A Machine Learning Method for the Optimization Design of Laser Pulse in Fast Ignition Simulations
Authors (first, second and last of 7)
Collection
Machine Learning Applications Enabling Fusion Energy
Over the last few years, machine learning helped to develop advanced capabilities for fusion energy over a broad range of domains. This includes advanced algorithms to extract information from fusion diagnostics, enhanced algorithms for plasma state estimation and control, accelerated simulation tools to improve predictive capabilities, and expanded modeling capabilities for fusion materials design.
This topical collection covers recent developments in machine learning applied research further enabling the path to fusion energy. The topical collection aims to reflect the current state of the field across the board of fusion subfields – from inertial confinement fusion, to magnetically confined plasma, including basic plasma research, as well as materials design and high temperature superconductors. The collection will also provide a critical outlook on how machine learning can be used in the future to accelerate the development of fusion energy as a reliable energy source.
Editors
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Cristina Rea (Plasma Science and Fusion Center, MIT, USA)
Dr. Rea, a research scientist and working group leader at MIT Plasma Science and Fusion Center, integrates machine learning algorithms with plasma control systems to address the challenge of disruptive tokamak plasmas. She works with scientists at Alcator C-Mod, DIII-D, EAST, and TCV facilities on machine learning applications for plasma stability. Dr Rea is the PSFC Disruptions Group leader and a key contributor to SPARC design and ITER research. Dr Rea further organizes the PSFC Computational Physics School for Fusion Research, focusing on High Performance Computing, Parallel Programming, Computational Statistics, and Machine Learning.
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Alessandro Pau
EPFL / Swiss Plasma Center (PPB-115) Station 13, Lausanne, Switzerland
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Ralph Kube
Princeton Plasma Physics Laboratory, Princeton, NJ, USA
