Plasma current tomography for HL-2A based on Bayesian inference  

作　　者：刘自结 王天博 吴木泉 罗正平 王硕 孙腾飞 肖炳甲 李建刚 Zijie LIU;Tianbo WANG;Muquan WU;Zhengping LUO;Shuo WANG;Tengfei SUN;Bingjia XIAO;Jiangang LI(College of Physics and Optoelectronic Engineering,Shenzhen University,Shenzhen 518060,People’s Republic of China;Southwestern Institute for Physics,Chengdu 610200,People’s Republic of China;Institute of Plasma Physics,Chinese Academy of Sciences,Hefei 230031,People’s Republic of China;University of Science and Technology of China,Hefei 230026,People’s Republic of China)

机构地区：[1]College of Physics and Optoelectronic Engineering,Shenzhen University,Shenzhen 518060,People’s Republic of China [2]Southwestern Institute for Physics,Chengdu 610200,People’s Republic of China [3]Institute of Plasma Physics,Chinese Academy of Sciences,Hefei 230031,People’s Republic of China [4]University of Science and Technology of China,Hefei 230026,People’s Republic of China

出　　处：《Plasma Science and Technology》2024年第5期165-173,共9页等离子体科学和技术（英文版）

基　　金：supported by the National MCF Energy R&D Program of China (Nos. 2018 YFE0301105, 2022YFE03010002 and 2018YFE0302100);the National Key R&D Program of China (Nos. 2022YFE03070004 and 2022YFE03070000);National Natural Science Foundation of China (Nos. 12205195, 12075155 and 11975277)

摘　　要：An accurate plasma current profile has irreplaceable value for the steady-state operation of the plasma.In this study,plasma current tomography based on Bayesian inference is applied to an HL-2A device and used to reconstruct the plasma current profile.Two different Bayesian probability priors are tried,namely the Conditional Auto Regressive(CAR)prior and the Advanced Squared Exponential(ASE)kernel prior.Compared to the CAR prior,the ASE kernel prior adopts nonstationary hyperparameters and introduces the current profile of the reference discharge into the hyperparameters,which can make the shape of the current profile more flexible in space.The results indicate that the ASE prior couples more information,reduces the probability of unreasonable solutions,and achieves higher reconstruction accuracy.

关 键 词：plasma current tomography Bayesian inference machine learning Gaussian distribution 

分 类 号：TL612[核科学技术—核技术及应用]