{
  "abstract": "A new approach to tokamak magnetic control enabling high-precision plasma shaping and novel real-time adaptability is experimentally demonstrated on the Tokamak a Configuration Variable (TCV). The method is motivated by the insight that, under appropriate assumptions, a real-time inverse Grad-Shafranov solver approximates an optimal control policy for plasma boundary regulation. Building on this, a control architecture is developed in which classical controllers enforce operational constraints while a fast surrogate model provides a real-time inverse mapping from the desired plasma boundary to Poloidal Field Coil currents. Experimental results on TCV demonstrate improved plasma shaping with respect to the standard discharge preparation procedure --- albeit without explicit real-time shape feedback --- while enabling flexible response to asynchronous events. It is shown that a single network provides satisfactory performance across a range of plasma magnetic configurations. Real-time adaptivity is demonstrated in simulation, and partially in experiment, through adaptive strike point motion and early termination in response to a real-time trigger. These results suggest a viable path toward magnetic control architectures that reduce reliance on dense diagnostic coverage while maintaining high-accuracy plasma shaping, with potential relevance for future fusion power plant operation.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2608.23976",
  "author_total": 15,
  "authors": [
    {
      "name": "Allen M. Wang"
    },
    {
      "name": "Adriano Mele"
    },
    {
      "name": "Cosmas Heiß"
    },
    {
      "name": "Cristian Galperti"
    },
    {
      "name": "Zander Keith"
    },
    {
      "name": "Alessandro Pau"
    },
    {
      "name": "Antoine Merle"
    },
    {
      "name": "Olivier Sauter"
    },
    {
      "name": "Daniel Gonzalez Castiñeiras"
    },
    {
      "name": "Francesco Carpanese"
    },
    {
      "name": "Federico Felici"
    },
    {
      "name": "Mark Dan Boyer"
    },
    {
      "name": "Cristina Rea"
    },
    {
      "name": "TCV Team"
    },
    {
      "name": "EUROfusion Tokamak Exploitation Team"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/7vbw6cs00ngss.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2608.23976",
  "fulltext_url": null,
  "id": "7vbw6cs00ngss",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2608.23976",
  "language": null,
  "licence": "LicenseRef-arXiv-nonexclusive-1.0",
  "licence_label": "arXiv licence",
  "licence_source": "article",
  "licence_url": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "physics.plasm-ph"
    ],
    [
      "openalex",
      "3106|Magnetic confinement fusion research"
    ]
  ],
  "openalex": "W7204247978",
  "pdf_url": "https://arxiv.org/pdf/2608.23976",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-01",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/7vbw6cs00ngss.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:18:00Z",
      "native_id": "2608.23976",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2608.23976"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "arxiv:physics.plasm-ph",
      "subfield": "plasma"
    }
  ],
  "title": "An Inverse Grad-Shafranov Neural Network Approach to Tokamak Magnetic Control",
  "title_text": "An Inverse Grad-Shafranov Neural Network Approach to Tokamak Magnetic Control",
  "type": "preprint",
  "updated_at": "2026-10-30T12:18:00Z",
  "url": "https://research.draconitic.com/paper/7vbw6cs00ngss",
  "venue": "arXiv",
  "versions": []
}