Integrated Data Analysis of Plasma Electron Density Profile Tomography for HL-3 with Gaussian Process Regression

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, we performed sensitivity tests on grid resolution, diagnostic data systematic errors and noise levels, and robustness validation across diverse magnetic configurations and density profiles. This comprehensive assessment provides a robust foundation for the real application to experimental data.