Big data requirements in current and next fusion research experiments

Manduchi, G.; Luchetta, A.; Taliercio, C.; Rigoni, A.

doi:10.1109/iscas.2018.8351712

Cited by 1 publication

(2 citation statements)

References 7 publications

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“…Fusion is a big-data science, and future experiments will generate a significant amount of experimental data [172]. However, the majority of this data will be unlabeled or may have few labels.…”

Section: Other Opportunitiesmentioning

confidence: 99%

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Machine learning and Bayesian inference in nuclear fusion research: an overview

Pavone

Merlo

Kwak

et al. 2023

Plasma Phys. Control. Fusion

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This article reviews applications of Bayesian inference and machine learning in nuclear fusion research. Current and next-generation nuclear fusion experiments require analysis and modelling eﬀorts that integrate diﬀerent models consistently and exploit information found across heterogeneous data sources in an eﬃcient manner. Model-based Bayesian inference provides a framework well suited for the interpretation of observed data given physics and probabilistic assumptions, also for very complex systems, thanks to its rigorous and straightforward treatment of uncertainties and modelling hypothesis. On the other hand, machine learning, in particular neural networks and deep learning models, are based on black-box statistical models and allow the handling of large volumes of data and computation very eﬃciently. For this reason, approaches which make use of machine learning and Bayesian inference separately and also in conjunction are of particular interest for today’s experiments and are the main topic of this review. This article also presents an approach where physics-based Bayesian inference and black-box machine learning play along, mitigating each other’s drawbacks: the former is made more eﬃcient, the latter more interpretable.

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Section: Other Opportunitiesmentioning

confidence: 99%

“…Traditional local storage solutions may have to be reconsidered in future fusion experiments [172]. The long duration of the plasmas, along with the significant use of camera-based diagnostics, will generate a vast amount of experimental data to store.…”

Section: Other Opportunitiesmentioning

confidence: 99%