English 
Italiano 
Homogeneity and low divergence are required for high-energy negative ion beams that will be used to heat and sustain the plasma of future nuclear fusion reactors. To characterize these large-size negative ion beam properties, for future ITER Heating Neutral Beam, non-invasive and high temporal and spatial resolution diagnostics are fundamental. A tomographic diagnostic consisting of 15 visible cameras is installed on SPIDER, the full-size prototype of the ITER negative ion source. It allows reconstructing the entire 2D emissivity pattern of SPIDER negative ion beam, starting from the visible light emitted by the beam particles propagating in the background gas. To improve the tomographic reconstruction technique several inversion algorithms as well as a priori assumptions are investigated. In this work, the Simultaneous Algebraic Reconstruction Technique (SART) algorithm already used to characterize SPIDER beam in the 28 beamlets configuration is improved, to increase the information obtained through tomographic inversion, as the position of the beamlets. The performances in terms of Root Mean Square (RMS), mean reconstruction error and maximum error of the SART algorithm are compared with that of Maximum-likelihood Expectation-Maximization (ML-EM) algorithm, both on experimental and simulated data, the latter with the entire beam composed of 1280 beamlets.
In a world increasingly facing new challenges at the forefront of plasma scientific research and technological innovation, CNR and ISTP pledge progress and achieve an impact in the integration of research into societal practices and policy
