Title: Simultaneous kinetic profile and magnetic equilibrium inference with Bayesian integrated data analysis in preparation for ITER Show Chinese title

Title: 用于ITER准备的贝叶斯综合数据分析中的同时动力学轮廓和磁平衡推断

Abstract: Accurate plasma state reconstruction will be crucial for the success of ITER and future fusion plants, but the harsh conditions of a burning plasma will make diagnostic operation more challenging than in current machines. Integrated data analysis (IDA) based on Bayesian inference allows for improved information gain by combining the analysis of many diagnostics into a single step using sophisticated forward models. It also provides a framework to seamlessly combine predictive modeling and data, which can be invaluable in a data-poor environment. As a step towards integrated data analysis at scale, we present a new, fast integrated analysis framework that allows for the simultaneous reconstruction of the kinetic profiles and the magnetic equilibrium with statistically relevant uncertainties included. This analysis framework allows for the systematic evaluation of models using extensive experimental data leveraging DOE supercomputing infrastructure, such as being developed through the DOE-ASCR Integrated Research Infrastructure (Smith, XLOOP). To test the performance and verify the code it was applied to an ITER-like scenario using a realistic machine geometry and diagnostic description. Using artificial data for magnetics, Thomson scattering, interferometry, and polarimetry generated from a known ground truth, the coupled equilibrium and kinetic profile reconstruction problem was solved via the Maximum a posteriori method in approximately three minutes on a multicore CPU including uncertainty quantification. The resulting equilibrium and kinetic profiles were found to be in reasonable agreement with the ground truth. Show Chinese abstract

Abstract: 精确的等离子体状态重建对于ITER和未来聚变设施的成功至关重要，但燃烧等离子体的恶劣条件将使诊断操作比在当前设备中更具挑战性。基于贝叶斯推断的综合数据分析（IDA）通过使用复杂的前向模型将多种诊断的分析结合到一个步骤中，从而提高了信息获取能力。它还提供了一个框架，可以无缝结合预测建模和数据，这在数据匮乏的环境中可能非常有价值。作为大规模综合数据分析的一个步骤，我们提出了一种新的快速综合分析框架，该框架允许同时重建动力学剖面和磁平衡，并包含统计相关的不确定性。该分析框架允许利用DOE超级计算基础设施（如通过DOE-ASCR综合研究基础设施开发的）进行广泛的实验数据，对模型进行系统评估。为了测试性能并验证代码，将其应用于一个类似ITER的场景，使用了真实的机器几何形状和诊断描述。使用从已知真实值生成的磁测量、汤姆逊散射、干涉测量和偏振测量的人工数据，通过最大后验方法在多核CPU上大约三分钟内解决了耦合的平衡和动力学剖面重建问题，包括不确定性量化。结果表明，得到的平衡和动力学剖面与真实值有合理的吻合。