用高斯过程融合多种数据，精准重建核聚变装置电子密度分布。
Integrated Data Analysis of Plasma Electron Density Profile Tomography for HL-3 with Gaussian Process Regression
- 结合激光干涉与雷达测点数据，用高斯过程实现二维密度重构。
- 重建误差低至3.60×10⁻⁴，磁通归一化下精度优异。
- 对网格、噪声等敏感性测试完备，适合真实实验应用。
针对HL-3托卡马克装置的等离子体电子密度剖面断层成像，提出一种基于高斯过程回归的综合数据分析模型。该模型融合远红外激光干涉仪的线积分测量与调频连续波后向散射雷达的点测量数据，利用高斯过程将点测量信息有效融入二维密度剖面重建，并通过坐标映射引入磁平衡信息。在归一化磁通条件下，重建剖面的平均相对误差仅为3.60×10⁻⁴。此外，对网格分辨率、诊断数据标准差及噪声水平进行了敏感性分析，为实际实验数据应用提供了可靠基础。
原文摘要 · Abstract (English)
An integrated data analysis model based on Gaussian Process Regression is proposed for plasma electron density profile tomography in the HL-3 tokamak. The model combines line-integral measurements from the far-infrared laser interferometer with point measurements obtained via the frequency-modulated continuous wave reflectometry. By employing Gaussian Process Regression, the model effectively incorporates point measurements into 2D profile reconstructions, while coordinate mapping integrates magnetic equilibrium information. The average relative error of the reconstructed profile obtained by the integrated data analysis model with normalized magnetic flux is as low as 3.60*10^(-4). Additionally, sensitivity tests were conducted on the grid resolution, the standard deviation of diagnostic data, and noise levels, providing a robust foundation for the real application to experimental data.
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