inage, Chiba 263-8555, Japan

11. Graduate School of Maritime Sciences, Kobe University 11 , Kobe 658-0022, Japan

12. Department of Advanced Environmental Science and Engineering, Kyushu University 13 , 6-1 Kasuga-Kohen, Kasuga, Fukuoka 816-8580, Japan

13. Graduate School of Information Science and Technology, Osaka University 14 , 2-1 Yamadaoka, Suita 565-0871, Japan

14. Department of Aerospace Engineering, Tohoku University 15 , 6-6-01 Aramakiazaaoba, Aoba-ku, Sendai 980-8579, Japan

15. Institute for Open and Transdisciplinary Research Initiatives, Osaka University 16 , 2-1 Yamadaoka, Suita, Osaka 565-0871, Japan

16. Centro de Laseres Pulsados (CLPU) 17 , 37185 Villamayor, Salamanca, Spain

17. National Institute for Fusion Science 18 , 322-6 Oroshicho, Toki, Gifu 509-5292, Japan

18. Astrophysical Big Bang Laboratory, RIKEN 20 , Wako, Saitama 351-0198, Japan

19. Department of Plasma Physics and Technology, Faculty of Science, Masaryk University 21 , Kotlářská 2, Brno 611 37, Czech Republic

20. Aix-Marseille Université CNRS PIIM, UMR 7345 22 , Marseille, France

Abstract

We have investigated space and astrophysical phenomena in nonrelativistic laboratory plasmas with long high-power lasers, such as collisionless shocks and magnetic reconnections, and have been exploring relativistic regimes with intense short pulse lasers, such as energetic ion acceleration using large-area suspended graphene. Increasing the intensity and repetition rate of the intense lasers, we have to handle large amounts of data from the experiments as well as the control parameters of laser beamlines. Artificial intelligence (AI) such as machine learning and neural networks may play essential roles in optimizing the laser and target conditions for efficient laser ion acceleration. Implementing AI into the laser system in mind, as the first step, we are introducing machine learning in ion etch pit analyses detected on plastic nuclear track detectors. Convolutional neural networks allow us to analyze big ion etch pit data with high precision and recall. We introduce one of the applications of laser-driven ion beams using AI to reconstruct vector electric and magnetic fields in laser-produced turbulent plasmas in three dimensions.

Funder

Japan Society for the Promotion of Science

National Science and Technology Council

National Institute for Physiological Sciences

Japan Society for the Promotion of Science,

NINS Program of Promoting Research by Networking among Institutions,

Ministry of Education, Youth, and Sports of the Czech Republic,

French Federation for Magnetic Fusion Studies (FR-FCM) and the Eurofusion Consortium, Search and Training Programme,

Sumitomo Foundation, the Research Foundation For Opto-Science and Technology

Publisher

AIP Publishing

Link