A neural network for fluctuation analysis in plasma tomography

Le résumé fourni par la source

Tomography serves as an advanced diagnostic tool for analyzing plasma fluctuations and turbulence. However, it requires time-consuming calculations, which impede rapid analysis. Integrating a neural network into tomography offers a potential solution. In this work, we present a trial conducted on a tomography system installed on the Plasma Assembly for Nonlinear Turbulence Analysis, a cylindrical plasma device designed for plasma turbulence research. This article reports on the optimization process of a neural network algorithm and on its excellent properties for tomographic reconstruction, including the extraction of plasma fluctuation properties. The neural network-aided tomography is 25 times faster than and provides comparable accuracy to, the standard algorithm, Maximum Likelihood Expectation Maximization.

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