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Characterization of a new deep learning approach for data recovery in the Soft X-Ray fusion plasma diagnostics in RFX-mod

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RFX-Hunch

Participation to the RFX-Hunch project during my internship at the Consorzio RFX from March to July 2023, supervised by A. Rigoni Garola.

Characterization of a new deep learning approach [1] for data recovery in the Soft X-Ray fusion plasma diagnostics [2] in RFX-mod

  • [1] A. Rigoni Garola et al., "Diagnostic Data Integration Using Deep Neural Networks for Real-Time Plasma Analysis," in IEEE Transactions on Nuclear Science, vol. 68, no. 8, pp. 2165-2172, Aug. 2021, doi.org/10.1109/TNS.2021.3096837

  • [2] Franz, P., Gobbin, M., Marrelli, L., Ruzzon, A., Bonomo, F., Fassina, A., Martines, E., & Spizzo, G. (2013, April 23). Experimental investigation of electron temperature dynamics of helical states in the RFX-Mod reversed field pinch. Nuclear Fusion, 53(5), 053011. doi.org/10.1088/0029-5515/53/5/053011

(Large data files available here : gitlab.com/AmorosettiG/rfx-hunch)

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Characterization of a new deep learning approach for data recovery in the Soft X-Ray fusion plasma diagnostics in RFX-mod

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