Determining the distribution of plasma current in the equilibrium state is one of the most important steps to realize effective and safe operation of tokamak. In this study, a novel reconstruction code based on Bayesian inference is developed to infer the plasma current distribution for experiment analysis of EAST. Without iteratively solving Grad-Shafranov (G-S) equation to find an optimal fit for the external magnetic diagnostic measurements, the distribution of toroidal current density and poloidal flux can be rapidly derived in a probabilistic manner. The reconstructed results are consistent with the results based on equilibrium fitting (EFIT) code, and the execution time is less than 1 ms for each time slice, which indicates its potential for application in future real-time plasma feedback control.

中文翻译：

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基于贝叶斯推理的 EAST 等离子体电流分布重建

确定平衡状态下等离子体电流的分布是实现托卡马克有效、安全运行的最重要步骤之一。在本研究中，开发了一种基于贝叶斯推理的新型重建代码来推断等离子体电流分布，用于 EAST 的实验分析。无需迭代求解 Grad-Shafranov (GS) 方程来找到外部磁诊断测量的最佳拟合，就可以以概率方式快速导出环形电流密度和极向磁通的分布。重构结果与基于平衡拟合（EFIT）代码的结果一致，并且每个时间片的执行时间小于1 ms，这表明其在未来实时等离子体反馈控制中的应用潜力。