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Next Step Fusion Publications

We're driven to advance fusion towards commercialization and to benefit humanity. While we can't always publish or present results from commercial customer projects, we always aim to share more about our technologies and work.

If you see anything you'd like to discuss, please contact us.

  • PUBLICATIONS

  • Validation of NSFsim as a Grad-Shafranov Equilibrium Solver at DIII-D

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  • Reconstruction-free magnetic control of DIII-D plasma with deep reinforcement learning

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  • Electromagnetic System Conceptual Design for a Negative Triangularity Tokamak

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  • Reconstructing the Plasma Boundary with a Reduced Set of Diagnostics

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  • [APS DPP 2024] Summary report from the mini-conference on Digital Twins for Fusion Research

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  • POSTERS

  • [EPS 2024] Validation and Verification of Synthetic Magnetic Diagnostics Based on Free Boundary Equilibrium Solver for DIII-D Plasma Control System

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  • [EPS 2024] Electromagnetic System Conceptual Design for a Negative Triangularity Tokamak

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  • [EEML 2024] Magnetic feedback control of DIII-D tokamak via deep reinforcement learning

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  • [APS DPP 2024] NSFsim Validation as a DIII-D Plasma Equilibrium Simulator

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  • [OSSFE 2025] Developing a State-Oriented Plasma Control System

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  • [EPS 2025] NSFsim Code for Machine Design and Scenario Development

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  • [EPS 2025] Design and Implementation of a Reinforcement Learning-based Plasma Shape Controller at DIII-D

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  • [EPS 2025] Fusion Twin Platform: An Innovative Tool for Fusion Research and Education

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  • PRESENTATIONS

  • Plasma Control Online Meetup - May 6th, 2025

    Plasma Control Online Meetup videos:
    1. Georgy Subbotin (Next Step Fusion), "Controlling fusion plasma with reinforcement learning"
    2. Adriano Mele (Swiss Plasma Center at EPFL), "Case Study: Application of Model Predictive Control to the Plasma Shape in TCV"
    3. Sara Dubbioso (Consorzio CREATE), "Data-driven and model free approaches for magnetic control"
    4. Vacslav Glukhov (Next Step Fusion), "Multi-Objective Optimization and Control of Plasma States"

    Watch

  • [PhDiaFusion 2025] Novel tools for tokamak design and control

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  • [AI4X 2025] Magnetic control of tokamak plasma through deep reinforcement learning with privileged information

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  • OTHER

  • Tech Blog

    Our tech blog is a valuable source of information about our work and our thoughts on the fusion industry.

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  • LinkedIn

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