Development of a neural network-based model for electron temperature inference via modelled and experimental argon spectra measured by x-ray crystal spectrometer with an extension to tungsten spectra on EAST

Accurate inference of electron temperature ( T _e ) profiles is essential for understanding energy transport and impurity dynamics in magnetic confinement fusion plasmas. Traditional spectral diagnostics based on satellite line ratios become unreliable in high- T _e regimes due to reduced line inten...

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Hlavní autoři:	Zichao Lin, Hongming Zhang, Fudi Wang, Jia Fu, Yongcai Shen, Shuyu Dai, Hailin Zhao, Kaixuan Ye, Guangle Lin, Yifei Jin, Bo Sun, Shengyu Fu, Zixuan Wen, Zihao Gao, Huajian Ji, Bo Lyu
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	IOP Publishing 2025-01-01
Edice:	Nuclear Fusion
Témata:	x-ray crystal spectrometer artificial neural networks electron temperature impurity profiles
On-line přístup:	https://doi.org/10.1088/1741-4326/ae130a
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