Machine Learning for Plasma Physics and Fusion Energy
The ability of modern experimental and computational plasma science to generate large quantities of complex data, combined with advances in mathematics, analytics and computation, has motivated researchers to explore the application of advanced statistical techniques to problems of plasma science. Such technologies include machine learning (ML), artificial intelligence (AI), dataset generation and curation, and predictive analytics, in both experimental and simulation contexts. Additionally, increased emphasis on ML and related technologies from funding agencies and the continued growth in general scientific machine learning has led to significant interest and activity within the plasma science community. This special issue collects numerous contributions to the Mini-conference on Machine Learning, Data Science, and Artificial Intelligence in Plasma Research from the 63rd Annual Meeting of the APS Division of Plasma Physics, as well as other contributed manuscripts.
Submission deadline: 31 May 2022
Special Issue Editor
Bill Dorland, University of Maryland
Communicating Scientists
Jeph Wang, Los Alamos National Laboratory
Ralph Kube, Princeton Plasma Physics Laboratory
Luc Peterson, Lawrence Livermore National Laboratory
Cristina Rea, Massachusetts Institute of Technology
Research Article
Towards fast and accurate predictions of radio frequency power deposition and current profile via data-driven modelling: applications to lower hybrid current drive
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- Journal of Plasma Physics / Volume 88 / Issue 4 / 2022
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- 18 August 2022, 895880401
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Statistical characterization of experimental magnetized liner inertial fusion stagnation images using deep-learning-based fuel–background segmentation
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- Journal of Plasma Physics / Volume 88 / Issue 5 / 2022
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- 15 September 2022, 895880501
Data augmentation for disruption prediction via robust surrogate models
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- Journal of Plasma Physics / Volume 88 / Issue 5 / October 2022
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- 04 October 2022, 895880502
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Database-wide hazard modelling of the onset of DIII-D tearing modes with field features
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- Journal of Plasma Physics / Volume 88 / Issue 5 / 2022
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- 17 October 2022, 895880503
Data-driven model for divertor plasma detachment prediction
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- Journal of Plasma Physics / Volume 88 / Issue 5 / October 2022
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- 21 October 2022, 895880504
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Nonlinear excitation of geodesic acoustic mode by reversed shear Alfvén eigenmodes in non-uniform plasmas
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- Journal of Plasma Physics / Volume 88 / Issue 6 / December 2022
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- 17 November 2022, 895880601
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Machine-learning-based models in particle-in-cell codes for advanced physics extensions
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- Journal of Plasma Physics / Volume 88 / Issue 6 / December 2022
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- 07 December 2022, 895880602
Plasma image classification using cosine similarity constrained convolutional neural network
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- Journal of Plasma Physics / Volume 88 / Issue 6 / December 2022
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- 16 December 2022, 895880603
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Data-driven model discovery for plasma turbulence modelling
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- Journal of Plasma Physics / Volume 88 / Issue 6 / 2022
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- 14 December 2022, 895880604
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Optimizing the configuration of plasma radiation detectors in the presence of uncertain instrument response and inadequate physics
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- Journal of Plasma Physics / Volume 89 / Issue 1 / 2023
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- 06 January 2023, 895890101
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A general infrastructure for data-driven control design and implementation in tokamaks
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- Journal of Plasma Physics / Volume 89 / Issue 1 / 2023
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- 17 January 2023, 895890102
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Transfer learning as a method to reproduce high-fidelity non-local thermodynamic equilibrium opacities in simulations
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- Journal of Plasma Physics / Volume 89 / Issue 1 / February 2023
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- 17 January 2023, 895890103
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Research on plasma vertical displacement calculation based on neural network
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- Journal of Plasma Physics / Volume 89 / Issue 1 / February 2023
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- 17 January 2023, 895890104
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In search of a data-driven symbolic multi-fluid ten-moment model closure
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- Journal of Plasma Physics / Volume 89 / Issue 1 / 2023
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- 03 March 2023, 895890105
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Unsupervised classification of fully kinetic simulations of plasmoid instability using self-organizing maps (SOMs)
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- Journal of Plasma Physics / Volume 89 / Issue 3 / 2023
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- 29 May 2023, 895890301
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