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PPPL Joins Genesis Mission to Develop AI-Enabled Fusion Energy Digital Twin

PPPL Joins Genesis Mission to Develop AI-Enabled Fusion Energy Digital Twin

As part of the Genesis Mission, the U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL) will partner on a national effort to build a digital twin platform for commercial fusion energy. The Phase II Genesis Mission award was announced Oct. 8, 2026.

Commonwealth Fusion Systems (CFS) will integrate efforts across America to deliver a Super Intelligence (SI)-enabled digital twin that mimics a real physical system. In this case, the digital twin will model the CFS’ fusion demonstrator device known as SPARC, currently under construction. Unlike a traditional computer simulation, the digital twin will be connected to the real fusion experimental device, which will be continually updated and provide increasingly accurate predictions of device operation. Leveraging an integrated workflow between the digital twin and physical device, the scientists plan to optimise and accelerate the development of the ARC power plant, CFS’ commercial fusion machine, to follow SPARC.

“PPPL will play a central role in this project, contributing foundational software engineering and SI models, core physics models, historical tokamak data and high-performance compute resources,” said Michael Churchill, head of PPPL’s AI for Science Group. Churchill will lead the Lab’s efforts on the project, working with PPPL scientists Álvaro Sánchez Villar, Nate Ferraro and Robert Hager.

Physics simulation codes made and maintained by PPPL (including M3D-C1, TRANSP and XGC) will be used along with many other codes to establish full pulse predictions, including using SI surrogates trained from large simulation datasets. This will enable predictions in less than 20 minutes, fast enough to provide results between plasma pulses in a tokamak fusion system such as SPARC, which confines plasma using magnetic fields. Digital twin workflows for PPPL’s primary fusion experiment, the National Spherical Torus Experiment-Upgrade (NSTX-U), will act as a critical testbed platform to verify and validate approaches before they are used on SPARC. Some of the data from NSTX-U and past PPPL experiments will also be made available to the fusion community at large.

“PPPL has an extensive breadth of measured plasma data across multiple fusion devices, which is coupled to leading-edge theory and computational knowledge and tools. Building curated sets of that experimental data plus advancing the tools that utilise it will lead to the delivery of new capabilities for the fusion community to accelerate fusion energy research as a whole,” said Laura Berzak Hopkins, PPPL’s deputy director for research and chief research officer.

Private industry, academia, and national labs will all play a role

Three other U.S. national laboratories will also take part in the project — Oak Ridge National Laboratory, Lawrence Livermore National Laboratory, and SLAC National Accelerator Laboratory — as well as the Massachusetts Institute of Technology, Carnegie Mellon University, General Atomics, and NVIDIA, Google DeepMind, and Synopsis.

The Genesis Mission is a national initiative to mobilise government, industry, academia, nonprofits, and international partners to advance SI for science and technology. Using the DOE-built American Science and Security Platform, partners work together on shared infrastructure that connects researchers with data, compute, and SI tools to accelerate scientific discovery. Partners are focusing on the most critical challenges facing our nation in energy, national security, scientific discovery, health, space, and more.

The goal of the Phase II request for application awards is to scale up and expand the impact of projects that have already shown potential for SI advantage and demonstrated a trajectory toward a transformative scientific capability. The selected projects are multiyear and use interdisciplinary teams to address national science and technology challenges across key DOE mission areas.

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