Special Issue on Machine Learning, Data Science, and Artificial Intelligence in Plasma Research

This Special Issue of the IEEE Transactions on Plasma Science (TPS) follows the first American Physical Society Division of Plasma Physics (APS-DPP) mini-conference on Machine Learning, Data Science, and Artificial Intelligence in Plasma Research held during the 60th APS-DPP Meeting in Portland, OR, USA (November 5–9, 2018). It contains selected highlights from not only the mini-conference but also the broader plasma physics community. Although data science has a long and rich history in plasma physics, dating back at least three decades, it is experiencing a renaissance, thanks in large part to the advances outside of plasma physics. Novel algorithms, hardware, and analytic techniques (buoyed by the open source software ecosystem) have led plasma scientists to explore ways in which the data revolution could accelerate and inform scientific discovery. Emerging data-driven methods could have a transformative effect across the full spectrum of plasma research. For fusion energy research, some areas of opportunities [item 1) in the Appendix] include using machine learning (ML) or data methods for scientific discoveries, augmented instrumentation, accelerated model development and simulations, data-informed intelligent controls of the experiment, and data-enhanced predictions. The DPP mini-conference and the articles herein represent only a tiny cross section of contemporary research on data-driven plasma science. The 3
^rd
International Conference on Data-Driven Plasma Science (ICDDPS-3) will be held in Okinawa, Japan, in April 2020 [item 2) in the Appendix], with expected presentations on fusion plasmas and low-temperature plasmas and beyond. Furthermore, Plasma Science is not unique in its exploration of Scientific Machine Learning: the Second Workshop on Machine Learning and the Physical Sciences (NeurIPS 2019, Vancouver, BC, Canada, December 2019) and it illustrates a trend in cross disciplinary collaboration with contributions from plasma research.