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

Fuente: arXiv

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Bibliographic Details
Main Authors:	Wang, Cong, Chen, Jiahong, Yang, Renjie, Li, Dong, Wang, Zhibin, Yang, Zongyu, Wang, Zhijun, Wei, Yixiong, Liu, Zhaoyang, Hu, Chenshu, Li, Jing
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
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_version_	1866910946714189824
author	Wang, Cong Chen, Jiahong Yang, Renjie Li, Dong Wang, Zhibin Yang, Zongyu Wang, Zhijun Wei, Yixiong Liu, Zhaoyang Hu, Chenshu Li, Jing
author_facet	Wang, Cong Chen, Jiahong Yang, Renjie Li, Dong Wang, Zhibin Yang, Zongyu Wang, Zhijun Wei, Yixiong Liu, Zhaoyang Hu, Chenshu Li, Jing
contents	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.
format	Preprint
id	arxiv_https___arxiv_org_abs_2502_08882
institution	arXiv
publishDate	2025
record_format	arxiv
spellingShingle	Integrated Data Analysis of Plasma Electron Density Profile Tomography for HL-3 with Gaussian Process Regression Wang, Cong Chen, Jiahong Yang, Renjie Li, Dong Wang, Zhibin Yang, Zongyu Wang, Zhijun Wei, Yixiong Liu, Zhaoyang Hu, Chenshu Li, Jing Machine Learning 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.
title	Integrated Data Analysis of Plasma Electron Density Profile Tomography for HL-3 with Gaussian Process Regression
topic	Machine Learning
url	https://arxiv.org/abs/2502.08882