Fusion and Plasma Physics Studies

Neueste Paper

• Multi-Agent Design Assistant for the Simulation of Inertial Fusion Energy

  Meir H. Shachar (Lawrence Livermore National Laboratory Livermore, CA, USA), Dane M. Sterbentz (Lawrence Livermore National Laboratory Livermore, CA, USA), Harshitha Menon (Lawrence Livermore National Laboratory Livermore, CA, USA), Charles F. Jekel (Lawrence Livermore National Laboratory Livermore, CA, USA), M. Giselle Fern\'andez-Godino (Lawrence Livermore National Laboratory Livermore, CA, USA), Nathan K. Brown (Sandia National Laboratories Albuquerque, NM, USA), Ismael D. Boureima (Los Alamos National Laboratory Los Alamos, NM, USA), Yue Hao (Lawrence Livermore National Laboratory Livermore, CA, USA), Kevin Korner (Lawrence Livermore National Laboratory Livermore, CA, USA), Robert Rieben (Lawrence Livermore National Laboratory Livermore, CA, USA), Daniel A. White (Lawrence Livermore National Laboratory Livermore, CA, USA), William J. Schill (Lawrence Livermore National Laboratory Livermore, CA, USA), Jonathan L. Belof (Lawrence Livermore National Laboratory Livermore, CA, USA) · 23. September 2026

  Inertial fusion energy promises nearly unlimited, clean power if it can be achieved. However, the design and engineering of fusion systems requires controlling and manipulating matter at extreme energies and timescales; the shock physics and radiation transport governing the physical behavior under …

• A Practitioner's Guide to Kolmogorov-Arnold Networks

  Amir Noorizadegan, Sifan Wang, Leevan Ling, Juan P. Dominguez-Morales · 8. Mai 2026

  Kolmogorov-Arnold Networks (KANs), whose design is inspired-rather than dictated-by the Kolmogorov superposition theorem, have emerged as a structured alternative to MLPs. This review provides a systematic and comprehensive overview of the rapidly expanding KAN literature. The review is organized …

• A Practitioner's Guide to Kolmogorov-Arnold Networks

  Amir Noorizadegan, Sifan Wang, Leevan Ling, Juan P. Dominguez-Morales · 16. April 2026

  Kolmogorov-Arnold Networks (KANs), whose design is inspired-rather than dictated-by the Kolmogorov superposition theorem, have emerged as a structured alternative to MLPs. This review provides a systematic and comprehensive overview of the rapidly expanding KAN literature. The review is organized …

• A Practitioner's Guide to Kolmogorov-Arnold Networks

  Amir Noorizadegan, Sifan Wang, Leevan Ling, Juan P. Dominguez-Morales · 16. April 2026

  Kolmogorov-Arnold Networks (KANs), whose design is inspired-rather than dictated-by the Kolmogorov superposition theorem, have emerged as a structured alternative to MLPs. This review provides a systematic and comprehensive overview of the rapidly expanding KAN literature. The review is organized …

• Challenges and opportunities for AI to help deliver fusion energy

  Adriano Agnello, Helen Brooks, Cyd Cowley, Iulia Georgescu, Alex Higginbottom, Richard Pearson, Tara Shears, Melanie Windridge · 30. März 2026

  There is great potential for the application of AI tools in fusion research, and substantial worldwide benefit if fusion power is realised. However, using AI comes with its own challenges, many of which can be mitigated if responsible and robust methodologies are built into existing approaches. To d…

• A Practitioner's Guide to Kolmogorov-Arnold Networks

  Amir Noorizadegan, Sifan Wang, Leevan Ling, Juan P. Dominguez-Morales · 6. Januar 2026

  Kolmogorov-Arnold Networks (KANs), whose design is inspired-rather than dictated-by the Kolmogorov superposition theorem, have emerged as a structured alternative to MLPs. This review provides a systematic and comprehensive overview of the rapidly expanding KAN literature. The review is organized …

• A Practitioner's Guide to Kolmogorov-Arnold Networks

  Amir Noorizadegan, Sifan Wang, Leevan Ling, Juan P. Dominguez-Morales · 6. Januar 2026

  Kolmogorov-Arnold Networks (KANs), whose design is inspired-rather than dictated-by the Kolmogorov superposition theorem, have emerged as a structured alternative to MLPs. This review provides a systematic and comprehensive overview of the rapidly expanding KAN literature. The review is organized …

• A Practitioner's Guide to Kolmogorov-Arnold Networks

  Amir Noorizadegan, Sifan Wang, Leevan Ling · 11. Dezember 2025

  The so-called Kolmogorov-Arnold Networks (KANs), whose design is merely inspired, rather than dictated, by the Kolmogorov superposition theorem, have emerged as a promising alternative to traditional Multilayer Perceptrons (MLPs). This review provides a systematic and comprehensive overview of the r…

• A Practitioner's Guide to Kolmogorov-Arnold Networks

  Amir Noorizadegan, Sifan Wang, Leevan Ling · 11. Dezember 2025

  The so-called Kolmogorov-Arnold Networks (KANs), whose design is merely inspired, rather than dictated, by the Kolmogorov superposition theorem, have emerged as a promising alternative to traditional Multilayer Perceptrons (MLPs). This review provides a systematic and comprehensive overview of the r…

• A Practitioner's Guide to Kolmogorov-Arnold Networks

  Amir Noorizadegan, Sifan Wang, Leevan Ling · 31. Oktober 2025

  Kolmogorov-Arnold Networks (KANs) have recently emerged as a promising alternative to traditional Multilayer Perceptrons (MLPs), inspired by the Kolmogorov-Arnold representation theorem. Unlike MLPs, which use fixed activation functions on nodes, KANs employ learnable univariate basis functions on e…