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Sponsored AI Networking Cookbook: Practical recipes for AI-assisted network automation and development AI Networking Cookbook: Practical recipes for AI-assisted network automation and development

Author

Zheng-Xiong Wang

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3 papers indexed here

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Open access Sep 2026

Enhanced physics-informed neural networks for Vlasov–Poisson simulations

Kinetic theory is one of the fundamental descriptions in plasma physics. Large-scale numerical simulations for kinetic models such as the non-relativistic Vlasov–Poisson system and the Vlasov–Maxwell system are computationally demanding. To save computer resources, this work uses physics-informed neural network (PINN)...

Yuan Fang, Feng Wang, Q. Luan et al. · 1 citation
Preprint Aug 2026

State-Space Model-Enabled Reinforcement Learning for Magnetic Configuration Controlon EXL-50U

Accurate feedback control of the plasma current ($I_p$) and centroid position $(R_c,Z_c)$ is essential for the stable operation of spherical torus (ST) plasmas. Conventional proportional-integral-derivative (PID) controllers require extensive manual tuning and struggle with the fast, strongly coupled dynamics that aris...

Peixin Guo, Zhengyuan Chen, Jianguo Chen et al. · 0 citations
Open access Sep 2026

Fourier-enhanced separable physics-informed neural networks for plasma kinetic simulations

Numerical results show that the improved PINN method can accurately capture time evolution of the distribution function and electric field, which are consistent with theoretical analysis and conventional numerical codes.

Yuan Fang, Feng Wang, Q. Luan et al. · 0 citations

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