Researchers at UW–Madison are taking part in a new collaboration built on open-science principles that will use machine learning to advance knowledge of promising sources of magnetic fusion energy, according to a recent press release.
The U.S. Department of Energy has selected the collaboration, led by researchers at the Massachusetts Institute of Technology, to receive nearly $5 million over three years. The teams — including researchers at UW–Madison, William & Mary, Auburn University, and the HDF group (a nonprofit data management technology organization) — are tasked with creating a platform to publicly share data they glean from several unique fusion devices and optimize that data for analysis using artificial intelligence tools. Student researchers from each institution will also have an opportunity to participate in a subsidized summer program that will focus on applying data science and machine learning to fusion energy.
The data sources will include UW–Madison’s Pegasus-III experiment, which is centered around a fusion device known as a spherical tokamak. Pegasus-III is a new Department of Energy-funded experiment that began operations in summer 2023 and represents the latest generation in a long-running set of tokamak experiments at UW–Madison. A primary goal of the experiment is to study innovative ways to start up future fusion power plants.
The collaboration is based around the principles of open science — the wealth of data coming from Pegasus-III and other fusion experiments will become more accessible and usable to others, particularly for machine learning platforms. UW–Madison is also supporting a broader push to diversify the fusion field. Some of the student researchers who will be participating in the new collaboration are part of the student-led Solis group, which provides gender-inclusive support for students studying plasma physics on campus.
